Luis Serrano, an AI scientist, YouTuber, and author, discusses the importance of diverse backgrounds in AI, the potential of online learning, and the components of large language models. He also explores the skills needed to use LLMs in applications and the role of prompt engineering in AI. Additionally, he talks about using AI for resume screening and the relevance and accessibility of AI education.

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?

Join us this week for a fascinating conversation on the What’s AI podcast, where Yotam Azriel, co-founder of TensorLeap, shares his fascinating journey, insights, and vision for the future of Explainable AI. Discover what the power of passion, curiosity, and focus can accomplish! Yes, I didn’t mention school or university voluntarily, as Yotam is a successful data scientist… without any formal university degree! ►Tensorleap: https://tensorleap.ai/?utm_source=YouTube&utm_medium=video&utm_campaign=Louis%20Bouchard%20&utm_id=Louis%20Bouchard%20&utm_term=Tensorleap&utm_content=Explanatory%20video ►Yotam Azriel: https://www.linkedin.com/in/yotam-azriel-01a953142/ ►Listen on Spotify: https://open.spotify.com/show/4rKRJXaXlClkDyInjHkxq3 ►Listen on Apple podcasts: https://podcasts.apple.com/ca/podcast/whats-ai-by-louis-bouchard/id1675099708 ►Twitter: https://twitter.com/tensorleap, https://twitter.com/Whats_AI ►Support me on Patreon: https://www.patreon.com/whatsai ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/ ►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. 00:26 Who are you and what’s your background? 04:39 And how did you find that job? 06:14 What would you recommend to someone from a different background who wants to get into the field? 08:23 So would you recommend having some sort of incentive to learn? 10:05 Why do you assume you’re not cut off for academia if you like writing and reading papers? 15:00 What is Tensorleap and what do you do there? 21:28 What is Explainability AI and please give an example of a technique? 27:35 Could you give an example of how an explainability AI technique could help improve or understand the SAM model? 31:39 Would the same explainability AI technique work for different architectures? 36:30 Can we do anything to understand the results of the model better when we work with pre-trained models? 40:20 What are the basics for someone new to the field who wants to get into explainability AI and use it to better understand their model and its results? 42:48 Should everyone creating AI models also be familiar with explainability and be able to understand the decisions of the models they create? 45:21 If the model's explanation is right or not you might need an expert in the specific field? 52:20 Is there a way to better understand models that are used through API’s, their decisions and why they answer the way they did? 56:15 Is the ultimate goal for explainability AI to do anything it can to understand the AI model? 58:50 Did you search into neurosciences and try to implement some of their ideas on artificial networks and vice versa? 01:01:20 How do you see the explainability AI field in 5 years? 01:03:27 What are the possible risks with explainability AI? 01:04:56 Who should use Tensorleap and why?

An interview with David Mertz, senior developer, data scientist, and author, who explores the fascinating world of generative AI and its applications in coding and AI coding assistants like Copilot and ChatGPT. ►David's Linkedin: https://www.linkedin.com/in/dmertz/ ►David's Book (David provided the code podwhatsai23 for 35% off for the listeners!): http://mng.bz/D4wg ►Follow on Twitter: https://twitter.com/Whats_AI ►My Newsletter: 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/ Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 1:59 Why did you get into the field of political science? 4:04 What is AI-generated? 9:06 What are the best insights from your books? 15:03 What are the dangers of using ChatGPT as a coding assistant? 16:45 Where do you draw the line from using a writing assistant to AI-generated? 18:38 Will AI coding assistants affect programming innovation? 20:49 Limitations of AI coding assistants... 27:27 How will AI coding affect copyrighting vs. other changes like the invention of the printer? 34:40 What can people who use or develop AI models do to help progress with copyrights and moral rights? 37:29 Watermarking in AI 41:05 Would you recommend using ChatGPT and/or Copilot? 43:25 What legal issues should the people using such technologies be afraid or careful of? 45:48 Are you optimistic regarding generative AI?

