presentation topic on ai

65+ Topics In Artificial Intelligence: A Comprehensive Guide To The Field

Jane Ng • 24 Jul 2023 • 6 min read

Welcome to the world of AI. Are you ready to dive into the 65+ best topics in artificial intelligenc e and make an impact with your research, presentations, essay, or thought-provoking debates?

In this blog post, we present a curated list of cutting-edge topics in AI that are perfect for exploration. From the ethical implications of AI algorithms to the future of AI in healthcare and the societal impact of autonomous vehicles, this “topics in artificial intelligence” collection will equip you with exciting ideas to captivate your audience and navigate the forefront of AI research.  

Table of Contents

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• Key Takeaways

FAQs About Topics In Artificial Intelligence

Here are topics in artificial intelligence that cover various subfields and emerging areas:

• AI in Healthcare: Applications of AI in medical diagnosis, treatment recommendation, and healthcare management.
• AI in Drug Discovery : Applying AI methods to accelerate the process of drug discovery, including target identification and drug candidate screening.
• Transfer Learning: Research methods to transfer knowledge learned from one task or domain to improve performance on another.
• Ethical Considerations in AI: Examining the ethical implications and challenges associated with the deployment of AI systems.
• Natural Language Processing: Developing AI models for language understanding, sentiment analysis, and language generation.
• Fairness and Bias in AI: Examining approaches to mitigate biases and ensure fairness in AI decision-making processes.
• AI applications to address societal challenges.
• Multimodal Learning: Exploring techniques for integrating and learning from multiple modalities, such as text, images, and audio.
• Deep Learning Architectures: Advancements in neural network architectures, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

Here are topics in artificial intelligence suitable for presentations:

• Deepfake Technology: Discussing the ethical and societal consequences of AI-generated synthetic media and its potential for misinformation and manipulation.
• Cybersecurity: Presenting the applications of AI in detecting and mitigating cybersecurity threats and attacks.
• AI in Game Development: Discuss how AI algorithms are used to create intelligent and lifelike behaviors in video games.
• AI for Personalized Learning: Presenting how AI can personalize educational experiences, adapt content, and provide intelligent tutoring.
• Smart Cities: Discuss how AI can optimize urban planning, transportation systems, energy consumption, and waste management in cities.
• Social Media Analysis: Utilizing AI techniques for sentiment analysis, content recommendation, and user behavior modeling in social media platforms.
• Personalized Marketing: Presenting how AI-driven approaches improve targeted advertising, customer segmentation, and campaign optimization.
• AI and Data Ownership: Highlighting the debates around the ownership, control, and access to data used by AI systems and the implications for privacy and data rights.

• AI-Powered Chatbot for Customer Support: Building a chatbot that uses natural language processing and machine learning to provide customer support in a specific domain or industry.
• AI-Powered Virtual Personal Assistant: A virtual assistant that uses natural language processing and machine learning to perform tasks, answer questions, and provide recommendations.
• Emotion Recognition : An AI system that can accurately recognize and interpret human emotions from facial expressions or speech.
• AI-Based Financial Market Prediction: Creating an AI system that analyzes financial data and market trends to predict stock prices or market movements.
• Traffic Flow Optimization: Developing an AI system that analyzes real-time traffic data to optimize traffic signal timings and improve traffic flow in urban areas.
• Virtual Fashion Stylist: An AI-powered virtual stylist that provides personalized fashion recommendations and assists users in selecting outfits.

Here are the topics in artificial intelligence for the seminar:

• How Can Artificial Intelligence Assist in Natural Disaster Prediction and Management?
• AI in Healthcare: Applications of artificial intelligence in medical diagnosis, treatment recommendation, and patient care.
• Ethical Implications of AI: Examining the ethical considerations and responsible development of AI Systems.
• AI in Autonomous Vehicles: The role of AI in self-driving cars, including perception, decision-making, and safety.
• AI in Agriculture: Discussing AI applications in precision farming, crop monitoring, and yield prediction.
• How Can Artificial Intelligence Help Detect and Prevent Cybersecurity Attacks?
• Can Artificial Intelligence Assist in Addressing Climate Change Challenges?
• How Does Artificial Intelligence Impact Employment and the Future of Work?
• What Ethical Concerns Arise with the Use of Artificial Intelligence in Autonomous Weapons?

Here are topics in artificial intelligence that can generate thought-provoking discussions and allow participants to critically analyze different perspectives on the subject.

• Can AI ever truly understand and possess consciousness?
• Can Artificial Intelligence Algorithms be Unbiased and Fair in Decision-Making?
• Is it ethical to use AI for facial recognition and surveillance?
• Can AI effectively replicate human creativity and artistic expression?
• Does AI pose a threat to job security and the future of employment?
• Should there be legal liability for AI errors or accidents caused by autonomous systems?
• Is it ethical to use AI for social media manipulation and personalized advertising?
• Should there be a universal code of ethics for AI developers and researchers?
• Should there be strict regulations on the development and deployment of AI technologies?
• Is artificial general intelligence (AGI) a realistic possibility in the near future?
• Should AI algorithms be transparent and explainable in their decision-making processes?
• Does AI have the potential to solve global challenges, such as climate change and poverty?
• Does AI have the potential to surpass human intelligence, and if so, what are the implications?
• Should AI be used for predictive policing and law enforcement decision-making?

Here are 30 essay topics in artificial intelligence:

• AI and the Future of Work: Reshaping Industries and Skills
• AI and Human Creativity: Companions or Competitors?
• AI in Agriculture: Transforming Farming Practices for Sustainable Food Production
• Artificial Intelligence in Financial Markets: Opportunities and Risks
• The Impact of Artificial Intelligence on Employment and the Workforce
• AI in Mental Health: Opportunities, Challenges, and Ethical Considerations
• The Rise of Explainable AI: Necessity, Challenges, and Impacts
• The Ethical Implications of AI-Based Humanoid Robots in Elderly Care
• The Intersection of Artificial Intelligence and Cybersecurity: Challenges and Solutions
• Artificial Intelligence and the Privacy Paradox: Balancing Innovation with Data Protection
• The Future of Autonomous Vehicles and the Role of AI in Transportation

Here topics in artificial intelligence cover a broad spectrum of AI applications and research areas, providing ample opportunities for exploration, innovation, and further study.

• What are the ethical considerations for using AI in educational assessments?
• What are the potential biases and fairness concerns in AI algorithms for criminal sentencing?
• Should AI algorithms be used to influence voting decisions or electoral processes?
• Should AI models be used for predictive analysis in determining creditworthiness?
• What are the challenges of integrating AI with augmented reality (AR) and virtual reality (VR)?
• What are the challenges of deploying AI in developing countries?
• What are the risks and benefits of AI in healthcare?
• Is AI a solution or a hindrance to addressing social challenges?
• How can we address the issue of algorithmic bias in AI systems?
• What are the limitations of current deep learning models?
• Can AI algorithms be completely unbiased and free from human bias?
• How can AI contribute to wildlife conservation efforts?

Key Takeaways 

The field of artificial intelligence encompasses a vast range of topics that continue to shape and redefine our world. In addition, AhaSlides offers a dynamic and engaging way to explore these topics. With AhaSlides, presenters can captivate their audience through interactive slide templates , live polls , quizzes , and other features allowing for real-time participation and feedback. By leveraging the power of AhaSlides, presenters can enhance their discussions on artificial intelligence and create memorable and impactful presentations. 

As AI continues to evolve, the exploration of these topics becomes even more critical, and AhaSlides provides a platform for meaningful and interactive conversations in this exciting field.

What are the 8 types of artificial intelligence?

Here are some commonly recognized types of artificial intelligence:

• Reactive Machines
• Limited Memory AI
• Theory of Mind AI
• Self-Aware AI
• Superintelligent AI
• Artificial Superintelligence

What are the five big ideas in artificial intelligence?

The five big ideas in artificial intelligence, as outlined in the book “ Artificial Intelligence: A Modern Approach ” by Stuart Russell and Peter Norvig, are as follows:

• Agents are AI systems that interact with and impact the world. 
• Uncertainty deals with incomplete information using probabilistic models. 
• Learning enables AI systems to improve performance through data and experience. 
• Reasoning involves logical inference to derive knowledge. 
• Perception involves interpreting sensory inputs like vision and language.

Are there 4 basic AI concepts?

The four fundamental concepts in artificial intelligence are problem-solving, knowledge representation, learning, and perception. 

These concepts form the foundation for developing AI systems that can solve problems, store and reason with information, improve performance through learning, and interpret sensory inputs. They are essential in building intelligent systems and advancing the field of artificial intelligence.

Ref: Towards Data Science | Forbes | Thesis RUSH  

A writer who wants to create practical and valuable content for the audience

More from AhaSlides

• Last updated March 22, 2024
• In AI Origins & Evolution

14 Best Presentations On Artificial Intelligence And Machine Learning

• Published on January 3, 2018
• by Jeevan Biswas

For a quick overview of a subject or a breakdown of concepts, SlideShare serves as a go-to platform for many. The recapitulations found in many of the presentations are both concise and informative.

The most popular presentations are the ones that have received the most number of likes and have been viewed more than the other presentations in a particular category.

AIM brings you the 14 most popular presentations on Artificial Intelligence, Machine Learning. Deep Learning and everything else in between.

Best AI PPT and Topics in 2024

1) artificial intelligence and law overview.

• 2)  What is Artificial Intelligence – Artificial Intelligence Tutorial For Beginners

3) Why Social Media Chat Bots Are the Future of Communication

4) ai and the future of work, 5) ai and machine learning demystified, 6) study: the future of vr, ar and self-driving car, 7) artificial intelligence, 8) solve for x with ai: a vc view of the machine learning & ai landscape, 9) deep learning – the past, present and future of artificial intelligence.

• 10) The Future Of Work & The Work Of The Future

11) Asia’s Artificial Intelligence Agenda

12) 10 lessons learned from building machine learning systems, 13) design ethics for artificial intelligence, 14) artificial intelligence.

People who are not aware of what artificial intelligence is will find the topic presented in a very simple manner here.

Along with the explanation of what AI is, the two major approaches towards AI are discussed– logic and rules-based approach, and machine learning approach. Special emphasis on the machine learning approach can be seen in the slides devoted to its detailed examination. The examination goes beyond the rudimentary explanation of what machine learning is and presents examples of proxies that seem like machine learning but are not.

The presentation lists examples of AI in the field of law and identifies some of the limitations of AI technology.

2)  What is Artificial Intelligence – Artificial Intelligence Tutorial For Beginners

For the uninitiated, this presentation offers an ideal rundown of AI. The question of AI being a threat is raised at the very beginning. However, as the presentation progresses, it discusses the basics necessary for understanding AI. The most basic question of what is artificial intelligence is answered.

A brief history of AI and the discussion on recent advances in the field of AI is also found. The various areas where AI currently sees practical application have been listed. Fascinating uses that AI can be put to in the future are also found in the presentation. The two approaches of achieving AI, machine learning and deep learning, is touched upon.

All in all, this presentation serves as a simple introduction to AI.

An exciting application of AI can be found in chatbots. Here, the limitless scope of chatbots is explored. The various milestones reached by leading players  in bot technology such as Facebook, Skype and KIK are enumerated.

The evolution of chatbots and its absorption of more AI in the future is also looked into. E-Commerce is touted as the biggest beneficiary of the advancement in chatbots and that bot technology will owe its rise to services and commerce.

Two tech giants, Facebook and Google, have been pitted against each other based on their ongoing developments in this area and the question of who will emerge as the best is raised.

This presentation talks about the far-fetching applicability of AI and ML,and the perils of that applicability. In order to derive a better understanding of this presentation, it is advisable to first watch the original talk.

During the course of the presentation, many examples of how machines can learn and perform any human task that is repetitive in nature are cited.

Other possibilities suggested include the creation of new unheard jobs for human beings as a result of aggressive use of AI and other allied technologies. Qualities that are characteristic only of human beings, may be the basis on which these jobs will be created is also suggested.

It concludes with a message- Ride the train, don’t jump in front of it.

In this presentation, Carol Smith establishes that AI cannot replace humans. Smith conveys that AI can serve the purpose of enabling human beings in making better decisions.

