In this episode, Luis Serrano and I dive into the transformative impact of AI on education, forecasting a radical shift in how future generations learn and think. ► Luis' website: https://serrano.academy/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Chapters: 00:00 Coming up in the conversation 00:01:50 Sharing journey: Why Luis became an educator 00:06:03 Can someone develop skills to become a better educator, and what are they? 00:08:07 Deciding the depth of explanation 00:10:57 AI’s impact on education 00:22:35 How does an explanation without graphic aid look? 00:27:15 Luis is explaining embedding in an intuitive way? 00:31:05 Is AI hard to explain because of newness or complexity? 00:34:01 Necessity of understanding the basics of AI 00:36:57 Why do people not want to learn about how AI works? 00:39:15 Importance of good story telling and explanation 00:42:01 Strategy to explain tough topics 00:48:12 Strategy to introduce complex words in explanation 00:55:14 Evolution in AI Education Approaches  01:02:03 Is it possible to bring good value through shorts or reels? 01:04:46 Rise of Podcast and reels

Register to GTC (attend in person, or free online): https://nvda.ws/3XQRtkl Interested in end-to-end PM job hunting and up-skilling program by Dr. Nancy Li’s PM Accelerator? Register this free masterclass about product portfolio and stay until the end to learn more about the program (Use the code LOUIS500 for 500$ off on her program!): https://www.drnancyli.com/a/2147615411/2HzsofFw Introducing Dr. Nancy Li, a versatile entrepreneur, Director of Products, YouTuber, and a Forbes-featured professional with 8 years of experience in driving cutting-edge technology products. Dr. Li currently serves as the CEO of PM Accelerator, the fastest-growing Product Management Professional Development Company in the industry, known for its engaging alumni network, and top-rated program, and she has a remarkable record of helping over 1000 aspiring product managers secure high-paying roles at tech giants and unicorn startups. Her journey, from being the youngest engineering Ph.D. to Director of Product in just four years, is a testament to her extraordinary career. Having personally launched award-winning AI products and mentored many into high-paying AI PM roles, Dr. Nancy offers a rare blend of expertise and experience. From her day-to-day interactions with AI engineers to the challenges of training AI models, she provides a comprehensive look into the dynamic world of AI product management. References we discussed in the episode: PM Accelerator by Dr. Nancy Li: https://www.drnancyli.com The ONLY 4 Ways to Become an AI Product Manager with No Experience: https://youtu.be/aQTuPUIkrxk?si=JJMih2qzC6iP2a8_ A Day in The Life of An AI Product Manager: https://youtu.be/waVyVcUzfeg?si=YOqUao6HCSHQ9MWG ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether 00:00:00 Coming up in the conversation 00:02:46 Nancy introduces herself 00:04:02 The reason Nancy couldn't drop her PhD 00:07:35 These are the people PhD is for 00:09:40 Secret revealed: How Nancy completed her PhD in 3.5 years! 00:14:07 Tips that helped Nancy peer with people from MIT 00:23:25 Are companies still prioritizing titles over practical skills? 00:26:21 Have PM skill requirements changed in recent years? 00:29:20 Crazy story: This is why she will never go to university to teach! 00:35:53 Online education vs offline education 00:41:29 Shifting from Material to AI: How she Landed a Job! 00:44:32 Staying up-to-date with technology and deciding when to implement which 00:46:41 Secret recipe to make successful AI products 00:51:19 Day to day life of a PM 00:55:28 Louis shares about his start-up Towards AI 00:58:21 Nancy shares information about her PM accelerator program