Everything you need to know about GPT, large language models and OpenAI with Logan Kilpatrick, Developer Advocate at OpenAI! References: ►Follow on Twitter: https://twitter.com/Whats_AI, https://twitter.com/OfficialLoganK ►My Newsletter: 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/ Chapters: 0:00 Leave a like if you enjoy the episode! Let me know who you'd like me to receive. 00:43 Who are you and what’s your background? 02:40 How long have you been doing your PHD? 04:29 What are your thoughts on the value of a PHD 06:10 What do you think is the ideal path for someone who would like to work in the AI field? 07:10 Would you say graduate studies are required to succeed in the AI field? 08:36 How did you get into OpenAI without a PHD? 11:03 Can you explain how it is to apply in OpenAI and the interview process? 12:58 Did they expect you to know what they offer and how their products work? 14:50 Can you explain what you're doing on Twitter? 16:41 Can you explain the difference between ChatGPT and GPT4? 17:16 What is GPT? 17:38 What is a token? 18:09 Can you explain what alignment is? 18:46 What is RLHF? 19:23 What is a prompt and a prompt engineer? 20:18 What is a modality and a multi-modal model? 20:49 What is model hallucination? 21:37 What is a GPT agent? 22:20 Are you excited about agents or do you think it's overrated? 23:43 What is an AGI? 24:47 Do you have tips about how to make the model be more human when writing? 27:02 How many examples of your style should GPT see to imitate you? 28:00 Do you have any tips to help avoid hallucination or plagiarism in the content? 31:46 Could you describe what is a developer advocate and what you do in your day to day life? 35:27 How are you helping developers who are using OpenAI's products? 39:19 Could you give an insight on what it's like to work at OpenAI? 43:47 Are there any steps that you are taking to ensure that the technology is being used in a responsible way? 47:45 What is the most interesting product that you've seen using OpenAI's products? 56:28 Are there any products that you've seen using GPT that help you personally for productivity? 58:17 Do you have any tips on better using ChatGPT for coding? 59:40 Are there any upcoming interesting features or products that aren't released yet 01:01:15 Are there any common recurring mistakes that you help developers with? 01:05:44 What would be your tips to get started implementing something from OpenAI when having no programming skills? 01:07:35 If programming wouldn't be required are there any other skills that would be? 01:08:08 What are the different GPT models and which should be used when? 01:10:06 When would you use the different GPT models available? 01:12:28 Is there anything you wish AI could do but can't do yet? 01:13:45 What is the biggest challenge the AI industry is facing right now? 01:14:41 How do you see AI evolving for the next 5 years? 01:17:40 What else are you working on?

This interview is with Limarc Ambalina, VP of Editorial at HackerNoon, on AI-generated content in the realm of writing and journalism! Get insights into his journey and how AI can enhance the writer's experience. References: ►Limarc Ambalina: https://www.linkedin.com/in/limarc-ambalina-11604371/ ►HackerNoon: https://hackernoon.com/ ►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 ►Support me through wearing Merch: https://whatsai.myshopify.com/ ►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. 00:30 Who are you and what’s your background? 02:52 Are you planning on going back to writing novels? 03:48 Did you end up developing a passion for AI? 05:50 Can you explain what HackerNoon is? 06:52 To you, what is AI generated content? 12:00 Are there any tools or algorithms that have been integrated to? 18:32 Are you allowing AI generated content on HackerNoon? 22:57 Are you afraid of AI generated content being the norm? 25:25 How many of the 300-400 weekly articles are AI generated? 26:38 Is the proportion of well performing AI generated content the same as human written content? 28:54 Have you seen any good articles that seem completely AI generated? 31:10 Do you envision any copyright issues with this AI generated content? 34:34 Should the credit go to the real authors or the AI that was trained on open data? 37:00 If a piece makes money what is the worst that can happen legally speaking? 40:57 Is AI creative? 44:14 Can an AI writing assistant make a difference in the writing quality? 52:30 Do you think AI generated content should be penalized in SEO 55:53 Do you think nowadays it’s necessary to use AI to compete with all other content? 57:06 Are you running a plagiarism check on submitted pieces? 58:45 If people want to write more and use ChatGPT safely, do you have general guidelines to give them? 1:00:33 Will more people get into writing thanks to ChatGPT? 01:01:44 What are your favorite AI tools for writing or editing? 01:07:32 How do you think AI is changing the landscape of journalism and media? #ai #writing #journalism