The slides talk about how the actions of AI are the result of the human inputs going into its programming. An AI’s bias is not its own, but the human bias with which it has been programmed, is emphasised on.

Other issues such as the need for regulations and other considerations within it that require deliberation are also touched upon. The presentation leaves you with a message – Don’t fear AI, Explore it.

Though no descriptive breakdown of topics related to AI is found, the presentation offers interesting numerical insights into many questions. Statistics on three main subjects – artificial intelligence, virtual reality and wearable technology, is provided here.

A variety of questions and the numerical representations of their responses are found under four main categories:

• Will you  purchase a self-driving car when they become available?
• Are you concerned with the rise of Artificial Intelligence?
• Is wearable technology part of your daily life?
• Do you own or intend to purchase a Virtual Reality headset in the next twelve months?

From consumer opinions to overall consensus of countries, the numbers show current trends and the possible trends in the future based on increasing development in the mentioned technologies.

There are many who have been introduced to AI only recently due to the buzz surrounding it and may not be aware of the early developments that led to its current status.

This presentation from 2009 offers a simple yet informative introduction to the rudiments of AI. AI’s history and a timeline of all the significant milestones in AI up to 2009 can be found. The presentation also provides an introduction to AI programming languages such as LISP and PROLOG.

For those who would like to have a crash course on the basics of AI in order to catch up with it current trends, this presentation serves the purpose.

While the concepts of  AI or ML are not spoken about, light is shed on other important aspects of it. The presentation discusses about how many known tech giants such as Google are bolstering their AI capabilities through mergers and acquisitions.

The role of venture capital(VC) in the landscape of AI and machine learning,and the involvement of VC in the firms that were acquired are mentioned.

Another point highlighted is how large companies are moving towards ML and re-configuring themselves around ML, and how it is not a US-centric phenomenon. Key points have been expressed in the form of self-explanatory graphical representations. Rounding off the presentation is the possible direction that ML can take and a few pointers on achieving success in ML.

This presentation provides a comprehensive insight into deep learning. Beginning with a brief history of AI and introduction to basics of machine learning such as its classification, the focus shifts towards deep learning entirely.

Various kinds of networks such as recurrent neural nets and generative adversarial networks have been discussed at length. Emphasis has been given to important aspects of these networks and other mechanisms such as natural language processing (NLP).

Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first time learner’s of AI to comprehend.

10) The Future Of Work & The Work Of The Future

The subject of self-learning of robots and machines is explored here. Talking about the fictional Babel fish, it is suggested that the advancements in technology leading to improved learning and translations by machines  made the Babel fish a near-real entity.

New ‘power’ values such as speed, networked governance, collaboration and transparency, among others, have been put forth and juxtaposed against older ones that are not fully technology  driven.

Going against the popular assumption that robots and machines will replace human beings, the presentation proposes that we are on the brink of the largest job creation period in humanity.

This presentation is a briefing paper by the MIT Technological Review and talks about how the global adoption of AI is being sped up by Asian countries. It suggests that Asia will not only benefit greatly from the rise in AI technology, but will also define it.

The data collected for the review has been summarized in the form of simple info-graphics. They are a numerical reflection of the mood surrounding the adoption of AI across different industries and how it could possibly impact human capital.  The review also suggests that while there is awareness about AI in Asia, only a small percentage of companies are investing in it.

Pointers for business leaders in Asia to capitalize on AI is offered in the end along presentation with an info-graphic timeline of the history of AI.

Download review report in pdf

While they are two separate presentations, they talk about the same subject- machine learning. The presentations are a summary of the analysis of machine learning adopted by two platforms, Netflix and Quora.

In case of Netflix, emphasis has been given to the choice of the right metric and the type of data used for testing and training. It also emphasises the need to understand the dependence between the data used and the models employed. The advice to optimize only areas that matter is offered.

The second presentation on Quora, talks about teaching machines only what is necessary. It stresses on the need the to focus on feature engineering and being thoughtful about the ML infrastructure. Another point it highlights is the combination of supervised and unsupervised being the key in ML application.

With 135 slides, this presentation provides an exhaustive insight into the creation of an ethically sound AI. An introduction to the subject of User Experience(UX) design is followed by the rules that have to be considered during the designing process.

The chronological progression of UX, beginning with experience design and ending with intelligence design, and the direction in which this process is headed is also discussed.

Supported by powerful visuals, the presentation touches upon many essential considerations such as nature of intelligence, purpose of existence, awareness of self and the need for which the AI is created.

It raises a pertinent point that while creating AI, human beings are creating something that embodies qualities that they lack.

Made for a school competition in 2009, it provides many examples of cutting-edge applications of AI at the time.

Many of the examples, such as mind controlled prosthetic limbs, Ultra Hal Assistant and Dexter- the robot provide a trip down the AI memory lane where the applications of AI seemed like a page out of a sci-fi novel. It presents a list of areas where AI can assist human beings.

It concludes with  a series of questions, some of which, are still being debated. Such as machines replacing human beings’ and human unemployment due to the use of machines.

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A guide to creating Artificial Intelligence presentations

Get your team on prezi – watch this on demand video.

Anete Ezera October 26, 2023

Artificial Intelligence (AI) is all the talk now. You can find Artificial Intelligence presentations, articles, books, and other sources to learn about it. Ultimately, AI is no longer confined to a niche group of tech experts and intellectuals; it has become a widely discussed topic. When discussing what AI is all about or introducing a new AI functionality, it’s important to present it with the same innovative enthusiasm that surrounds the subject. That’s why in this article, we’ll delve into the topic of AI and provide tips on how to make your presentations on AI topics highly captivating and engaging.

Why Artificial Intelligence presentation topics have become so popular

Artificial Intelligence excites us because it’s changing our world in big ways. From self-driving cars and virtual helpers to health checks, AI is everywhere in our daily lives. It’s pushing new ideas, making things more efficient, and helping in decision-making across many fields.

Businesses are leveraging AI to gain a competitive edge, healthcare professionals are harnessing it to save lives, and educators are using it to enhance learning experiences. As a result, AI has become a hot topic in boardrooms, labs, and classrooms worldwide.

Understanding Artificial Intelligence

Artificial Intelligence (AI) lets computers perform tasks typically requiring human cognitive abilities. This includes understanding language, spotting trends, tackling problems, and making smart choices. AI achieves this by analyzing extensive datasets and using intelligent algorithms. 

Here are some examples of AI you may encounter on a day-to-day basis:

Delivery robots

AI-driven delivery robots have become increasingly common, like those from Serve Robotics in the US to bring online orders to customers’ doors. These robots rely on AI to navigate streets and sidewalks, avoid obstacles, and ensure they deliver orders on time.

AI voiceovers for video editing

AI has entered the realm of video production, allowing for polished voiceovers. Many have noticed on social media that AI can turn written words into lifelike speech, improving videos without relying on human narrators.

Virtual assistants

Virtual assistants like Siri and Alexa exemplify AI’s role in daily life. They understand and respond to natural language commands, assisting users with tasks such as setting reminders, answering questions, and controlling smart devices.

Healthcare diagnostics

AI is crucial in healthcare as it helps analyze medical visuals such as X-rays and MRIs, spotting diseases early on. It also helps doctors by sifting through vast amounts of patient information to guide treatment choices.

AI customer service

Have you ever tried to contact a company and encountered a pop-up typing robot in the corner of your screen? This is likely one of the AI forms that many of us have come across. AI customer service has revolutionized the way businesses deal with customer inquiries. 

The practical uses of AI, like the examples shown above, come from processing large amounts of data and applying advanced algorithms, showing how AI can improve different parts of our daily lives.

What is an Artificial Intelligence presentation? 

An AI presentation aims to teach the audience about a part of AI that suits their field or interests. These presentations break down the confusing stuff about AI to make it easy for everyone to understand. They share helpful ideas, show real-life examples, and explain how AI is changing different areas. With high-quality images, engaging structure, and useful examples, AI presentations help people see why AI is important and how it can be useful. They encourage people to talk about AI and understand what it’s all about.

Creating an engaging Artificial Intelligence presentation

If you’re planning to create a presentation on AI, follow these steps: 

Choose an AI topic

Choosing the right AI topic is your first step. Think of it as setting the stage for your Artificial Intelligence presentation. Here’s how to navigate this:

• Audience relevance: Your chosen topic should resonate with your audience. Consider their interests, needs, and expectations. If you’re presenting to a healthcare audience, delve into “Artificial Intelligence in healthcare.” For tech enthusiasts, explore “AI in emerging technologies.” The goal is to make your Artificial Intelligence presentation relatable and valuable to your specific audience.
• Hot topics: AI is a vast field, so stay updated on the latest trends and hot-button issues. Ethical considerations, AI’s impact on the job market, and its role in shaping the future are all intriguing angles. Don’t be afraid to think outside the box and explore uncharted territory.
• Industry relevance: If you’re representing a particular industry, tailor your topic accordingly. For instance, if you’re in the finance sector, consider “AI in financial services.” Highlight how AI solutions are transforming and improving that specific field.

Explore examples of Artificial Intelligence topics for presentations

• AI in healthcare: You could explore how Artificial Intelligence transforms the healthcare industry, from medical diagnosis to drug discovery and patient care.
• Ethical considerations in AI: Delve into the ethical challenges posed by AI, including issues related to bias, privacy, and job displacement.
• AI and education: You could discuss how AI is revolutionizing education, from personalized learning experiences to automating administrative tasks in schools and universities.
• AI in business: Explore how businesses are leveraging AI for tasks like data analysis, customer service, and process automation, leading to improved efficiency and decision-making.
• AI in finance: You could examine the impact of AI on the financial sector, including algorithmic trading, fraud detection, and customer service in banking.
• AI and autonomous vehicles: Discuss the role of AI in self-driving cars and its potential to revolutionize transportation.
• Natural language processing (NLP): Dive into NLP and its applications, such as chatbots, sentiment analysis, and language translation.
• AI in robotics: Explore how AI is driving advancements in robotics, leading to applications in manufacturing, healthcare, and more.
• AI and creativity: You could discuss how AI is being used in creative fields like art, music, and literature, generating unique and innovative content.
• The future of AI: Predict where AI is headed in the coming years, including its potential impact on society, jobs, and technology.

3. Craft your presentation

Once you’ve chosen your Artificial Intelligence topic, it’s time to create the presentation. Make sure to follow these tips to craft a highly engaging story:

Try Prezi AI presentation maker

What better tool to use to create an Artificial Intelligence presentation than an AI presentation maker –  Prezi AI . Prezi AI intelligent features streamline the presentation creation process, taking care of time-consuming layout tweaks. This ensures your presentations are polished, professional, and captivate your audience. Prezi AI empowers you to transform ideas into captivating presentations with an intuitive and efficient workflow. Try it out now!

Engaging introduction

Your presentation should start with a bang. Hook your audience from the get-go with a compelling introduction. Share a fascinating AI-related fact, an attention-grabbing quote, or a relatable anecdote. Capture their curiosity right from the beginning.

Visual appeal

Remember that a picture is worth a thousand words. Utilize visuals such as graphs, charts, diagrams, and images to illustrate your key points. Visual aids not only enhance understanding but also keep your audience visually engaged. Make complex AI concepts visually digestible.

Real-world examples

Ground your Artificial Intelligence presentation in the real world by incorporating concrete examples and case studies. Share success stories where AI made a significant impact. Use these examples to demonstrate how AI isn’t just a theoretical concept but a practical solution that brings tangible benefits.

Relevance focus

In the vast landscape of AI, stay focused on what’s most relevant to your audience. Avoid overwhelming them with overly technical details. Instead, tailor your content to address the aspects that directly affect their lives or work. Explain how AI is a solution to real-world challenges.