In this episode, I talk with Avery Smith, a data analytics expert and educator who gives practical strategies for breaking into the data analytics field, leveraging AI for learning and career development. Avery shares his journey into data and teaching, and insights on helping others transition into data careers through his Data Analytics Accelerator program, emphasizing the importance of practical projects and how he leverages AI in enhancing learning and job preparation processes (and he shares tips to help you do that too!). References: ►Avery Smith: https://www.linkedin.com/in/averyjsmith/ ►Data Career Jumpstart: https://www.datacareerjumpstart.com/ ►Podcast: https://podcasters.spotify.com/pod/show/datacareerpodcast ►AveryGPT: https://www.datacareerjumpstart.com/averygpt ►AI Interview Simulator: https://www.datacareerjumpstart.com/interviewsimulator ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Timestamps: 00:00 Coming up in the conversation 01:45 Avery shares about his background 03:00 Making people land data job in 90 days! 07:02 Theory vs Practical knowledge 08:34 Importance of Explainability in Models 10:28 The Future of Traditional and Online Education 12:00 Networking while studying remotely 14:09 Maintaining consistency in value in LinkedIn posts. 16:20 Is greater studies still relevant in the era of ChatGPT? 17:45 Becoming freelancing ready in data analytics 20:53 Keeping course content up to date  23:56 This is how Avery utilizes AI 29:16 Discussion on AI Avatars 38:01 Does Avery provide lessons on how to better use ChatGPT? 40:08 Avery shares his learning resources 43:12 Book recommendations 44:52 Is the field of data field too saturated to join right now? 46:58 Discussion on the current reality of freelancing

In this episode I had the opportunity to talk with Tina Huang, founder of the Lonely Octopus platform, a highly successful YouTube channel and experienced freelancer in the AI space. Tina shares her invaluable insights on leveraging AI in education, the nuances of freelancing in the tech industry, and strategies for enhancing personal productivity. The episode is for anyone looking to navigate the landscape of technology (especially AI), offering practical tips to work in the field or just leverage AI better. ►Check out Tina's channel  @TinaHuang1  ►Lonely Octopus: https://www.lonelyoctopus.com/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether Timestamps: 00:00 Coming up in the conversation 02:00 How did Tina get into AI and YouTube? 03:17 Tina's goal and mission 04:09 Tina’s niche 06:40 Higher education in the AI and data science space 10:36 Tips for beginners to become freelancing-ready 17:24 What will be more important in the future, LLMs or coding languages? 22:30 Tips for those who want to change field while balancing their current job 25:16 Using YouTube to force ownself to learn 27:17 How to make commitments and what kind of commitments should you have? 33:05 Louis shares about the AI market he believes has the most potential 37:44 Tina discussed where she wants to contribute more 39:09 Tine shares the benefits that her YouTube venture has brought 40:40 How can one use content to create leverage in freelancing? 43:05 Is audience conversion from shorts to long-form content really an issue? 46:46 Freelancing vs corporate employment vs entrepreneurship 50:33 What skills should one develop to secure freelance opportunities in the field of AI? 54:00 Tina shares about her upcoming plans

In this episode, I received Mariam Brian, CEO of Holo Art, to talk about the transformative role of AI in the art world. She discusses how artificial intelligence is reshaping artistic creation and expression and addresses the ethical implications of this technological evolution. This conversation, accessible to anyone, offers a fantastic perspective on the intersection of art and AI, highlighting the potential for a new era of creativity and collaboration between humans and machines! ►Mariam's LinkedIn: https://www.linkedin.com/in/mariamhashemi/►Holo Art: https://holo-art.io/about-us ► Holo Art announcement: https://medium.com/@mariambrian/patented-ai-process-for-executives-organizations-looking-to-level-up-e465c1c35a07 ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether Timestamps: 00:00:00 Coming up in the conversation 00:01:32 Mariam shares about his background 00:02:15 The Intersection of AI and Philosophy 00:05:39 The Impact of AI on Art and Artists 00:08:36 The Future of AI and Art 00:09:13 The Role of AI in Business and Ethics 00:10:55 AI might the Pandora box of lot of problems! 00:14:39 Simultaneous rise of Podcast & Shorts and their impact on the lives of billions 00:23:42 The Creativity of AI and its Impact on Artists 00:28:53 Can AI generated art hurt creativity of artist? 00:33:22 To be an artist, ethics becomes a way of life 00:35:45 Mariam's Personal Use of AI in Art 00:40:30 AI's Potential in Human-Machine Co-Creation 00:41:27 Understanding Ourselves and AI's Perception of Us 00:46:32 W.I.E.R.D Science 00:50:02 While using AI model do you try to control it or let it surprise you? 00:54:38 Public Perception of AI-Generated Art 01:01:44 The Risks and Opportunities for Artists Using AI 01:10:53 Mariam's message for listeners