Are you considering pursuing a Ph.D. in machine learning? Or just wondering how to get into the AI field, how to become Twitter famous, or even just how to find a first job/internship? Before you take the plunge, take a moment to listen to this insightful interview with Brian Burns, Ph.D. candidate at the University of Washington and founder of the AI Pub Twitter account. References: ►YouTube Episode: https://youtu.be/M0aLFZegaec ►Brian's Twitter AI Pub: https://twitter.com/ai__pub ►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 ►Support me through wearing Merch: https://whatsai.myshopify.com/ ►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. 00:35 Who are you and what's your background? 01:53 What was your reason for starting a PHD? 03:06 Why did you choose the graduate studies path? 04:29 Do you think the time invested in the PHD is worth the certification? 14:19 What do you think that is more important when matching a company with an individual? 19:43 How are you matching people and finding candidates? 22:35 How are you matching people and finding candidates? 29:02 Why is Twitter useful and why should one have an account? 31:54 Is it difficult to share the most advanced algorithms while making it accessible in short threads? 34:43 Do you have any tip for people who want to explain their own work in a simple way? 38:35 How are you staying up-to-date with the progress in AI? 42:30 How do you get a viral Twitter post? 46:00 How much time does it take to grow a Twitter account? 48:32 How do you decide which paper is worth sharin 51:38 How are you engaging with your Twitter audience? 53:50 Are there any challenges that we don't expect to see when managing a Twitter account? 55:58 How do you monetize your Twitter account? 59:57 How are you managing Twitter controversies and polarizing topics? 01:01:54 What's the most challenging thing about hosting a podcast? 01:06:13 What do you enjoy most about hosting a podcast? 01:07:12 Are you planning on interviewing other kind of background and researchers? 01:08:10 Will you stick with research papers for your podcast? 01:09:55 How has social media impacted the way AI research is communicated and shared with the broader public? 01:13:00 Would you say Twitter has a positive impact on the research industry? 01:14:40 What is your next project and what are you working on?

In this podcast, Louis Bouchard interviews Jérémy Cohen, founder and CEO of Think Autonomous. They discuss the self-driving car industry, ML-related roles, and how to break into the industry. They touch on topics such as LIDAR technology, salary expectations, the value of online course certificates, challenges of finding self-driving car companies, and the importance of computer vision in the field.

An interview with Sander Schulhoff, creator of learnprompting.org, the largest prompting resource online. Watch the video version on YouTube: https://youtu.be/BNrPs3ANz1E References: ►Listen on Spotify: ►Listen on Apple podcasts: ►Learn prompting: https://learnprompting.org/ ►Twitter: https://twitter.com/learnprompting, 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 ►Support me through wearing Merch: https://whatsai.myshopify.com/ ►Join Our AI Discord: https://discord.gg/learnaitogether Chapters: 0:00 Hey! I hope you enjoy this interview. Follow to learn more about AI and prompting with amazing upcoming guests! 00:30 Who are you? What's your background? 01:40 How where you involved with reinforcement learning? 03:10 How was AI used within Minecraft? 06:04 What made you transition into prompting? 07:03 What is learnprompting.org? 08:57 How does prompting work? What are common types of prompting? Is it only in English? 10:48 What can you improve with prompting vs. just natural language and talking with another human being? 13:49 How do LLM work? Why are they able to understand and generate text? Why can’t it be able to understand us like other humans do? 15:51 Is the main thing that LLM’s lack emotion? Or is there another big difference? 17:27 Can you give an example of where you used prompting? 19:11 Can you give more details on what is Lang Chain and how it’s used? 20:17 How can one benefit from using prompting vs. Googling the answer? 24:38 Can you get paid by being a prompt engineer? 25:55 What do prompt engineers do? What are their tasks? 30:40 Who can become a prompt engineer? 32:48 Is there any way to measure that you are improving and going in the right direction for improving prompts for a specific task? 35:24 How would you recommend people to learn prompting? 37:57 Is prompt engineering a job for the future? 39:00 Do you think prompt engineering might get better and better as to in the end replace a human? 40:40 What are the differences in prompting between two separate models and a model over time? 42:24 Is there a way to be sure you’re not specializing on only one model? 43:54 Is it important for prompt engineers to better understand models? 45:49 Could you explain the difference between fine tuning and prompting? 49:29 Are there any misconceptions that you often need to clarify to those new to prompting? 51:46 Do you see any clear limitations of prompting? 55:12 What are the biggest challenges you see for prompting? 56:23 Was GPT-3 trained to be unbiased? 58:43 Did you solve the issue of ChatGPT not having only one word? 01:00:38 Why do you think it’s so difficult to output only one word? 01:01:37 Do you think the model doesn’t listen or it doesn't understand? 01:02:55 Can you think of any ethical problems that may arise because of this new technology? 01:04:09 What are you currently working on? What’s your next project?

This is an interview with Or Gorodissky, VP of R&D at an amazing generative AI startup called D-ID. This was my first-ever interview! I hope you will still enjoy this mini-series put together and take some good bits of advice out of it... The first part of this interview focuses on Or's academic background, his Master's degree, and recommendations for doing one and a Ph.D. We then discuss the differences and resemblances between industry vs. academia. In the second part, we dive into the startup world and, more precisely, the application process and how to optimize your profile to find a job in generative AI as a researcher, ml engineer, or data scientist. Or also explains how he identifies good candidates and gives great tips to improve your resume and stand out. We also dive into who can work as an AI research scientist in generative AI startups and the importance of background differences. Finally, the third and last part is about working in the startup world. How it is, what is day-to-day life like, applying research papers in the real world, developing state-of-the-art applications, and more!