Final thoughts

When wrapping up your presentation on Artificial Intelligence, aim to leave a lasting impression on your audience. Make sure they reflect on the insights you’ve shared. Here’s how to craft a memorable ending:

• Highlight the essentials: Briefly go over the primary messages from your presentation. This strengthens the main ideas for your audience, making them more memorable.
• Stimulate reflection: Prompt your audience with questions that make them think deeply about the content they’ve just heard. Aim for questions that promote discussion and challenge their viewpoints.
• Present a future outlook: Describe what the future might hold with AI’s continued growth and its potential effects on our lives. Inspire your audience to look forward with excitement and wonder about the possibilities ahead.
• End with an inspiring quote: Conclude your presentation with an inspiring quote related to AI or innovation. A well-chosen quote can leave a lasting impression and motivate your audience to explore AI further.
• Call to action: Encourage your audience to take action. Whether it’s suggesting further reading, inviting questions, or proposing a challenge related to AI, give your audience a clear next step to engage with the topic.

Creating an AI presentation that resonates with your audience depends on these two key steps. By choosing the right topic and crafting your presentation thoughtfully, you’ll educate your audience in a captivating way, leaving them with a deeper understanding and appreciation for the exciting world of Artificial Intelligence. 

Why choose Prezi for Artificial Intelligence presentations?

When it comes to sharing the magic of AI with your audience, Prezi stands out for a handful of reasons. 

Captivating visuals

Imagine telling your AI story with a tool that weaves a dynamic, non-linear narrative. Prezi lets you craft visually stunning presentations that’ll impress your audience. Think of it as the key to making complex AI concepts not only understandable but also captivating.

Smooth transitions

Prezi’s zoomable canvas and cinematic transitions make the presentations even more engaging. You can seamlessly zoom in for detail and pan out for the big picture. This makes your presentation journey much more captivating to follow.

Templates to jumpstart creativity

Don’t want to start from scratch? No problem. There are plenty of customizable presentation templates to choose from. By creating your presentation from a template, you’ll save valuable time and effort. Also, you’ll be able to focus more on the content of your AI topic, making sure it comes across the way you intend it to. 

Storyboard for structure

Prezi’s storyboard function is an excellent choice for your AI presentation. Rather than having a block of slides, Prezi lets you lay out your topics visually. You might begin with AI’s history, move to its use in various sectors with real-life instances, and end with what’s next for AI. It helps you design an engaging and coherent narrative for your viewers.

Prezi AI: Your go-to tool for AI presentations

Prezi AI is an innovative tool that leverages the power of artificial intelligence to streamline the presentation creation process. It empowers users of all skill levels to craft compelling and impactful presentations in a fraction of the time it would take using traditional methods. By automatically generating content, suggesting design elements, and offering personalization options, Prezi AI removes the guesswork from presentation design, allowing you to focus on delivering your message with confidence. Whether you’re a seasoned professional or a student embarking on your first presentation, Prezi AI can be your secret weapon for creating presentations that leave a lasting impression.

Artificial Intelligence presentation example

Still, wondering how Prezi can boost your AI presentation game? Take a look at the following presentation AI presentation by David Vandegrift . This presentation offers an easy-to-follow history and definition of AI, presented in a way that leaves a memorable impression. You can use the outline of this presentation to spark creative ideas for your own Artificial Intelligence presentation.

A glimpse into the future of AI

The future of Artificial Intelligence is brimming with possibilities that promise to reshape our world in profound ways. As AI continues to evolve at an unprecedented pace, here are some exciting areas to explore:

Emerging applications

AI’s potential extends far beyond what we see today. Imagine:

• Personalized medicine:  AI could revolutionize healthcare with personalized diagnostics, treatment plans, and even preventative measures tailored to individual patients.
• Climate change solutions:  AI can play a crucial role in developing sustainable solutions by analyzing climate data, optimizing energy use, and even designing more efficient renewable energy technologies.
• Space exploration:  AI-powered robots and spacecraft could venture further into the cosmos, assisting with tasks like exploration, resource discovery, and even establishing a permanent human presence on other planets.

Human-AI collaboration

The future of work won’t be about humans versus machines, but rather humans and AI working together. AI can handle repetitive tasks and complex data analysis, freeing up human minds for creative problem-solving, strategic thinking, and tasks requiring social intelligence.

The rise of AGI (Artificial General Intelligence)

While still a distant possibility, some experts believe AI could eventually reach a level of intelligence comparable to humans, known as Artificial General Intelligence (AGI). This would bring about a paradigm shift in our understanding of intelligence and consciousness, requiring careful consideration of the ethical implications.

Ethical frameworks

As Artificial Intelligence becomes more sophisticated, the need for robust ethical frameworks to guide its development and deployment becomes paramount. These frameworks will need to address issues like bias, transparency, accountability, and the potential impact of AI on human rights and freedoms.

The future of AI holds immense potential for progress and positive change. By embracing AI responsibly and fostering human-AI collaboration, we can create a future where AI empowers us to solve complex challenges, improve our lives, and explore the vast unknown.

Make your AI presentations more engaging with Prezi

AI has got our attention, and there’s already a sea of AI presentations out there. As you’re looking to create a presentation on an AI topic, remember to make sure it’s as engaging as the topic itself. With Prezi AI , you can create your AI presentation in minutes and weave a narrative that not only educates your audience about AI but also leaves them inspired by its boundless possibilities.

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21 Artificial Intelligence Seminar Topics For 2024 (with examples)

⏱️ First Published: September 17, 2022 | Last Updated : November 25, 2023

We last updated this article on 25th November to replace 19 AI seminar topic ideas that are trending and more specific to the AI field. Also, we have included research references for each topic so you can study further.

If you’re a college student looking for final-year project ideas or struggling to find interesting artificial intelligence seminar topics, this listicle guide is for you.

As an AI developer, I understand the current trends and AI presentation topics that will stand out from your classmates.

After days of research through Google Scholar, asking ChatGPT, and exploring the latest AI projects, I have created this list of 21 AI seminar topics for 2024.

The best part?

You will also find free resources for each AI topic so you can do your further research.

Before diving into the topics, let’s cover the basics first.

What is Artificial Intelligence?

Artificial Intelligence is a technology of making a computer or software intelligent enough to think like a human brain. So that machines can do human tasks more effectively and find better solutions than human minds.

These machines are mainly used for repetitive and complex human tasks but they can also think, learn, and improve their work performance, just like human beings.

AI research and seminar topics for 2024

Let’s explore the latest artificial intelligence (AI) seminar topics of 2024:

1. Generative AI in virtual reality

Gen AI is a type of artificial intelligence that can create new content (image, video, text, audio) based on what it has learned from the existing content. Specifically used for creative tasks like making art, music, and writing. All you need to do is feed it with data, and it uses its training to generate unique creative outputs.

However, the role of generative is not only limited to creating content. You can also use the technology in virtual reality and metaverse. In this seminar you can discuss the synergy between generative AI and VR, exploring the potential for transformative and personalized virtual experiences.

In this Gen AI seminar presentation, you can cover the following topics:

1. Generative Algorithms for VR Environments:

• Procedural generation
• Machine learning-based scene generation
• Adaptive content creation

2. Real-Time Adaptation:

• Based on user interactions, preferences, or external factors
• Enhancing user engagement and personalizing the VR experience

3. Immersive Storytelling:

• Dynamically generating story elements, characters, and plot developments
• Creating interactive and responsive storytelling experiences

4. User Experience and Interaction Design

• Enhancing engagement, presence, and overall satisfaction
• Discussing its role in interaction design within VR applications

5. Challenges and Future Directions

• Computational constraints, user feedback, and ethical considerations
• Explore potential future developments in the VR and generative technology landscape

6. Gen AI use cases and applications:

• Gaming, training simulations, architectural visualization, virtual tourism

Seminar references: 

• Generative AI Models and Extended Reality (XR) Content for the Metaverse  
• A curated list of modern Generative Artificial Intelligence projects and services

2. Transformers

Transformers are a type of neural network that work by using a self-attention mechanism and can generate human-like text. They are trained on massive amounts of text and code, and can be used for tasks like text summarization and answering questions.

Transformers can learn long-range dependencies in text, which means they can understand relationships between words that are far apart in a sentence. This is important for many NLP tasks, such as machine translation, where the meaning of a word can depend on the whole sentence. It is a must-attend seminar as it is still an active area of research and there are many opportunities to contribute to the field.

Project references:

• 100 incredible projects built in the vicinity of transformers.
• Introduction to Transformers

3. Deep Learning in Healthcare

Deep learning comes from the family of machine learning but with the advancement of making predictions by learning the stored data and analyzing it. In recent years, deep learning has become one of the most popular topics in the field of artificial intelligence (AI). 

The reason being the success of deep learning in many different applications,such as vision, natural language processing, and robotics. 

Here’s a note from an AI developer who worked on this project:

If you’re interested in choosing the seminar topic ‘deep learning in healthcare, you will need to consider highlighting topics on CNN, transfer learning, and metrics precision. Different models of neural networks (such as ResNet, DenseNet, Xception, etc.) are fundamental to know. Also, you will need a clear idea of which model you will use for the research and study. Pro tip: If you can show the implementation of different algorithms on your dataset and their results, it will be easy for others to understand which algorithm is suitable for which situation When presenting something related to healthcare, it will be a little tricky because your approach needs to be noble, making it easy-to-detect diseases that will help doctors. When your approach can compete with manual detection or a long-time process of tests, then only it will be considered a noble approach. — Contributed by Shrabana Saha (AI software developer)

Project references: Identification of Coronavirus & Pneumonia from Chest x-ray Scans using Deep Multilayered CNN

4. Generative Adversarial Networks

GANs are a type of machine learning model that can be used to generate realistic data. The model works by training two neural networks against each other: a generator and a discriminator. The generator tries to create fake data, while the discriminator’s job is to tell real from fake, and by doing so they improve over time and generate very realistic and creative content.

GANs are an interesting topic for seminars as they can be used to generate realistic images and videos. Also, GANs are relatively new, which means there is still a lot of active research going on.

Project references: GAN applications and demonstrations

5. Graph Neural Networks (GNNs)

GNNs are a type of artificial intelligence technology that helps us understand and process data structured as graphs. They are used to represent connections between things, like social networks or molecular structures to analyze and learn, making them useful for recommendation systems, identifying patterns, and solving complex problems. To use GNNs, you’d start with a graph dataset, create a GNN model, and train it to make predictions or gain insights from the connections within the data.

Project references: 

• Financial fraud detection using graph neural networks
• What are GNNs and how do they work  

6. Reinforcement Learning

Reinforcement Learning is a type of machine learning where the model makes decisions and improves its performance through trial and error. To execute RL, you set up a learning environment, and define actions and rewards, and the agent learns by taking actions and receiving feedback.

It’s like teaching a dog tricks; they learn by doing and getting treats when they do well, which makes it a powerful method for training AI systems.

Project references: Introduction to Reinforcement Learning with David Silver, DeepMind

7. Explainable AI

Explainable AI (XAI) is a way to make AI systems understandable to humans. It can help us to answer questions like “How does this AI system work?” and “Why did it make that decision?” Therefore, it can help us to trust AI systems and make better decisions because we understand their predictions. XAI is a quickly growing field with a wide range of potential applications. We will see even more innovative and impactful applications of XAI in the future.

Project references: From Artificial Intelligence to Explainable Artificial Intelligence in Industry 4.0: A Survey on What, How, and Where

Automated Machine Learning is a technology that automates the process of building and optimizing machine learning models. It empowers non-experts to create effective AI solutions without in-depth knowledge. To use AutoML, you typically select a dataset, choose the type of task you want to perform (e.g., classification or regression), and let the system automatically handle model selection, hyperparameter tuning, and optimization. This simplifies AI development, making it accessible to a broader audience, and can save a lot of time and effort in building machine learning models.

• Bank Customer Churn Prediction using H2O (AutoML)
• How Tesla uses ai technologies to build autonomous cars  

9. Artificial Neural Networks 

Seminars on this topic tend to elaborate on the processing of data by computer programs that resemble the way human brains draw connections. This has been a huge savior for many sectors and companies by solving complex issues within shorter spans.

Hence, just as biological neurons form a big part of a science student’s curriculum, ANNs are major topics for AI enthusiasts. 

• Applied Deep Learning- ANN – the architecture and how they can be applied
• Autonomous Navigation Project on Artificial Neural Networks

10. Ensemble Techniques

Ensemble Techniques typically involve combining multiple models to improve the overall accuracy. It is like asking a team of experts to make a prediction, and then averaging out their answers. You just create a team of models, such as decision trees or neural networks, and use techniques like bagging or boosting to combine their results. The final prediction of the ensemble model would likely be more accurate than the prediction of any individual model.