A new episode with Jerome Pasquero, a Machine Learning Director at Sama, a leading company for data annotation solutions, where we dive into the role of data in AI's evolution. We explore the nuances of data annotation, the ethical implications of data in AI, and how data is shaping the future of technology. Don't miss Jerome Pasquero's insights on the intersection of data and AI! ►Jerome Pasquero: https://www.linkedin.com/in/jeromepasquero/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether Timestamps: 00:00:00 Coming up in the conversation 00:01:34 Jerome shares about his background 00:04:07 How did Jerome get into the data field? 00:05:23 AI back in the days of 2000s 00:07:20 Back then, what piqued Jerome's interest the most in AI? 00:08:40 Using AI to try to mimic human comprehension 00:12:47 Present challenges and the prospective outlook of computer vision 00:14:54 Using Humans vs. ML Models to Annotate Data 00:17:46 Jerome's perspective on Constitutional AI or RLAIF 00:24:52 Impact of LLM and AI on the Job market 00:26:27 Is the AI revolution bigger than previous tech revolutions? 00:28:35 Will there be something more interesting than AGI? 00:31:15 Dealing with complex annotation tasks and different perspectives 00:33:33 Dealing with biases 00:36:18 Using a single annotator vs. multiple annotators on the same data 00:37:49 Synthetically generated data 00:40:47 Scaling quality assurance for large datasets 00:42:46 When is machine learning better at annotation than human annotators? 00:45:34 Reduction of Humans-in-the-loop due to the constant evolution of AI 00:46:42 Data Requirements for Training Autonomous Vehicles 00:51:43 Sensors for transferring human driving skills to Autonomous cars 00:53:20 Why don’t we build only autonomous subway system? 00:55:26 Use of AI in the vision industry and example of vision technology used in our daily life 01:00:17 The potential of haptics and its link with AI

►Think Autonomous: https://www.thinkautonomous.ai/ ►Jeremy’s linkedin: https://www.linkedin.com/in/jeremycohen2626/ ►Newsletter: https://www.thinkautonomous.ai/private-emails-home/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Become a member of the YouTube community, support my work and get a cool Discord role : https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 00:01:31 Jeremy shares about his background 00:03:55 The future of Self-driving cars is not that straightforward! 00:07:49 If there are numerous challenges, why are companies still developing autonomous cars? 00:08:46 The future might involve more self-driving buses and trucks instead of cars 00:09:24 Are AI Start-ups dead? 00:14:25 Can 'wannabe' AI start-ups harm the actual AI economy and market? 00:16:50 Should AI research prioritize progress over control and a deep understanding of algorithms? 00:21:14 Can AI replace experts? 00:24:04 If we make AI hyper-personalized or make it impersonate someone, can it replace experts? 00:25:18 If AI cannot replace experts, should we be worried about our jobs? 00:26:18 How to find out if your job can be taken by AI or not? 00:33:06 Potential of AI in creative expression, entertainment, and journalism 00:38:11 Will AI make us dumb? 00:40:16 Can hallucination be fixed or not? 00:46:29 Is it possible to build a biasless AI model? 00:52:24 Transparency is going to be a big thing AI economy 00:55:59 AI can make your content boring! 01:02:39 Your mom might not use AI unless this happens! 01:09:08 Is AI democratizing opportunities or is it still only benefitting the rich?

Follow the podcast for more interesting conversations with experts in the AI space! For more: ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/

In this 25th episode, Jerry, co-founder and CEO of LlamaIndex shares valuable insights for anyone implementing LLM solutions. I decided to focus on Retrieval Augmented Generation (RAG) since it is the current "hype" solution, but we also touched on LLMs in general, the importance of good communication and documentation and more about the business sides of things. I hope you enjoy this episode of the What's AI podcast! ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 01:30 Jerry shares about his journey into AI 03:29 Went into AI product space instead of doing a master's degree and research? 04:56 Understanding the Basics of AI and LLMs 07:16 Beginner in AI... note down this recommendation! 09:50 Understanding LlamaIndex 12:40 Comparing LlamaIndex with Other Tools 16:30 Thoughts on Gemini? 19:29 Dealing with Multimodalities in LlamaIndex 21:25 Importance of Good Documentation 24:12 Deep Dive into Retrieval Augmented Generation (RAG) 28:35 RAG vs Fine-Tuning 34:43 The Importance of Chunking Size in RAG System 37:49 The Importance of Data Quality in Chunks 42:55 Evaluate the RAG system 46:05 The future of LLM 49:29 The Role of Prompt Engineering in AI 53:33 Which AI tools do you use?

