Our guest today is Sebastian Raschka, Senior Staff Research Engineer at Lightning AI and bestselling book author.In our conversation, we first talk about Sebastian's role at Lightning AI and what the platform provides. We also dive into two great open source libraries that they've built to train, finetune, deploy and scale LLMs.: pytorch lightning and litgpt. In the second part of our conversation, we dig into Sebastian's new book: "Build and LLM from Scratch". We discuss the key steps ...

Our guest today is Loubna Ben Allal, Machine Learning Engineer at Hugging Face 🤗 . In our conversation, Loubna first explains how she built two impressive code generation models: StarCoder and StarCoder2. We dig into the importance of data when training large models and what can be done on the data side to improve LLMs performance. We then dive into synthetic data generation and discuss the pros and cons. Loubna explains how she built Cosmopedia, a dataset fully synthetic generated using Mixt...

Our guest today is Petar Veličković, Staff Research Scientist at Google DeepMind and Affiliated Lecturer at University of Cambridge.In our conversation, we first dive into how Petar got into Graph ML and discuss his most cited paper: Graph Attention Networks. We then dig into DeepMind where Petar shares tips and advice on how to get into this competitive company and explains the difference between research scientists and research engineering roles. We finally talk about applied work that Peta...

Our guest today is Lewis Tunstall, LLM Engineer and researcher at Hugging Face and book author of "Natural Language Processing with Transformers". In our conversation, we dive into topological machine learning and talk about giotto-tda, a high performance topological ml Python library that Lewis worked on. We then dive into LLMs and Transformers. We discuss the pros and cons of open source vs closed source LLMs and explain the differences between encoder and decoder transformer architectures....

Our guest today is Maria Vecthomova, ML Engineering Manager at Ahold Delhaize and Co-Founder of Marvelous MLOps.In our conversation, we first talk about code best practices for Data Scientists. We then dive into MLOps, discuss the main components required to deploy a model in production and get an overview of one of Maria's project where she built and deployed a fraud detection algorithm. We finally talk about content creation, career advice and the differences between an ML and an MLOps engi...

Our guest today is Reah Miyara. Reah is currently working on LLMs evaluation at OpenAI and previously worked at Google and IBM. In our conversation, Reah shares his experience working as a product lead for Google's graph-based machine learning portfolio. He then explains how he joined OpenAI and his role there. We finally talk about LLMs evaluation, AGI, LLMs safety and the future of the field. If you enjoyed the episode, please leave a 5 star review and subscribe to the AI Stories Youtube ch...

Our guest today is Erwin Huizenga, Machine Learning Lead at Google and expert in Applied AI and LLMOps. In our conversation, Erwin first discusses how he got into the field and his previous experiences at SAS and IBM. We then talk about his work at Google: from the early days of cloud computing when he joined the company to his current work on Gemini. We finally dive into the world of LLMOps and share insights on how to evaluate LLMs, how to monitor their performances and how to deploy...

Our guest today is Andras Palffy, Co-Founder of Perciv AI: a startup offering AI based software solutions to build robust and affordable autonomous systems. In our conversation, we first talk about Andras' PhD focusing on road users detection. We dive into AI applied to autonomous driving and discuss the pros and cons of the most common pieces of hardware: cameras, lidars and radars. We then focus on Perciv AI. Andras explains why he decided to focus on radars and how he uses Deep Learning...

Our guest today is Franziska Kirschner, Co-Founder of Intropy AI and ex AI & Product Lead at Tractable: the world’s first computer vision unicorn. In our conversation, we dive into Franziska's PhD, her career at Tractable and her experience building deep learning algorithms for computer vision products. She explains how she climbed the ladder from intern to AI Lead and shares how she launched new AI product lines generating £ millions in revenues. If you enjoyed the episode, please...

Our guest today is Maxime Labonne, GenAI Expert, book author and developer of NeuralBeagle14-7B, one of the best performing 7B params model on the open LLM leaderboard. In our conversation, we dive deep into the world of GenAI. We start by explaining how to get into the field and resources needed to get started. Maxime then goes through the 4 steps used to build LLMs: Pre training, supervised fine-tuning, human feedback and merging models. Throughout our conversation, we also discuss RAG vs...

Our guest today is Harpreet Sahota, Deep Learning Developer Relations Manager at Deci AI.  In our conversation, we first talk about Harpreet’s work as a Biostatistician and dive into A/B testing. We then talk about Deci AI and Neural Architecture Search (NAS): the algorithm used to build powerful deep learning models like YOLO-NAS. We finally dive into GenAI where Harpreet shares 7 prompting tips and explains how Retrieval Augmented Generation (RAG) works.  If you enjoyed the episode,...

Our guest today is Ryan Shannon, AI Investor at Radical Ventures, a world-known venture capital firm investing exclusively in AI. Radical's portfolio includes hot startups like Cohere, Covariant, V7 and many more.  In our conversation, we talk about how to start an AI company & what makes a good founding team. Ryan also explains what he and Radical look for when investing and how they help their portfolio after the investment. We finally chat about some cool AI Startups like Twelve Labs...