This is because the ensemble model is able to leverage the strengths of each individual model, while mitigating their weaknesses.

• https://www.youtube.com/watch?v=TAm1iW2yeVY
• Ensemble techniques for software change prediction

11. Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are a type of artificial neural network that can process sequential data. They work by processing data one step at a time. At each step, the RNN takes the current input and its previous state to produce a new output and a new state. The new state is then used to process the next input.

This process is repeated until the end of the input sequence. At the final point, the RNN’s output is the final prediction. This allows RNNs to make predictions that are based on the entire input sequence, not just the current input.

• Predicting Popularity of Open Source Projects Using Recurrent Neural Networks

12. Recommender System

Have you wondered how your feed automatically aligns with your social media interests? Well, this is the recommender system. Learners often get curious about such day-to-day life topics and turn to seminars and workshops to get their queries answered.

In addition, recommender systems fall under the machine learning model and employ strategies to track user preferences.

• A systematic review and research perspective on recommender system

13. Natural Language Processing

Your Google Assistant or the Amazon Alexa form in this very category of natural language processing applications. These machines are programmed to mimic human speech or text and respond to it aptly.

Students attending seminars on this can better understand how these machines not only understand the text and speech but also reciprocate with meaning and advancement. 

Project references: Medical Natural Language Processing Project

14. Transfer Learning

Transfer learning is a technique in which a pre-trained model (BERT, GPT-3, ResNet, etc) is used on a new task. This is handy for people working on real-world machine learning projects who don’t have a lot of data or who find it difficult to train a model from scratch. We take the already learned model and adjust it to fit the new task, which is easier than starting from scratch.

Visual representation of the model’s working : (timestamp 2:18 to 5:12)

Project references: Using Transfer Learning for Code-Related Tasks

15. Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are a type of artificial neural network that is particularly well-suited for image recognition and classification tasks. CNNs work by breaking down images into small pieces and then learning to identify patterns in those pieces. It makes a very interesting topic for a seminar as it is one of the most successful types of machine learning models for image recognition and classification tasks and is relatively easy to understand and implement.

• Real-Time classification of Plankton species using Convolutional Neural Networks
• Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python)  

16. Computer Vision

Computer Vision is a unique field of artificial intelligence that deals with deriving information from visual inputs like images. Students can learn how these computers are trained to understand the image and derive from it a result in as little time as possible. The system operates with cameras and other data inputs to achieve accurate results. 

You can also extend this seminar topic to pattern recognition— which is a closely related concept of computer vision and machine learning. 

Pattern recognition is about identifying and classifying the data based on previous inputs to predict a pattern. Common examples may include speech recognition and speaker identification, commonly discussed in seminars.

Pattern recognition project idea: Work on developing an AI system that can recognize and diagnose plant diseases based on images of plant leaves. For this you will need to collect a diverse dataset of images featuring healthy plants and various diseased conditions. Include common plant diseases like rust, powdery mildew, and blight.

This way, you can train the machine to identify the pattern in images of leaves. 

• Real-Time Computer Vision Project with OpenCV
• Using Deep Learning for Image-Based Plant Disease Detection  
• Pattern recognition and image analysis

17. Autoencoders

Autoencoders are a type of neural network used in artificial intelligence that can take complex data, like images or text, and simplify it into a compact code. Then, they can unscramble this code to reconstruct the original data and hence the name. Autoencoders are used in various applications, like image denoising, compression, and even recommendation systems, where they help find things you might like based on your past preferences and this is why many learners are propelled to this topic after getting enough information. 

Project references:  

• AutoEncoders Explained  
• Image Denoising using AutoEncoders -A Beginner’s Guide

18. You Only Look Once

You Only Look Once (YOLO) is a real-time object detection algorithm that has gained popularity in recent years. It is a single-stage algorithm which means that it can detect objects in a single pass of the image. This makes it very fast and efficient, making it ideal for real-time applications such as video surveillance and self-driving cars. It makes an interesting topic for a seminar because it is a state-of-the-art object detection algorithm that is used in a wide variety of applications and also a relatively easy algorithm to understand, making it a good choice for students.

• Object Detection Using YOLO YOLO Algorithm for Object Detection Explained [+Examples]

19. Semi-Supervised Learning

Semi-supervised learning (SSL) is a type of machine learning that uses a small amount of labeled data and a large amount of unlabeled data to train a model.

It is an interesting topic for a seminar because it allows us to train models on large datasets without having to label all of the data, which can be very time-consuming and expensive. Seminars conducted on this topic are precisely made to teach the extensive working of this relatively new field.

Project references: Semi-supervised learning: A brief review

20. AI-Powered Chatbots for Social Good

AI-powered chatbots are computer programs that can talk like humans. Used as a substitute for professional help as the bots can talk, offer emotional support, and suggest coping strategies. 

Attending such a seminar can help in building a good professional network and learn about responsible AI development and deployment.

Project references: Chatbot for mental health

21. Robotic Process Automation

Robotic Process Automation (RPA) is a technology that allows businesses to automate repetitive and rule-based tasks. RPA bots can mimic human actions to perform tasks such as data entry, order processing, and customer service. In seminars dealing with this, students understand how RPA is shaping the future of work and its potential when integrated with AI to transform the way businesses operate.

RPA project idea: Intelligent Document Processing (IDP) with RPA 

In this project you can develop an RPA project that integrates IDP to automate the extraction and processing of information from unstructured documents. The goal of this project will be to streamline document-intensive processes in various industries— which results in enhancing efficiency and reducing manual labor.

• RPA and the future Workforce
• https://arxiv.org/ftp/arxiv/papers/2112/2112.14070.pdf  

FURTHER RESOURCES ON AI CAREER:

• Artificial Intelligence Documentaries
• How Can DevOps Teams Take Advantage of AI?
• Will AI replace software engineers?

How do I ensure my AI seminar topic is current and relevant?

Step 1: stay connected with ai experts.

Follow AI influencers and related hashtags on platforms like Twitter or LinkedIn for the latest news. Some notable influencers on Twitter include Yann Lecun , Yoshua Benjio , Geoffrey Hinton (who invented backpropagation), and Andrew Ng .

You can also use LinkedIn to find AI developers and professionals from a specific country or region.

Step 2: Read recent research and findings

Google your keyword on the ‘ Google Scholar ’ section to find the latest academic research and related publications. Check Google News for trending articles and industry updates. For instance, Here’s a screenshot of search results for ‘genai’. Top publications like Springer and arxiv show credibility and high-quality research.

Step 3: Type your keyword in Google Trends and see the search demand.

The below graph shows the search demand for the keyword ‘Generative AI.’

This will help you understand the demand of certain topics in the artificial intelligence domain. Also, you can find trending topics from Google Trends data.

Step 4: Find the industry demands

Review job postings on LinkedIn to see what skills or knowledge the tech industry is currently seeking in AI.

Carefully, read the job description and find the most common tools, technologies, and skills required in the AI field.

What tips do you have for presenting a successful AI seminar?

To give a great seminar, make sure the information is easy for everyone to understand, regardless of prior AI knowledge. Use visuals such as diagrams, charts, and graphs for better understanding. Ask questions and encourage people to join in. Finally, give a list of resources where they can learn more about AI.

What are some interesting final-year AI presentation topics for engineering students?

Based on my research through journals and research papers, I found the following AI presentation topics suitable for final year college students:

• Implementing neural networks for a specific application (e.g. image classification, speech recognition)
• Comparing different deep learning architectures
• AI for self-driving cars
• AI for robotics and controls
• Smart home automation with AI
• AI for predictive maintenance in manufacturing
• AI for financial forecasting and modeling
• AI security issues: threats and defenses
• AI in the cloud: opportunities and challenges

What are some good AI seminar topics for CSE final-year students?

If you’re a computer science engineering student you should pick seminar or presentation topics that are based on AI, data science, algorithms, and your technical skills (programming, project experience, etc.).

Below, I have shared 11 AI topics where you can showcase your technical core skills.

• Implementing chatbots using deep learning: focus on natural language processing and neural network architectures for developing conversational AI.
• Computer vision for facial recognition: explore techniques like CNNs and face detection frameworks like OpenCV.
• AI for self-driving cars: discuss sensor fusion, path planning, and decision making algorithms for autonomous vehicles.
• Text summarization and generation: use seq2seq models and attention for abstractive text summarization.
• AI for logistics and supply chain optimization: apply AI to optimize costs and routes in supply chains.
• Generative adversarial networks: implement GAN models for generating synthetic images, videos, and data.
• Reinforcement learning for games: train AI agents to play games like chess, go, and Atari using RL algorithms.
• Game theory: AI agents for games like chess, go, DOTA using min-max algorithms, alpha-beta pruning and heuristic search.
• Machine translation with neural networks: build an English-to-French neural machine translation model.
• Predictive maintenance with AI: use machine learning to predict equipment failures and guide maintenance.
• AI for fraud detection: apply anomaly detection and classification algorithms to detect bank fraud.

Learn about: CSE seminar topics

Final Words

If you’re serious about becoming an AI engineer, you should learn the fundamentals of artificial intelligence , AI career paths , branches , and current trends. Once you cover the basics, you can prepare your AI seminar presentation on any technical topics with ease.

Have any AI presentation topic ideas? Feel free to message me .

Tata Sai Nandini is an IT Professional with experience in the Python and Data Science domain. With expertise in Statistical Analysis, Exploratory Data Analysis, Data Visualization, Data Extraction, Data Wrangling, Image Processing, Text Processing, and the creation of Machine Learning and Deep Learning models, she is a versatile and skilled practitioner in the field. Tata Sai Nandini’s skillset encompasses a wide range of tools and technologies, including Python, C++, C, various IDEs, Python libraries, data visualization tools, and machine learning and deep learning frameworks.

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25+ AI PowerPoint Templates (For AI Presentations)

Artificial Intelligence (AI) is one of the most discussed topics around the world these days. If you’re also working on preparing a presentation related to AI, we have the perfect set of PowerPoint templates for your project.

Diving into the world of artificial intelligence can be complex, but presenting your findings or concepts doesn’t have to be. This post has been created to make your life easier by providing you with some of the best AI PowerPoint templates with cool technology-themed designs. These are ideal for designers and marketers who want to structure visually appealing and effective presentations on topics related to AI.

Whether you are a startup working on new AI tech or an agency promoting its AI-powered services, our list has templates to give your presentation a professional edge and make your audience dive deep into the futuristic world of artificial intelligence.

The PowerPoint templates in this collection range from both paid and free options, giving you the flexibility to choose what fits your needs the most. Have a look.

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Pitch Deck Templates

Startup pitch deck.

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Pitch PowerPoint

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Mystify Presentation

Explore PowerPoint Templates

AI Artificial Intelligence PowerPpoint Presentation

The AIONIC PowerPoint template is a unique and customizable slideshow designed for presentations related to artificial intelligence and technology. It features over 25 unique layouts, at 16:9 aspect ratio, and a high-resolution format of 1920×1080 pixels. Perfect for creating detailed pitch decks or marketing kits, the template is easy to use and provides numerous layout variations to choose from.

Artificial Intelligence PowerPoint Template

Avilon PowerPoint Template is a modern slideshow template for creating technology and AI-themed presentations. With 35 unique slides that are fully customizable, it allows users to easily switch up colors, text, and images. All graphics and shapes are resizable and editable, with various infographics and a 16:9 HD widescreen format included. You can use this template to create bold AI presentations that wow your audience.

Aizone – Artificial Intelligence PowerPoint Template

This PowerPoint template is an ideal choice for creating AI presentations with a futuristic theme. With 30 slides and an array of customizable graphics, it offers unique design elements and professional layouts. Users can easily edit content and images thanks to the drag-and-drop feature. It’s modern and visually appealing, ensuring an engaging presentation experience.