In this episode, I received Greg Coquillo, 2-times LinkedIn top voice, senior product manager and AI startup investor. I took this opportunity to into the lifecycle of startups, discussing the critical phases from prototyping to achieving market dominance. Greg shares his expertise on identifying crucial market signals that guide startups on whether to pivot or persevere. We also explore common pitfalls that AI startups face, such as scaling too rapidly and misalignment within teams. Particularly compelling is Greg's perspective on the current startup investment landscape and the exciting potential in AI-enabled solutions. He also shares his story and debuts on LinkedIn, giving great insights to build your own audience. This episode is a must-listen for entrepreneurs, investors, and anyone interested in the dynamic world of startups and AI innovation. ►Greg's linkedin: https://www.linkedin.com/in/greg-coquillo/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 01:19 Greg Coquillo’s Introduction 05:26 Why Start Investing in Start-Ups? 10:20 Why Choose Start-Ups Over Public Companies for Investments? 13:48 Assessing Risk in Start-Up Investments 21:41 Considering Your Expertise on Subject Matter in Start-Up Investments? 27:12 Invest in someone even if they pivot their problems and solutions. 31:07 Decoding Market Signals for a Pivot 37:39 Key Pitfalls for Advisors, Investors, and Entrepreneurs to Navigate. 39:36 Exploring Potential in Start-Ups and Investing And Current Market Conditions. 43:41 Story behind 190k+ followers on LinkedIn page 50:15 Greg shares why he didn't start on multiple platforms even after a large audience on LinkedIn 54:00 Sharing knowledge was more beneficial for Greg than building a brand, but why? 58:12 Discussion about content creators 01:00:28 Some type of content is hurting actual content 01:09:40 Greg's message to viewers

If you are interested in better leveraging AI for your work and productivity, building things (startups), or the world of podcasting, this episode with @KenJee_ds is for you! Subscribe to my newsletter and keep learning about AI and my projects: https://louisbouchard.substack.com/ ►Twitter: https://twitter.com/Whats_AI, https://twitter.com/KenJee_DS ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Become a member of the YouTube community, support my work and get a cool Discord role : https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 00:39 Introduction of Ken 01:29 Ken shares how he got into AI/Data Science 06:35 This type of Start-up is going to fail! 12:40 Will the OpenAI store revolutionize everything? 15:41 AI is spoiling our brains (Most probably), but how!? 22:49 Ken uses hallucination for his benefit 25:02 Ken's hack to use AI models w/o any prior background knowledge 36:43 Ken shares his current plans in general 39:54 Ken shares how he manages life and work 43:58 Why everyone should start a podcast? 49:50 Ken gives tips for beginners who want to start a podcast 01:01:15 Podcasting and Money 01:04:29 Is expertise necessary to launch a niche podcast on topics like AI? 01:05:50 Discussion - Just put the fear and greed aside and start podcasting 01:12:31 This is the reason why Ken succeeded! 01:16:22 Get success with 66 days of data

Check out MindStudio: https://bit.ly/MindStudioWhatsAI This is an interview with Dmitry Shapiro, previously working at Google and CTO of MySpace Music. Now, Dmitry is building something super ambitious with the goal of democratizing artificial intelligence. We talk about his platform, MindStudio, but also give super applicable tips to build better AI apps, such as the model selection, prompting, using RAG and more. We also talk a lot about the user perspective, democratizing AI and the future of AI. Dmitry also has another goal of indexing the mind of everyone. And I for sure talked about that in this episode. I hope you enjoy it. ►Follow Dmitry: https://www.linkedin.com/in/dmitry-shapiro-a2b1/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Become a member of the YouTube community, support my work and get a cool Discord role : https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 00:35 Introduction 01:23 This inspired Dmitry to create YouAI 06:14 Building thousands of applications vs Building one foundation model 09:24 Will AI never become like a Swiss army knife? 12:26 Tips to become a good prompt engineer 14:55 ChatGPT vs Specialized models --> What is better for you? 17:31 Some people are not using the AI model even if they know they can be more productive with that but WHY! 22:57 If AI is intelligent, shouldn’t it figure out that it needs more information and gather it up? 26:06 Indexing the Mind 31:39 Privacy concerns with Mind Indexing 35:12 Mind Indexing vs Neuralink 37:57 Tips for Model Selection 43:09 Identifying and mitigating hallucination 47:08 Is Dmitry concerned about big companies that can rival MindStudio? 50:34 Will prompt engineering skills become irrelevant? 52:33 Do we developers or only prompt engineers are enough? 53:48 Beginner's approach towards learning AI 57:11 Communication >> Programming 01:03:42 Democratization of AI is extremely important