Our guest today is Christoph Molnar, expert in Interpretable Machine Learning and book author.  In our conversation, we dive into the field of Interpretable ML. Christoph explains the difference between post hoc and model agnostic approaches as well as global and local model agnostic methods. We dig into several interpretable ML techniques including permutation feature importance, SHAP and Lime. We also talk about the importance of interpretability and how it can help you build better models...

Our guest today is Demetrios Brinkmann, Founder and CEO of the MLOps Community. In our conversation, Demetrios first explains how he transitioned from being an English teacher to working in sales and then founding the MLOps community. He also talks about the role of MLOps in the ML lifecycle and shares a bunch of resources to level up your MLOps skills. We then dive into the hot topic of GenAI and LLMOps where Demetrios shares his view on specialised vs generalised LLMs and why it can be...

Our guest today is Noah Gift, MLOps Leader and award winning book author. Noah has over 30 years of experience in the field and has taught to hundreds of thousands of students online. In our conversation, we first talk about Noah's experience building data pipelines in the movie industry and his experience in the startup world. We then dive into MLOps. Noah highlights the importance of MLOps,  outlines the Software Engineering best practices that Data Scientists must learn and explains why...

Our guest today is Marianne Ducournau, Head of Data Science at Qonto and ex Data Scientist at Amazon and Uber. In our conversation, we first discuss Marianne's first job in Data Science working in the public sector and managing a 10-15 people team. Marianne then talks about her experience at Uber and shares various projects that she worked on. We dive into price elasticity modelling and financial forecasting where her team built thousands of model to forecast financial metrics in multiple...

Our guest today is Christof Henkel, Senior Deep Learning Data Scientist at NVIDIA and world number 1 on Kaggle: a competitive machine learning platform. In our conversation, we first discuss Christof's PhD in mathematics and talk about the importance of maths in a Data Science career. Christof then explains how he started on Kaggle and how he progressed on the platform to become the world number 1 amongst millions of users. We also dive into recent competitions that he won and the algorithms...

Our guest today is Davis Blalock, Research Scientist and first employee of Mosaic ML; a startup which got recently acquired by Databricks for an astonishing $1.3 billion. In our conversation, we first talk about Davis' PhD at MIT and his research on making algorithms more efficient. Davis then explains how and why he joined Mosaic and shares the story behind the company. He dives into the product and how they evolved from focusing on deep learning algorithms to generative AI and large...

Our guest today is Kellin Pelrine, Research Scientist at FAR AI and Doctoral Researcher at the Quebec Artificial Intelligence Institute (MILA). In our conversation, Kellin first explains how he defeated a superhuman Go-playing AI engine named KataGo 14 games to 1. We talk about KataGo’s weaknesses and discuss how Kellin managed to identify them using Reinforcement Learning. In the second part of the episode, we dive into Kellin’s research on building practical AI systems. We dig into his...

Our guest today is Chanuki Seresinhe, head of Data Science at Zoopla,  a company which provides millions of users with access to properties for sale and for rent. In our conversation, we first talk about Chanuki’s PhD where she used machine learning to identify relationships between beautiful places and happiness. We then dive into Data Science at Zoopla and talk about Generative AI and other exciting projects that Chanuki is currently working on. Throughout the episode, Chanuki shares...

Our guest today is Rémi Ounadjela, Senior Data Science Manager at TikTok and ex-Data Scientist at Google and Amazon.  During the first part of our conversation, Rémi talks about his experience working on shipment optimisation at Amazon and on Data Science for risk and safety at TikTok.  During the second part, we discuss the differences between working as a Data Scientist at TikTok, Google and Amazon. Rémi also shares advice on how to get into Big Tech and the common mistakes that you should...

Our guest today is Barr Moses, Co-Founder & CEO of Monte Carlo, the first end-to-end data observability platform.  In our conversation, we first talk about how Barr got into the field and the early influence of her parents. Barr shares her previous experiences working with data in the Israeli Army and working on data strategy at Bain.  We then dig into Monte Carlo and the new field of DataOps along with data observability and its 5 pillars . Barr explains how and why she founded this...

Our guest today is Parul Pandey, Principal Data Scientist at H2O.ai, Kaggle Grandmaster (notebooks) & book author of “Machine Learning for High Risk Applications”.  In our conversation, we first dig into Kaggle. Parul explains how she became a Grandmaster, shares tips about data analysis and discusses the pros of learning on Kaggle.  The second part of the episode is around machine learning for high risk applications. We talk about the risks of using AI to make decisions, talk about...

Our guest today is Marijn Markus, Managing Data Scientist at Capgemini.  In our conversation, we first talk about data analysis to model and visualise the spread of Ebola. We then dig into crime analysis back to when Marijn worked with the police in the Netherlands. Marijn also shares his thoughts on the importance of causal inference and the value that humans can add to AI algorithms.  We then explore machine learning applied to the consulting sector and discuss the pros and cons of working...