Prompt Artificial Intelligence PowerPoint Template

This is a versatile PowerPoint template ideal for those needing to create engaging presentations revolving around prompt engineering and AI technology. With 35 unique, high-resolution layouts available, the template is fully editable, allowing for a tailored approach to fit your brand. It comes with a set of stylish slides with a bold dark color theme as well.

Aexos – AI Tech Presentation PowerPoint Template

A PowerPoint template specially designed for tech enthusiasts who need to create engaging presentations related to AI. With 36 easily editable slides, users can simply drag and drop to create visually captivating presentations to articulate their tech narratives with precision. It includes free fonts, resizable shapes, icons, and much more as well.

SynthAI – AI PowerPoint Presentation Template

SynthAI is a creative PowerPoint template designed for creating sleek, modern presentations. With a focus on artificial intelligence, business, and technology, its fully editable slides give you the freedom of customization. It features a widescreen 16:9 ratio, useful data charts, and convenient drag and drop functionality.

AI Presentation – Technology PowerPoint Template

This is an expertly crafted PowerPoint template perfect for crafting striking presentations about artificial intelligence. With its modern design, 30 creative slides, standard and widescreen formats, and six color combinations, it is highly versatile for business and educational presentations or marketing purposes. Its customizable nature and impressive icons enhance its appeal significantly.

Artificial Intelligence AI PowerPoint Template

A modern, infographic-style PowerPoint template ideal for exploring vast topics related to AI. With 20 unique, editable slides boasting a 16x9HD, retina-ready resolution, this template touches on intriguing facets of AI such as machine learning, AI subfields, and their usages. It offers ten pre-made colour themes, detailed instructions, and the flexibility to customize your own theme.

AI Industry PowerPoint Presentation Template

A minimalist yet flexible PowerPoint template to assist you in producing engaging AI-themed presentations. Perfect for marketing, technology startups, and broad business usage, the package offers 30 easily editable slides in HD widescreen format (1920×1080 pixels). With this template, elements, colors, shapes, and charts can all be tailored to your context.

AI Technology Presentation Template for PowerPoint

A user-friendly PowerPoint template for creating professional AI-related presentations. Its elegant design, complete with gradient-style slides, flat colors, and a variety of infographics, is fully customizable and multipurpose. Its 30 clean and creative slide templates in HD 16:9 widescreen format are simple to use; all graphs are editable and customizable.

Futura – Modern AI Presentation Template

Futura is a modern PowerPoint template for creating top-notch presentations focusing on AI, VR, or other futuristic technologies. It’s adaptable for Powerpoint, Keynote, and Google Slides, and completely editable to suit any topic, like Security or Networking. The package includes 2400 total slides with 30 unique slides each, in five color themes, accommodating both dark and light backgrounds.

Stylish Artificial Intelligence PowerPoint Template

A sleek and modern PowerPoint template ideal for developers, researchers, and scientists wishing to create educational and visually appealing presentations. With 35 customizable slides, integrating graphics, diagrams, and images has never been easier. Predesigned with 16:9 HD widescreen slide format and editable fonts, this template effortlessly handles data representation and typography modifications.

Modern Artificial Intelligence PowerPoint Template

This PowerPoint template enriches your presentations with a sleek, contemporary design. This set of over 30 unique slides gives your content a polished look and features like an editable chart and elements deliver flexibility to cater to your presentation needs. Available in both light and dark versions, this AI-themed template enhances your business narratives, rendering them more engaging for your audience.

Blouniverse – Artificial Intelligence PowerPoint Template

A meticulously designed, ultra-modern PowerPoint template for AI-themed presentations. It presents a blend of usability and aesthetics across its 27 unique slides, tailored for a range of presentations from business to branding. The template features easy customizability, over a variety of vectors and icons, paired with free support and HD quality.

Neurimo – Artificial Intelligence AI PowerPoint Template

The Neurimo is a PowerPoint template designed for a wide range of tech-related presentations, including AI, augmented reality, and cryptocurrency. This professional and modern template features over 30 easily editable slides with resizable graphics, free web fonts, and a wide screen ratio. It’s intricately thought-out yet convenient to use, ensuring a powerful presentation every time.

Cognify – AI PowerPoint Presentation

The Cognify PowerPoint template provides a robust and user-friendly slideshow for AI-related presentations. Designed with over 30 unique slides that are easily customizable, this PowerPoint template fits a 16:9 widescreen ratio and includes picture placeholders.

Rebotech – Artificial Intelligence PowerPoint Template

This PowerPoint template offers a sleek, modern design for a variety of AI-related presentations. It includes a unique layout with editable infographics, graphs, and icons, suitable for market reviews, funding pitches, product analysis, and more. Additionally, it boasts a 16:9 wide-screen ratio and features like picture placeholders, vector icons, and easy editability.

Cyborge – AI PowerPoint Template

The Cyborge is an advanced, professionally styled PowerPoint template ideal for future technology presentations. It includes 30 unique, easy-to-use slides, presented in a trending style theme. The template features various slide layouts, including cover, portfolio, product, and contact slides, and a widescreen ratio of 16:9. All of these elements combine to create a presentation that will easily attract and engage your audience.

Metaspace – AI, Virtual Reality and Mataverse PPT

Metaspace is an adaptable presentation template perfect for a range of purposes including AI, digital marketing, startups, and more. With 36 unique slides and over 1,000 easy-to-edit icons, this PowerPoint resource prioritizes simplicity and creativity. Its versatile design, equipped with a 16:9 widescreen ratio and drag-and-drop functionality, makes it a standout choice for your presentation needs.

DeepMind – Artificial Intelegence PowerPoint Template

This PowerPoint template is a valuable resource for AI startups and tech businesses. It’s a time saver, allowing users to focus on the content while providing a visually appealing design. This template features resizable and editable graphics, free web fonts, and an easily editable format for creating presentations with ease.

Metaficial – Artificial Intelligence PowerPoint Template

The Metaficial is a PowerPoint template perfect for creating AI-themed slideshows. With its customizable features including 35 unique slides, resizable graphics, and drag-and-drop image placeholders, crafting a presentation to your liking is seamless. It also includes a variety of infographics and templates for diagrams, tables, and charts.

Artific – Artificial Intelligence Presentation

Artific is an AI-themed PowerPoint presentation template ideal for any Artificial Intelligence and technology-related content. The modern, sleek, and futuristic pre-designed slides can easily be customized using PowerPoint or Google Slides. It offers 25 unique slides in a 16:9 widescreen ratio with image placeholders, editable icons, and elements, all resizable and detachable without losing quality.

Ashoiy – AI Technology PowerPoint Template

Ashoiy is an ultra-modern, professionally designed set of slides for a wide range of presentations such as business, branding, and advertising. Boasting over 25 unique slides with high attention to detail, the template features a clean, multipurpose design built on master slides, with easy-to-use vector icons and changeable colors.

Best Free AI PowerPoint Templates

Artificial intelligence (ai) startup business plan free ppt.

This is a free PowerPoint template you can use to create presentations related to artificial intelligence and technology. It’s especially ideal for new startups to create a business plan slideshow. The template has 35 unique slides.

Artificial Intelligence (AI) Technology Project Proposal Free PPT

Create your AI-related project proposals in style using this free PowerPoint template. It comes with 29 unique slides with dark and creative layouts. It also uses free fonts and an icon pack.

AI Technology Thesis Free PowerPoint Template

This free PowerPoint template is designed to help you create more engaging and effective slideshows for your AI-related thesis defense. It has 35 unique slides to choose from and has a fully customizable slide design.

Cyber-Futuristic AI Technology Thesis Free PPT

Another free PowerPoint template for your AI-related thesis defense. This template has a much more modern and colorful design with lots of space for images. There are 25 slides in this template.

AI Marketing Free AI PowerPoint Template

This PowerPoint template comes with a multipurpose design featuring more than 25 slides for creating various AI-related presentations. You can fully customize each slide to your preference as well.

Artificial Intelligence Topics for Presentation

Introduction to Artificial Intelligence Topics

Imagine a day in the future where intellect is not limited to human beings!! A time when machines are intelligent enough to collaborate with people to create a fascinating universe. Despite the fact that we are still a long way from this future, Artificial Intelligence has come a long way since then. Almost all areas of AI, including quantum computers, medicine, autonomous cars, the internet-of-things, automation, etc., are the subject of intense research.

You may concentrate on several sub-topics if you want to deliver a presentation on AI and its realm. A brief introduction to some of these themes is given below.

Important Artificial Intelligence Topics for Presentation

Artificial Intelligence is a vast domain and covers a variety of topics. Some important and effective Artificial Intelligence topics for presentation are:

Machine Learning

Machine Learning (ML) is a subcategory of Artificial Intelligence (AI). The science of Machine Learning involves the creation and use of learning algorithms. If a behavior has previously occurred, you can predict when it will occur again. As a result, there cannot be a prediction without precedents. ML may be used to tackle complex problems like detecting credit card fraud, enabling self-driving automobiles, and detecting and recognizing faces.

To analyze data patterns and enable computers to adapt to circumstances they’ve never been expressly trained, Machine Learning (ML) employs sophisticated algorithms that repeatedly loop through enormous data sets. The machines use historical precedent to provide accurate findings, and Machine Learning algorithms use statistics and Machine Learning to forecast sensible outputs.

Application of AI in Industries

In today’s culture, Artificial Intelligence is used in various ways. Due to its ability to effectively address complex issues across various industries, including healthcare, media, banking, and education, it is becoming increasingly important in the modern world. AI is enhancing the convenience and speed of our daily lives.

• AI in Astrophysics
• Healthcare and AI
• AI in Finance and Gaming
• AI in the Entertainment
• Social media using AI
• Data Security Using AI
• Robots with AI
• AI in the Automotive Sector

Thus, Artificial Intelligence is being thoroughly used in the business world today.

Benefits of AI

The following are some advantages of Artificial Intelligence:

• Continuous endurance and accessibility – AI-powered machines can carry out the monotonous or difficult activities for which they are trained without making mistakes and shouldn’t have to eat or sleep.
• AI increases Industry Efficiency – Robotics and AI may improve how well businesses do their duties. With computer vision and pattern recognition, AI can get wiser over time and become more effective like Artificial Intelligence chatbots .
• Convenience and Individual – Opportunities People may now do daily chores more quickly and easily thanks to AI technologies, including virtual support and intelligent automation of repetitive work, which also increases productivity in many other ways.
• Safety and Health – Healthcare practitioners may work more quickly and successfully thanks to AI, which positively influences patient outcomes. By working in dangerous areas, robotics and automation processes also lower the hazard to health employees.
• The drawbacks of AI

Every coin has two aspects. Given all the advantages AI offers, we should also be aware of its drawbacks.

• Increased Implementation Costs: Given the intricacy of engineering in creating one, setting up AI-based equipment, computers, etc., involves enormous expenditures. Additionally, the outrageous costs don’t end there because repairs and upkeep can cost thousands of dollars.
• This can replace people: There is no question that computers do tasks significantly more effectively than people. And even then, at least in the long term, replacing people with AI is almost impossible.
• Doesn’t Get Better with Experience: The capacity of human cognitive strength to improve with maturity and experience is one of the most astounding features. However, Artificial Intelligence (AI) cannot be true. A computer does not become better with use but degrades over time.
• Lack of Creativity AI was not designed to produce artistic works. Even while they can assist you in inventing and producing something unique, they still fall short of the human brain in terms of complexity.
• Artificial Intelligence’s past

Despite appearing to be a relatively new technology, Artificial Intelligence has a long history, as shown by doing a little investigation. It is thought that concepts from Artificial Intelligence were employed in Greek mythology.

Robert McNamara and Herbert Crevasses initially proposed the artificial neuron concept in 1943. After seven years, in 1950, Alan Turing submitted a research paper on AI with the working title “Computer Machinery and Intelligence.” Robert McNamara, regarded as the founder of Artificial Intelligence, first used the phrase in 1956.

AI: Will It Destroy Human Labor?

The threat of this has long hung over Artificial Intelligence. Experts and industry heavyweights like Elon Musk and Stephen Hawkings have cautioned people about technology’s negative effects and dangers. One frequently cited effect is AI replacing humans in the workforce, resulting in significant job losses. This notion is greatly exaggerated, and academics concur that while AI may replace humans in specific employment categories, it will not do so across the board. Routine employment and repetitive operations, such as selecting and packing products, sorting and arranging resources, and answering frequent consumer questions, are likely to be replaced by AI. Some of these duties are still carried out by people today, but AI is predicted to eventually replace them.