This week I received Paige Bailey, Lead product manager at Google DeepMind and previously working at Microsoft GitHub building Copilot. In this episode, we discussed the democratization of AI, advancements in AI-assisted coding, and the ethics of innovation. Discover how AI is subtly reshaping our everyday experiences and the realm of software engineering. Follow Paige Bailey on all platforms, https://twitter.com/DynamicWebPaige ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Become a member of the YouTube community, support my work and get a cool Discord role: https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Timestamps: 01:27 Introduction of Paige Bailey 03:29 External coding assistants vs In-built copilots of IDEs 08:10 Problem:  Beginners using ChatGPT without a core understanding of the subject 15:08 Solving hallucination (At least trying!) 19:29 Does size matters for models? 22:12 Making small products competent for big products (SAFELY!) 26:57 Paige's role as a Product manager in DeepMind 29:46 Paige shares what it's like to work in a constantly innovating space as a product manager. 33:36 When should you establish an AI research team in your startup? 35:45 Using GPT-4 to finetune your smaller models for commercial use isn't allowed (But it's good tho!) 37:48 Paige's suggestions for Model Fine-tuning 41:42 AI will not increase the gap b/w rich and poor (Hopefully!) 44:33 AI's effects on job roles and eligibility requirements 48:56 Master's or PhD degree may not be as relevant in the AI age 51:19 Paige's advice for AI newcomers 54:31 Is having theoretical knowledge of the technology behind models relevant? 56:13 Paige's tips for good team communication 59:20 Communication tips for job-seeking newcomers 01:01:15 Paige shares the kind of features she wants in the AI 01:03:11 Paige suggests skills for beginners who want to enter MLOps.

In this episode, we explore the world of AI ethics and governance with an expert, delving into responsible AI practices, the balance between innovation and regulation, and the role of ethics in AI development and deployment. Gain insights on the challenges and solutions in aligning AI technologies with societal values and legal frameworks. Please leave a 5-star review and follow the podcast. You'll learn a lot of cool stuff, I promise. References: ►Learn more about Auxane:Her linkedin: https://www.linkedin.com/in/auxane-boch-2a958511b/ Her website: https://bochauxane.wixsite.com/auxane-boch Links discussed in the interview: https://www.ieai.sot.tum.de/publications-and-reports/research-briefs/https://aiethicscourse.org/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Become a member of the YouTube community, support my work and get a cool Discord role : https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Chapters: 0:00 Hey! Please leave a 5-star review and follow the podcast. You'll learn a lot of cool stuff, I promise. 00:59 Responsible AI vs AI Governance explained 02:24 Steps to become AI responsible 06:21 Are AI regulations hampering the progress of AI? 07:35 Self-regulation in private companies 12:07 Are companies compelled to implement AI ethics? 15:39 Are companies hesitant about AI ethics? 16:24 Engaging with stakeholders regarding AI regulations 17:31 Assisting startups toward responsible AI 21:57 Societal Values and Responsible AI 27:49 Should regulations be determined by one officer or collaboratively? 30:48 Understanding the risk factors of the startup in terms of AI ethics 36:01 Do companies act irresponsibly without being aware of it? 37:36 Does a low entry barrier lead developers to overlook the solution-market fit? 40:35 Implement this to improve AI governance and responsible use? 46:22 Are AI governance challenges due to the novelty of the technology? 48:21 How does Auxane find ways to implement Responsible AI? 51:21 Do ethics problems stem from developer unawareness rather than AI itself? 55:59 Best place to learn AI ethics 58:27 When and how to reach out to Auxane? 59:04 Issue of AI ethics not been talked about frequently 59:58 Making AI ethics videos interesting

Welcome to this special episode of the What’s AI podcast. Today, it’s just you and me, no guests. For the new listeners, my name is Louis Bouchard, and I am currently doing a PhD in AI at Polytechnique Montreal and Mila. I wanted to take the time to talk about what I am doing: my Ph.D. in artificial intelligence. This episode is for you whether you are thinking of doing a Ph.D. or simply if you are curious and want to learn more about what’s it like to do a Ph.D. and do research in artificial intelligence. I wanted to demystify a bit what it is, what it looks like, or at least, in my case, in biomedical engineering. In this episode, I will cover my personal experience with the Ph.D. in general, doing research in AI, the challenges and reasons for doing a Ph.D., and more about how I’m using AI to help the medical field. Ask any questions or connect with me on Twitter/X: https://twitter.com/Whats_AI

Join us in this captivating episode as we dive into the world of AI with Aleksa Gordić, ex-research scientist at DeepMind turned startup founder. Discover his unique journey from DeepMind to launching his own innovative startup, Ortus. Gain valuable insights on breaking into the AI field without a formal degree and landing a software engineer role at top tech companies. Explore the future of AI in video creation, productivity-enhancing tips, and the impact of AI on content creation. Don't miss out on this informative and inspiring conversation that delves into the latest advancements in AI. Listen now on to learn from Aleksa's experiences and stay ahead in the fast-evolving AI landscape. Try Ortus: https://www.ortusbuddy.ai/ Aleksa's LinkedIn: https://www.linkedin.com/in/aleksagordic/ Timestamps: 00:06 Intro 00:40 Aleksa's current priorities. 02:54 Work at DeepMind 07:05 Why Aleksa drop-out from Masters? 09:54 How did Aleksa land a software engineer role in ML without an official degree? 14:46 Get an AI job at DeepMind or Microsoft without a master's degree 18:18 Secure a research role at DeepMind 21:47 Aleksa's open-source work 22:34 Aleksa shares how he got into DeepMind 23:54 Did Aleksa face challenges in getting into DeepMind due to not having a master's or Ph.D. degree? 25:58 Why Aleksa left DeepMind? 28:07 Has AI made things more challenging by increasing competition? 32:08 What is Ortus? 34:15 How is Ortus doing better than its competitors? 36:32 Will Aleksa integrate article and blog parsing into Ortus? 37:37 How did your technical expertise aid in the creation of Ortus? 40:11 Challenges that were much more complex than anticipated  42:44 Challenges that were much easier than anticipated? 43:45 Doing everything alone vs. building a team 44:48 Hiring a generalist 48:54 Can a person who excels in one area but lacks interest in other subjects still achieve success? 51:25  Is there an easy path to success for the average person? 57:13 Next step for Ortus 58:02 AI will change content creation 01:00:20 Future of AI in video creation 01:02:05 Use cases for AI-generated video content 01:06:02 Aleksa shares his productivity-enhancing resources and tips 01:08:56 Discussion about habits and the 'Atomic habits' book 01:12:03 Feeling of urgency is the key to productivity 01:14:33 Benefits of Physical training 01:20:21 Outro

In this podcast episode, I interview Petar Veličković, a research scientist at DeepMind. We discuss his academic background and his journey from competitive programming to machine learning. Petar shares insights on the value of a PhD, emphasizing its role as an entry ticket into research and the opportunity it provides to build connections and adaptability. He also highlights the evolving landscape of AI research, where diverse backgrounds and contributions are essential. Overall, the interview offers valuable perspectives on academia, industry, and the importance of curiosity in driving impactful research. ►Twitter: https://twitter.com/PetarV_93, https://twitter.com/Whats_AI ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Timestamps: 00:05 Intro 00:37 Academic Background of Petar 02:07 The switch into the Machine Learning 05:33 Was Ph.D. worth it? 14:26 Is a Ph.D. worth it if you want to become a MLOps or a developer? 19:15 What was more useful to you to find research work at DeepMind? 22:28 Skills and portfolio tips for non-Ph.D. person to get into Google DeepMind 30:08 Work of research scientist at DeepMind 33:52 Promising avenue for AGI 42:36 Travel time prediction algorithm that was implemented in Google Maps 48:26 Why Petar wants to do more applied research projects? 51:07 Biggest challenges in AI research vs AI in the industry 53:37 Do you believe Graph Neural Network is the future? 58:07 Upcoming Projects of Petar