Tips for Preparing a Presentation on Artificial Intelligence 

• Create a short design template by using the slide master function. It is fine to change how the material is presented (using a bulleted list, two columns of text, text plus an image, etc.), but keep the font, color, and backdrop the same.
• Using fewer words on every slide is important as it simplifies the points. Use keywords and only give pertinent details.
• Avoid using all-caps for words and use little punctuation. 
• Use backgrounds and text that are in contrasting colors. Backgrounds with patterns might make text harder to read.
• Stay away from using showy transitions like text fly-ins. Though first striking, these elements are intrusive and gradually get stale.

People with varying perspectives and beliefs about Artificial Intelligence make it an excellent topic for debate in businesses and classrooms. The subjects and the information provided in this article will be useful when you work on a presentation on Artificial Intelligence. There are numerous ways to delve deeper into the field of AI. The Executive PG Diploma in Management & Artificial Intelligence by IIM Indore, in collaboration with UNextm Jigsaw, is one of the best to master the nuances of AI and Management skills.

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10 Best AI Tools for Presentations in 2024

Senior Content Marketing Manager

February 13, 2024

Presentations are a powerful way to share information, but building your slide deck is often time-consuming.

Artificial intelligence (AI) is revolutionizing how people put professional and engaging presentations together, allowing you to create polished presentations in seconds. With AI, say goodbye to tediously moving elements around on a slide and say hello to getting time back in your schedule to work on the stuff that matters most.

Ready to harness this presentation superpower? Learn more about AI presentation tools , what to look for, and some of the best AI presentation makers available in 2024.

What to look for in AI tools for presentations

1. beautiful.ai, 2. simplified’s ai presentation maker, 3. slidebean, 4. designs.ai, 6. presentations.ai, 8. kroma.ai, 10. deckrobot.

What are AI Tools for Presentations?

Various software and platforms use AI to help users create, enhance, and deliver visually appealing slides. These tools can assist with all aspects of the presentation creation process, from the initial creation to supercharging engagement.

Depending on the specific AI presentation tool, it can help you with tasks such as:

• Designing stunning presentations: AI can understand and follow the rules for good design, enabling it to craft professional-looking slide decks that are visually appealing and relevant to your content
• Creating content: Tell the AI writing tool what you want to write about, and it will generate content for each slide and even create your speech notes
• Building visuals for data: Give the platform your data, and it can create easy-to-read visualizations of your information ready to add to your slide deck

AI presentation makers help you produce engaging content faster and connect with your audience more effectively. But with so many AI presentation makers available today, you’ll want to work with a few options and determine which suits your workflow and style best.

When looking for an AI presentation maker, you’ll want to find something that feels intuitive and has a user-friendly interface. You don’t want to spend hours learning how to use a new piece of software, and you shouldn’t need extensive technical expertise to put these tools to work.

You’ll also want to ensure that the AI tool you choose integrates well with the rest of your tech stack. A stunning presentation is no good if you can’t get it to work with your preferred software, such as Google Slides or Microsoft PowerPoint.

You should also look for AI-powered tools that offer the functionality you need. For example, maybe you love designing slides but aren’t strong at crafting engaging copy. In that case, look for tools that focus on content generation with interactive elements so you can flex your design skills.

Or, you may want an AI presentation generator that does everything, from designing graphics to writing copy. These are often paid tools, but you can use free trials to determine your best options for creating presentations.

10 Best AI Presentation Tools 2024

Beautiful.ai is an innovative AI presentation maker that aims to revolutionize how you create engaging presentations. The platform makes smart design recommendations through its intuitive interface and streamlines the creation process. You focus on your content while Beautiful.ai manages the aesthetics. Customizable templates, smart charts for data visualization, and analytics to track which slides get the most engagement from your audience are available.

Beautiful.ai best features

• Insightful analytics give you information on which slides in your presentation are making the most significant impact in a professional or academic setting
• Secure sharing helps protect sensitive information while making it easy to access for key stakeholders
• Seamless integration allows you to design slides in Beautiful.ai and edit them in PowerPoint

Beautiful.ai limitations

• While the templates offer beautiful designs, some users complain that there aren’t enough options compared with other platforms. Some users may want more control over their final design than the platform allows

Beautiful.ai pricing

• Pro for individuals: $12/mo
• Team for team collaboration: $40/mo
• Enterprise for advanced security and support: Contact sales for a custom plan

Beautiful.ai ratings and reviews

• G2: 4.7/5 (160+ reviews)
• Capterra: 4.6/5 (70+ reviews)

Simplified’s AI Presentation Maker promises to help you make on-brand presentations effortlessly. The platform handles image and content creation for any topic, and you can customize the results to suit your needs. All you have to do is tell the AI what topic you want to present, and it will generate the presentation in a few seconds.

Simplified best features

• A range of pre-designed templates and a vast visual library, even for users on the free plan
• Integration with all your favorite platforms, including Google Drive and Shopify
• Easy real-time collaboration on presentations

Simplified limitations

• The software can quickly become expensive, especially compared with similar services. It may be too costly for small organizations

Simplified pricing

• Design Free: $0 for one seat
• Design Pro: $6/month for one seat
• Design Business: $10/month for five seats
• Enterprise: Contact for pricing

Simplified ratings and reviews

• G2: 4.6/5 (1800+ reviews)
• Capterra: 4.7/5 (160+ reviews)

Slidebean is an AI presentation software that focuses on helping founders and startups create their pitch decks. It helps simplify the pitching process and ensures you have the right pitch for the right stage of company development. Whether you need an initial pitch deck, a marketing presentation, or a sales deck, Slidebean has solutions to suit your needs and help you get a yes.

Slidebean best features

• Online sharing keeps your deck (and ideas!) secure while putting the right information in front of the right investors
• Analytics track the activity of every slide in your deck so you know who viewed it, how many times, and when
• Easy collaboration options help you get the whole team in on the action

Slidebean limitations

• The user interface can be clunky, and some users may find editing AI-generated graphics and images difficult

Slidebean pricing

• All Access: $199/year
• Accelerate: $499/year

Slidebean ratings and reviews

• G2: 4.5/5 (20+ reviews)
• Capterra: 4.2/5 (50+ reviews)

Designs.ai offers a full suite of AI-powered creation tools. The platform offers AI writing assistance, a logo maker, a video presentation maker, and natural-sound AI voiceovers.

Those looking for help designing presentations will love the platform’s Designmaker, which creates visual content for you in seconds. Choose from a vast library of presentation templates, then give the platform your content and let it take care of the rest.

Designs.ai best features

• The huge library of templates and design elements enables you to customize your AI presentations to suit your needs
• One-click resize feature allows you to optimize your presentation for Instagram, mobile, projector screens, and other devices
• Intuitive design editor means that you don’t have to be a master of graphic design to create a gorgeous deck

Designs.ai limitations

• Exporting files can be slow and cumbersome

Designs.ai pricing

• Basic: $19/month
• Enterprise: Call for a custom quote

Designs.ai ratings and reviews

• G2: 4.3/5 (6+ reviews)
• Capterra: 4.5/5 (2+ reviews)

Pitch helps you create sleek presentations in seconds. Pick your template and add your content; you’ll soon have a beautiful deck ready to share. The platform allows you to share a link, present your presentation live, or even embed it on the web so you can direct viewers to it anytime. It has robust integration capabilities, connecting with tech-stack favorites like Slack, Vimeo, and YouTube.

Pitch best features

• Great integration capabilities make it easy to add content to your deck and share it with others
• Analytics help you track what’s working in your deck and see what you need to tweak
• Great presentation tools make it simple to share, record, and present your deck

Pitch limitations

• While the AI-generated slides are aesthetically pleasing, slide editing features can be clunky

Pitch pricing

• Starter: $0, free forever
• Pro: $8 per member per month
• Enterprise: Contact for a custom quote

Pitch ratings and reviews

• G2: 4.4/5 (40+ reviews)
• Capterra: 4.9/5 (30+ reviews)

Presentations.ai aims to help you reduce presentation creation time while improving your overall presentation design quality. The platform uses AI technology to make creation effortless and offers many personalized design options. You can then share, track, and analyze your presentations to see how they perform with your audience.

Presentations.ai best features

• Create presentations in seconds from a single prompt
• Get the perfect final look with various presentation tools and customization options
• Great branding options so you have a consistent, polished look for everything you create

Presentations.ai limitations

• The platform focuses heavily on pitch decks and marketing presentations, so the templates may be frustrating for users looking to create educational or informative presentations. Some templates and slides are behind a paywall, limiting options for free users

Presentations.ai pricing

• Starter: $0 (beta pricing)
• Pro: $396 (beta pricing)

Presentations.ai ratings and reviews

• Not available

Gamma uses natural language processing to help users create dynamic decks. Start writing your content, then use the built-in AI chatbot to change the look of your deck. When you’re happy with the deck, enter present mode and show your work off in a live presentation or send it as a webpage for users to view independently. It’s a flexible, user-friendly platform that helps you engage your audience.

Gamma best features

• Change up the look of your slide deck at any time with the help of the AI-assisted presentation tool
• Embed GIFs, charts, videos, and even websites to bring presentations to life
• Receive instantaneous feedback on your presentations from viewers with quick reactions

Gamma limitations

• Templates offer significant color customization, but there is little variation in layout and design

Gamma pricing

• Starter: Free
• Pro: Coming soon
• G2: 4/5 (6+ reviews)
• Capterra: 4/5 (1+ reviews)

Kroma.ai helps you create beautiful decks whether you present them to potential investors or need to share your ideas and data.

Simply pick your template, choose your colors, and add your logo. Then, use the grab-and-go expertly generated content to take your presentation to the next level, making it more persuasive and engaging with the help of industry leaders.

Kroma.ai best features

• Choose content from industry experts to boost your professional presentation
• Make your numbers stand out with robust data visualization tools
• Create stunning presentations with expertly designed templates that ensure that you have the right format for the job

Kroma.ai limitations

• Some parts of the user interface aren’t hugely intuitive
• Some users may not care about the expert-written content, which is one of the platform’s big selling points

Kroma.ai pricing

• Explorer: Free
• Premium: $49.99 per user per month
• Enterprise: $1,699 per year

Kroma.ai ratings and reviews

Tome wants to be your go-to AI presentation tool. Tell the platform what you want to do with a simple prompt, and it will generate images, copy, and slides to help you achieve your goal.

You can tweak every aspect of the design, asking the AI tool to change the tone or generate a new AI image in a different style. It’s also great for turning boring documents into dynamic presentations.

Tome best features

• It helps you find and cite references that support your claims
• Easy language translations permit you to your share presentations across the world
• Excellent customizable templates allow you to create pitch decks, marketing presentations, and educational presentations

Tome limitations

• Some users are encountering issues with the platform, though this could be because the tool is still in development

Tome pricing

• Free Forever
• Pro: $8 per person per month
• Enterprise: Contact for custom pricing

Tome ratings and reviews

• G2: 4.8/5 (20+ reviews)

DeckRobot is a handy plug-in that turns your drafts into polished presentation decks in seconds. It even ensures that your final deck complies with your corporate branding guidelines so you maintain consistent branding in everything you create. It’s a great way to reduce manual design time, and all your data stays securely on your servers.

DeckRobot best features

• Plug-in for PowerPoint presentations takes the first draft of your presentation and turns it into a polished final deck
• Your data stays secure because all information stays on your server
• It allows you to redesign with preset corporate branding in one click

DeckRobot limitations

• This plug-in is for PowerPoint, so if you’re using another platform, you’ll need to opt for another AI solution

DeckRobot pricing

• Call for custom pricing

DeckRobot ratings and reviews

Other ai tools for slide creation.

Are you looking for more tools to help you harness the power of AI? If so, discover the game-changing power of  ClickUp Brain . ClickUp Brain integrates seamlessly with the rest of the project-management platform. That means you can use the AI with your ClickUp Docs  to take your content creation to the next level.

ClickUp’s AI technology enhances your written copy with grammar and spell-checks plus custom suggestions tailored to your role and writing style. Use the AI Writer for Work not only to change the tone, language, or audience for your content but also to produce on-point new copy in just a few clicks. The AI writer will also help make your copy more engaging or simplify complex concepts.

ClickUp’s AI writing tools can create emails, draft blog posts, and summarize long documents in a few clicks. Generate action items and provide recaps from meeting notes to save you from tedious admin tasks. There are prompts for every department, helping everyone in your company work smarter.

If you need help creating an excellent presentation, use the  ClickUp Presentation Template as a launching point. You can use the integrated AI tools to make your content, then collaborate with the rest of your team on polishing the final deck with the innovative collaboration tools. With ClickUp’s robust integration options, you can easily pull content into your presentation and share it with stakeholders when it’s complete.

ClickUp Brain revolutionizes how you write, manage tasks, and create content. Sign up for your free account today, and start using ClickUp’s innovative AI tools to get more done!

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120 Presentation Topic Ideas Help You Hook Your Audience

Updated: January 15, 2024

Published: August 09, 2023

Cooking is easy. The puzzle is figuring out what to eat. As soon as you know that, you can get started. The same holds for presentations. The sooner you can whip up a good, informative, and catchy topic, the easier the rest of the process becomes.

Pick a good topic that resonates with you and your audience to set a strong foundation. But select the wrong topic, and it becomes difficult to connect with your audience, find mutual interests, or hold their attention.

So, let’s learn how to develop thought-provoking and relevant topics for your presentations. You’ll also find some best practices to make your presentation memorable.

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Table of Contents

How to Choose a Great Presentation Topic in 5 Steps

120 presentation topic ideas, 5 presentation tips.

4. Choose an appropriate presentation style.

There are many ways to present a topic. Your personality, the topic at hand, and your audience’s personas will help you determine which style would best fit you and your audience.

Select a presentation style that will communicate the main idea clearly and have a lasting impact on your audience.

For instance, explore a freeform style presenter by Sir Ken Robinson.

5. Engage with your audience.

Work on your presentation skills to make a strong connection with your audience, get through to them and leave a mark.

Think of the presenter as the link between the topic and the audience. A strong or a weak presenter can make a difference between a presentation being a thriving success or a boring failure.

Hone your skills by engaging and interacting with your audience. Make them feel like a part of the presentation and not just spectators. 70% of marketers have found presentations with interactive content to be more effective than those without.

Here are a few ways you can make your presentation interactive:

• Start your speech with uncommon questions to your audience. Involve them from the get-go, like ask to raise their hands if X.
• Make eye contact to build credibility and show confidence. Don’t stare at your slides or notes. Smile occasionally and talk to the audience directly.
• Have an active and confident body language. Don’t stand in the same place the entire time. Move around the stage.
• Don’t be monotonous. Speak as you would to a colleague — with enthusiasm.
• Ask close-ended questions in between to keep the audience engaged without losing time. Address them using their names to keep things interesting.
• Share personal experiences and stories that your audience will find fascinating and relatable.
• Practice thoroughly before you present so you’re fluent with the material and delivery.
• Energy and excitement can be quite contagious. Make sure you exude enough to spread some to your audience.

Feeling Inspired Yet?

Now you have all the right ingredients for choosing amazing topics and a hundred ideas to drive inspiration from. So, go ahead and start cooking presentations that will blow your audience away.

Don’t forget to choose a super-relevant topic and add meaty information. Do it with excitement to make it enjoyable for you and your audience. Best of luck!

Don't forget to share this post!

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AI Presentation Maker

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Top 5 AI Trends to Watch in 2024

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The AI trend may seem to be following a similar trajectory of hype and adoption as previous enterprise tech trends such as cloud and machine learning, though it’s different in significant ways, including:

• AI requires massive amounts of compute for the processes that let it digest and recreate unstructured data.
• AI is changing how some organizations look at organizational structure and careers.
• AI content that can be mistaken for photographs or original artwork is shaking up the artistic world, and some worry it could be used to influence elections.

Here are our predictions for five trends in AI, which often refers to generative models , to keep an eye on in 2024.

AI adoption increasingly looks like integration with existing applications

Many generative AI use cases coming to market for enterprises and businesses integrate with existing applications as opposed to creating completely new use cases. The most high-profile example of this is the proliferation of copilots , meaning generative AI assistants. Microsoft has installed Copilots next to the 365 suite offerings, and businesses like SoftServe and many others provide copilots for industrial work and maintenance. Google offers a variety of copilots for everything, from video creation to security .

But all of these copilots are designed to sift through existing content or create content that sounds more like what a human would write for work.

SEE: Is Google Gemini or ChatGPT better for work? (TechRepublic)

Even IBM asked for a reality check about trendy tech and pointed out that tools like Google’s 2018 Smart Compose are technically “generative” but weren’t considered a change in how we work. A major difference between Smart Compose and contemporary generative AI is that some AI models today are multimodal, meaning they are able to create and interpret pictures, videos and charts.

“We’ll see a lot of innovation about that (multimodality), I would argue, in 2024,” said Arun Chandrasekaran, distinguished VP, analyst at Gartner, in a conversation with TechRepublic.

At NVIDIA GTC 2024, many startups on the show floor ran chatbots on Mistral AI’s large language models since open models can be used to create custom-trained AI with access to company data. Using proprietary training data lets the AI answer questions about specific products, industrial processes or customer services without feeding proprietary company information back into a trained model that might release that data onto the public internet. There are a lot of other open models for text and video, including Meta’s Llama 2 , Stability AI’s suite of models, which include Stable LM and Stable Diffusion, and the Falcon family from Abu Dhabi’s Technology Innovation Institute.

“There’s a lot of keen interest in bringing enterprise data to LLMs as a way to ground the models and add context,” said Chandrasekaran.

Customizing open models can be done in a few ways, including prompt engineering, retrieval-augmented generation and fine-tuning.

Another way AI might integrate with existing applications more in 2024 is through AI agents, which Chandrasekaran called “a fork” in AI progress.

AI agents automate the tasks of other AI bots, meaning the user doesn’t have to prompt individual models specifically; instead, they can provide one natural language instruction to the agent, which essentially puts its team to work pulling together the different commands needed to carry out the instruction.

Intel Senior Vice President and General Manager of Network and Edge Group Sachin Katti referred to AI agents as well, suggesting at a prebriefing ahead of the Intel Vision conference held April 9–11 that AI delegating work to each other could do the tasks of entire departments .

Retrieval-augmented generation dominates enterprise AI

Retrieval-augmented generation allows an LLM to check its answers against an external source before providing a response. For example, the AI may check its answer against a technical manual and provide the users with footnotes that have links directly to the manual. RAG is intended to increase accuracy and decrease hallucinations .

RAG provides organizations with a way to improve the accuracy of AI models without causing the bill to skyrocket. RAG produces more accurate results compared to the other common ways to add enterprise data to LLMs, prompt engineering and fine-tuning. It is a hot topic in 2024 and is likely to continue to be so later in the year.

Organizations express quiet concerns about sustainability

AI is used to create climate and weather models that predict disastrous events. At the same time, generative AI is energy- and resource-heavy compared to conventional computing.

What does this mean for AI trends? Optimistically, awareness of the energy-hungry processes will encourage companies to make more efficient hardware to run them or to right-size usage. Less optimistically, generative AI workloads may continue to draw massive amounts of electricity and water. Either way, generative AI may become a matter that contributes to national discussions about energy use and the resiliency of the grid. AI regulation now mostly focuses on use cases, but in the future, its energy use may fall under specific regulations as well.

Tech giants address sustainability in their own way, such as Google’s purchase of solar and wind energy in certain regions. For example, NVIDIA touted saving energy in data centers while still running AI by using fewer server racks with more powerful GPUs .

The energy use of AI data centers and chips

The 100,000 AI servers NVIDIA is expected to send to customers this year could produce 5.7 to 8.9 TWh of electricity a year, a fraction of the electricity used in data centers today. This is according to a paper by PhD candidate Alex de Vries published in October 2023. But if NVIDIA alone adds 1.5 million AI servers to the grid by 2027, as the paper speculates, the servers would use 85.4 to 134.0 TWh per year, which is a much more serious impact.

Another study found that creating 1,000 images with Stable Diffusion XL creates about as much carbon dioxide as driving 4.1 miles in an average gas-powered car.

“We find that multi-purpose, generative architectures are orders of magnitude more expensive than task-specific systems for a variety of tasks, even when controlling for the number of model parameters,” wrote the researchers, Alexandra Sasha Luccioni and Yacine Jernite of Hugging Face and Emma Strubell of Carnegie Mellon University.

In the journal Nature , Microsoft AI researcher Kate Crawford noted that training GPT-4 used about 6% of the local district’s water.

The roles of AI specialists shift

Prompt engineering was one of the hottest skill sets in tech in 2023, with people rushing to bring home six-figure salaries for instructing ChatGPT and similar products to produce useful responses. The hype has faded somewhat and, as mentioned above, many enterprises that heavily use generative AI customize their own models. Prompt engineering may become part of software engineers’ regular tasks more going forward, but not as a specialization — simply as one part of the way software engineers perform their usual duties.

Use of AI for software engineering

“The usage of AI within the software engineering domain is one of the fastest growing use cases we see today,” said Chandrasekaran. “I believe prompt engineering will be an important skill across the organization in the sense that any person interacting with AI systems — which is going to be a lot of us in the future — have to know how to guide and steer these models. But of course people in software engineering need to really understand prompt engineering at scale and some of the advanced techniques of prompt engineering.”

Regarding how AI roles are allocated, that will depend a lot on individual organizations. Whether or not most people doing prompt engineering will have prompt engineering as their job title remains to be seen.

Executive titles related to AI

A survey of data and technology executives by MIT’s Sloan Management Review in January 2024 found organizations were sometimes cutting back on chief AI officers. There has been some “confusion about the responsibilities” of hyper-specialized leaders like AI or data officers, and 2024 is likely to normalize around “overarching tech leaders” who create value from data and report to the CEO, regardless of where that data comes from.

SEE: What a head of AI does and why organizations should have one going forward. (TechRepublic)

On the other hand, Chandrasekaran said chief data and analytics officers and chief AI officers are “not prevalent” but have increased in number. Whether or not the two will remain separate roles from CIO or CTO is difficult to predict, but it may depend on what core competencies organizations are looking for and whether CIOs find themselves balancing too many other responsibilities at the same time.

“We are definitely seeing these roles (AI officer and data and analytics officer) show up more and more in our conversations with customers,” said Chandrasekaran.

On March 28, 2024, the U.S. Office of Management and Budget released guidance for the use of AI within federal agencies , which included a mandate for all such agencies to designate a Chief AI Officer.

AI art and glazing against AI art both become more common

As art software and stock photo platforms embrace the gold rush of easy images, artists and regulators look for ways to identify AI content to avoid misinformation and theft.

AI art is becoming more common

Adobe Stock now offers tools to create AI art and marks AI art as such in its catalog of stock images. On March 18, 2024, Shutterstock and NVIDIA announced a 3D image generation tool in early access.

OpenAI recently promoted filmmakers using the photorealistic Sora AI . The demos were criticized by artist advocates, including Fairly Trained AI CEO Ed Newton-Rex, formerly of Stability AI, who called them “Artistwashing : when you solicit positive comments about your generative AI model from a handful of creators, while training on people’s work without permission/payment.”

Two possible responses to AI artwork are likely to develop further over 2024: watermarking and glazing.

Watermarking AI art

The leading standard for watermarking is from the Coalition for Content Provenance and Authenticity , which OpenAI ( Figure A ) and Meta have worked with to tag images generated by their AI; however, the watermarks, which appear either visually or in metadata, are easy to remove. Some say the watermarks won’t go far enough when it comes to preventing misinformation, particularly around the 2024 U.S. elections.

SEE: The U.S. federal government and leading AI companies agreed to a list of voluntary commitments , including watermarking, last year. (TechRepublic)

Poisoning original art against AI

Artists looking to prevent AI models from training on original art posted online can use Glaze or Nightshade , two data poisoning tools made by the University of Chicago. Data poisoning adjusts artwork just enough to render it unreadable to an AI model. It’s likely that more tools like this will appear going forward as both AI image generation and protection for artists’ original work remain a focus in 2024.