My interview with Jay Alammar, widely known inthe AI and NLP field mainly through his great blog on transformers and attention. ►Watch on YouTube: https://youtu.be/TO0IV9e2MMQ ►LLM University: https://docs.cohere.com/docs/llmu ►Jay's blog: http://jalammar.github.io/illustrated-transformer/ ►Twitter: https://twitter.com/JayAlammar, https://twitter.com/Whats_AI ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/ Become a member of the YouTube community, support my work and get a cool Discord role : https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 00:43 Introduction of Jay Alammar 04:00 Why Jay got into AI 8 years ago? 08:07 Why teach after learning 16:12 What is a Transformer? 21:03 What the blocks are made of and how they work? 26:27 Training steps of LLM explained in simple words 39:31 Re-rank Systems 41:47 How to know that your problem can be solved by LLM? 45:31 Chatbot on private or proprietary data 47:10 Challenges with AI Apps 50:51 The requirement to create AI apps 56:11 Mitigate model hallucination from your side 59:05 How does ChatGPT work with any language you type in? 01:02:56 AI evolution in next few years 01:05:38 Jay wants AI to be able to do this 01:08:10 AI apps used by Jay 01:10:10 Projects of Jay

Welcome to another episode of the What's AI Podcast, where we dive deep into the world of artificial intelligence and its various applications. In this episode, we have a special guest, Luis Serrano, an AI scientist, YouTuber, and author, known for his popular YouTube channel, Serrano.Academy, and his book, "Grokking Machine Learning." Currently, he is working at Cohere, where he is involved in building a groundbreaking resource called LLM University. Watch the episode (and more videos) on YouTube: https://youtu.be/NoyQKKQdI0M References: ► Cohere's LLM U: https://docs.cohere.com/docs/llmu ► Cohere's Discord community for LLM U: https://discord.gg/co-mmunity ► Luis' YouTube: ⁠ @SerranoAcademy ⁠ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether 00:06 Intro 00:33 Introduction and Background of Luis Serrano 02:17 Why did Luis pursue LLM? 02:59 Requirements to learn NLP and AI 05:32 Is a Ph.D. worth it? 07:56 Is learning fully online good or not? 09:50 What is a LLM? 13:00 Why learn AI if you only want to use it? 14:50 Practical use case of LLMs 16:12 Build application using Cohere 19:10 Base skills to use LLMs 19:10 Programming language to use LLMs 25:27 Prompting 29:23 Optimism about Prompt Engineering 29:42 Be a Better Prompt Engineer 31:32 Advice for non-AI people 35:17 Use AI without prior coding knowledge 37:32 Is there a job that does not require learning AI? 40:43 Overview of LLM University 45:07 LLM University is beginner friendly 47:40 Tips to explain better 58:10 Variety in AI learners 01:00:43 Personal project of Luis Serrano

This new episode features Felix Tao, CEO of Mindverse AI, and his years of experience working as a researcher at Facebook and Alibaba, mostly involved in language applications and AI. In this interview, Felix gives his insights on the evolution of AI, large language models, and finding the right balance between research and application. ►Felix Tao: https://www.linkedin.com/in/felix-tao-96456623/ ►Mindverse AI: https://www.mindverse.ai/ ►Twitter: https://twitter.com/Whats_AI ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/ ►Support me on Patreon: https://www.patreon.com/whatsai ►Join Our AI Discord: https://discord.gg/learnaitogether Chapters: 00:00:06 Intro 00:00:35 Introduction of Felix Tao 00:01:57 Is Ph.D. still worth it? 00:03:52 Is the research path still relevant? 00:07:36 Future of Ph.D. in A.I. 00:09:26 Work at Facebook 00:14:35 Waking up of A.I. consciousness 00:21:56 Future of Large Language Models in specific tasks 00:27:51 Aim of Mindverse with MindOs 00:31:59 Mindverse's take on mitigating the risk of hallucinations 00:38:04 Is hallucination-free output possible? 00:39:58 Tough challenge faced by Mindverse 00:45:38 Improve your work using Mindverse and MindOs 00:53:48 The thing A.I. need to have in future 00:55:56 Upcoming challenges in A.I. 00:58:04; A.I. in next five years 01:00:01 Can ChatGTP improve further?