Is AI overhyped?

AI was so popular in 2023 that it was inevitably overhyped going into 2024, but that doesn’t mean it isn’t being put to some practical use. In late 2023, Gartner declared generative AI had reached “ the peak of inflated expectations ,” a known pinnacle of hype before emerging technologies become practical and normalized. The peak is followed by the “trough of disillusionment” before a rise back up to the “slope of enlightenment” and, eventually, productivity. Arguably, generative AI’s place on the peak or the trough means it is overhyped. However, many other products have gone through the hype cycle before, many eventually reaching the “plateau of productivity” after the initial boom.

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Gemini 1.5 and Google’s Nature

It was impossible to miss the leading message at yesterday’s Google Cloud Next keynote : Google has the best infrastructure for AI. This was CEO Sundar Pichai in his video greeting:

I want to highlight just a few reasons Google Cloud is showing so much progress. One is our deep investments in AI. We’ve known for a while that AI would transform every industry and company, including our own. That’s why we’ve been building AI infrastructure for over a decade, including TPUs, now in their 5th generation. These advancements have helped customer train and serve cutting-edge language models. These investments put us in the forefront of the AI platform shift.

Google Cloud CEO Thomas Kurian made the priority clear as well:

Today we’re going to focus on how Google is helping leading companies transform their operations and become digital and AI leaders, which is the new way to cloud. We have many important advances, starting with our infrastructure.

What was most interesting about the keynote, though, is what that infrastructure makes possible, and, by extension, what that says about Google’s ability to compete.

One of the most surprising things about large language models (LLMs) is how much they know; from the very beginning, though, hallucinations have been a concern. Hallucinations are, of course, part of what makes LLMs so impressive: a computer is actually being creative! It’s also a feature that isn’t particularly impressive to the enterprise customers that this keynote was directed at.

To that end, Kurian, shortly after going over Google’s infrastructure advantages, talked about “grounding”, both in terms of the company’s Gemini model broadly, and for enterprise use cases specifically in the context of Google’s Vertex AI model management service:

To augment models, Vertex AI provides managed tooling to connect your model to enterprise applications and databases, using extensions and function-calling. Vertex also provides retrieval augmented generation (RAG) combining the strengths of retrieval and generative models to provide high quality personalized answers and recommendations. Vertex can augment models with up-to-date knowledge from the web and from your organization, combining generative AI with your enterprise truth. Today we have a really important announcement: you can now ground with Google Search, perhaps the world’s most trusted source of factual information, with a deep understanding of the world’s knowledge. Grounding Gemini’s responses with Google Search improves response quality and significantly reduces hallucinations. Second, we’re also making it easy to ground your models with data from your enterprise databases and applications, and any database anywhere. Once you’ve chosen the right model, tuned it, and connected it with your enterprise truth, Vertex’s MLOps can help you manage and monitor models.

A RAG implementation using Google Search is an obvious win, and mirrors ChatGPT’s integration with Bing (or Microsoft Copilot in Bing): the LLM provides answers when it can, and searches the web for things it doesn’t know, a particularly useful feature if you are looking for more recent information.

A more impressive demonstration of grounding, though, was in the context of integrating Gemini with Google’s BigQuery data warehouse and Looker business intelligence platform :

In this demo, the worker gets an alert that a particular product is selling out; using generative AI the worker can see sales trends, find similar models, and create a plan of action for dealing with declining inventory for delivery to her team.

What is notable is not the demo specifics (which is unapologetically made-up for Cymbal, Google’s demo brand ); rather, note the role of the LLM: it is not providing information or taking specific actions, but rather serving as a much more accessible natural language interface to surface and collect data that would otherwise take considerably more expertise and time. In other words, it is trustworthy because it is grounded through integration Google is promising with its other enterprise data services.

At the same time, that last section didn’t really follow on from the introduction: yes, those LLMs leveraging Google or BigQuery are running on Google’s infrastructure, but other companies or startups can build something similar. This is where the rest of Pichai’s introduction comes in:

We also continue to build capable AI models to make products like search, Maps, and Android radically more helpful. In December, we took our next big step with Gemini, our largest and most capable model yet. We’ve been bringing it to our products and to enterprises and developers through our APIs. We’ve already introduced our next generation Gemini 1.5 Pro. It’s been in private preview in Vertex AI. 1.5 Pro shows dramatically enhanced performance and includes a breakthrough in long context understanding. That means it can run 1 million tokens of information consistently, opening up new possibilities for enterprises to create, discover, and build using AI. There’s also Gemini’s multi-modal capabilities, which can process audio, video, text, code and more. With these two advances, enterprises can do things today that just weren’t possible with AI before.

Google hasn’t said how Gemini 1.5 was made, but clearly the company has overcome the key limitation of traditional transformers: memory requirements increase quadratically with context length. One promising approach is Ring Attention with Blockwise Transformers , which breaks long contexts into pieces to be computed individually even as the various devices computing those pieces simultaneously communicate to make sense of the context as a whole; in this case memory requirements scale linearly with context length, and can be extended by simply adding more devices to the ring topology.

This is where Google’s infrastructure comes in: the company not only has a massive fleet of TPUs, but has also been developing those TPUs to run in parallel at every level of the stack, from chip to cluster to even data centers (this latter requirement is more pertinent for training than inference); if there is a solution that calls for scale, Google is the best placed to provide it, and it seems the company has done just that with Gemini 1.5.

To that end, and per Pichai’s closing line, almost all of the other demos in the keynote were implicitly leveraging Gemini 1.5’s context window.

In a Gemini for Workspaces demo, the worker evaluated two statements of work against each other, and against the company’s compliance document:

Here are the key quotes:

Google Drive is ready without any additional AI pre-work… Each of these documents is over 70 pages. It would have taken me hours to review these docs, but instead Gemini is going to help me find a clean answer to save me a ton of time… Before I proceed with this vendor, I need to ensure that no compliance issues exist, and I’m going to be honest, I have not memorized every rule in our compliance rulebook because it is over 100 pages. I would have to need to scour the 80 pages of this proposal and compare it manually with the 100 pages of the rulebook. So instead, in the side panel I ask, “Does this offer comply with the following” and I’m going to just @-mention our compliance rulebook, hit Enter, and see what Gemini has to say. So interesting: Gemini has found an issue, because the supplier has not listed their security certifications. Because Gemini is grounded in my company’s data, with source citations to specific files, I can trust this response and start to troubleshoot before selecting a vendor.

The key distinction between this demo and the last one is that quote at the beginning: a large context window just works in a far greater number of use cases, without any fiddly RAG implementations or special connections to external data stores; just upload the files you need to analyze, and you’re off.

In a Creative Agent with Imagen demo, the worker was seeking to create marketing images and storyboards for an outdoor product:

Here is the key quote:

The creative agent can analyze our previous campaigns to understand our unique brand style and apply it to new ideas. In this case, the creative agent has analyzed over 3,000 brand images, descriptions, videos, and documents of other products that we have in our catalog, contained within Google Drive, to create this summary…The creative agent was able to use Gemini Pro’s 1 million token context window and it’s ability to reason across text, images, and video to generate this summary.

This was, to be fair, one of the weaker demos: the brand summary and marketing campaign weren’t that impressive, and the idea of creating a podcast with synthetic voices is technically impressive and also something that will never be listened to. That, though, is impressive in its own right: as I noted in an Update when Gemini 1.5 was first announced , “a massively larger context window makes it possible to do silly stuff”, and silly stuff often turns into serious capabilities.

In a Gemini Code Assistant Demo (formerly Duet AI for Developers), a developer new to a job (and the codebase) was tasked with making a change to a site’s homepage:

For the developers out there, you know that this means we’re going to need to add padding in the homepage, modify some views, make sure the configs are changed for our microservices, and typically, it would take me a week or two to even just get familiarized with our company’s code base which has over 100,000 lines of code over 11 services. But now, with Gemini Code Assist, as a new engineer on the team, I can be more productive than ever and can accomplish all of this work in just a matter of minutes. This is because Gemini’s code transformations with full codebase awareness allows us to easily reason through our entire codebase, and in comparison, other models out there can’t handle anything beyond 12,000 to 15,000 lines of code. Gemini with Code Assist is so intelligent that we can just give it our business requirements, including the visual design…Gemini Code Assist doesn’t just suggest code edits; it provides clear recommendations, and makes sure that all of these recommendations align with [the company’s] security and compliance requirements…

And the conclusion:

Let’s recap: behind the scenes Gemini has analyzed my entire codebase in GitLab; it has implemented a new feature; and has ensured that all of the code generated is compatible with my company’s standards and requirements.

Again, leave aside the implausibility of this demo: the key takeaway is the capabilities unlocked when the model is able to have all of the context around a problem while working; this is only possible with — and here the name is appropriate — a long context window, and that is ultimately enabled by Google’s infrastructure.

Google’s Nature

In case it isn’t clear, I think that this keynote was by far the most impressive presentation Google has made in the AI era, not least because the company knows exactly what its advantages are. Several years ago I wrote an Article called Microsoft’s Monopoly Hangover that discussed the company’s then-ongoing transition away from Windows as the center of its strategy; the central conceit was a comparison to Lou Gerstner’s 1990’s transformation of IBM.

The great thing about a monopoly is that a company can do anything, because there is no competition; the bad thing is that when the monopoly is finished the company is still capable of doing anything at a mediocre level, but nothing at a high one because it has become fat and lazy. To put it another way, for a former monopoly “big” is the only truly differentiated asset.

My argument was that business models could be changed: IBM did it, and Microsoft was in the process of doing so when I wrote that. Moreover, Gerstner had shown that culture could be changed as well, and Nadella did just that at Microsoft . What couldn’t be changed was nature: IBM was a company predicated on breadth, not specialization; that’s why Gerstner was right to not break apart the company but to instead deliver Internet solutions to enterprises. Similarly, Microsoft was a company predicated on integration around Windows; the company’s shift to services centered on Teams as Microsoft’s operating system in the cloud was also true to the company’s nature.

Google is facing many of the same challenges after its decades long dominance of the open web: all of the products shown yesterday rely on a different business model than advertising, and to properly execute and deliver on them will require a cultural shift to supporting customers instead of tolerating them. What hasn’t changed — because it is the company’s nature, and thus cannot — is the reliance on scale and an overwhelming infrastructure advantage. That, more than anything, is what defines Google, and it was encouraging to see that so explicitly put forward as an advantage.

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10 April 2024

Airbus shareholders approve all resolutions at 2024 agm.

Amsterdam, 10 April 2024 – Airbus SE (stock exchange symbol: AIR) shareholders approved all resolutions at the Company’s 2024 Annual General Meeting (AGM) held on 10 April in Amsterdam.

Resolutions included the renewal of the three-year Board mandate of Chairman René Obermann and those of fellow non-executive directors Victor Chu, Jean-Pierre Clamadieu and Amparo Moraleda. Mr. Obermann was formally reappointed Chairman of the Board at a Board meeting held after the AGM.

Dr. Feiyu Xu was appointed as a non-executive director following approval at the shareholder meeting. She replaces Ralph D. Crosby, Jr., who resigned with effect of the date of the AGM having served on the Board since 2013. Dr. Xu was appointed for a term of two years, corresponding to the remainder of Mr. Crosby’s mandate.

Dr. Xu is a member of the Supervisory Board of technology company ZF Friedrichshafen AG and a leading expert in the application of artificial intelligence in industry. Her appointment increases the proportion of female directors from 33% to 42%, in line with the Company’s commitment to promote greater diversity on the Board and Executive Committee, both in terms of gender and background.

Airbus Board mandates are renewed at each AGM in blocks of four for three years, in order to ensure a smooth transition of the Board’s composition and that the appropriate skills are retained among the directors.

The proposed payments of a 2023 gross dividend of € 1.80 per share (2022: € 1.80 per share) and a special dividend of € 1.00 per share were also approved.

Further details on Airbus’ Annual General Meetings are available on the Investors page .

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