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Artificial Intelligence, Machine Learning, Data Science and Deep Learning are completely changing the world we live in today. Companies around the world start to make sensible use of big data to influence business decisions and create our future. From video recommendations to autonomous driving, from stock prediction to weather forecasting, the AI revolution is everywhere. The AI stories podcast brings together some of the best Data Scientists, Machine Learning Engineers, Business leaders and researchers that are at the front of this revolution. They are here to talk about their career, how they arrive where they are, give advice and share their vision. They explain how they make use of AI in their daily routine, how they use algorithms to solve business problems and make the world a better place. They are here to share their stories: their AI stories. Hosted by Neil Leiser, Data Scientist at Iwoca. Follow Neil to learn more about career, Data Science, AI and Machine Learning. Linkedin: https://www.linkedin.com/in/leiserneil/ Twitter: https://twitter.com/LeiserNeil
62 Episodes
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Our guest today is Dawn Choo, founder of Interview Master and ex Data Scientist from Amazon and Meta. In our conversation, we first dive into Dawn's past Data Science projects at Amazon and Instagram. She explains how a pet project skyrocketed her career at Amazon and also shares details on the most impactful project that she worked on at Instagram. We then discuss Dawn's experience living in a van for a year before digging into Interview Master: a platform to help Data Scientists...
Our guest today is Ritchie Vink, CEO & Founder of Polars: an open source data manipulation library known for being extremely fast. As of today, polars has over 32k stars on github. In our conversation, Ritchie first explains how Polar which started as a side project evolved to what it is today. We then discuss the differences between Polars and Pandas, why Polars is fast and optimised and dig into Polars cloud: a platform which manages the compute infrastructure, allowing users to f...
Our guest is Philippe Mizrahi, CEO of Linkup: a french startup building the world's best search agents. In our conversation, Philippe first shares how he got into search by building an internal dataset search tool at Lyft. We then dive into Linkup where Phil explains how linkup started, how it evolved and how they managed to build the best search agents achieving state-of-the-art results on OpenAI SimpleQA dataset. If you enjoyed the episode, please leave a 5 star review and subsc...
Our guest is Samuel Colvin, Co-Founder and CEO of pydantic: a data validation library with millions of downloads per month. In our conversation, we first discuss Pydantic and their observability platform: logfire. We then dive into agents where Samuel shares his vision on how to build production ready agents and what makes PydanticAI different than other frameworks. If you enjoyed the episode, please leave a 5 star review and subscribe to the AI Stories Youtube channel. 👉 From beg...
👉 From beginner to advanced LLM developer course by Towards AI (use the code AISTORIES10 to get a 10% discount): https://academy.towardsai.net/courses/beginner-to-advanced-llm-dev?ref=63e5e3 👉 8-hour GenAI Primer course by Towards AI (use the code AISTORIES10 to get a 10% discount): https://academy.towardsai.net/courses/8-hour-genai-primer?ref=63e5e3 Our guest today is Max Buckley, Senior Software Engineer at Google. From business analyst intern to Senior LLM engineer at Google! Max ha...
👉 From beginner to advanced LLM developer course by Towards AI (use the code AISTORIES10 to get a 10% discount): https://academy.towardsai.net/courses/beginner-to-advanced-llm-dev?ref=63e5e3 👉 8-hour GenAI Primer course by Towards AI (use the code AISTORIES10 to get a 10% discount): https://academy.towardsai.net/courses/8-hour-genai-primer?ref=63e5e3 Our guest today is Wojtek Kuberski, Co-Founder and CTO at NannyML. In our conversation, we first discuss Wojtek's experience working as a fre...
Our guest today is Thomas Scialom, Senior Staff Research Scientist at Meta. In our conversation, we first discuss Thomas' PhD where he explains how he managed to publish around 20 academic papers. We then dive into several LLMs that Thomas built at Meta including Galactica, Llama 2 and Llama 3. We finally dig into AI Agents, their limitations and how close we are to AGI and ASI. If you enjoyed the episode, please leave a 5 star review and subscribe to the AI Stories Youtube channel. 👉 Fr...
Our guest today is Başak Eskili, Machine Learning Engineer at Booking.com and C-Founder of Marvelous MLOps. In our conversation, we first dive into MLOps, its key components and how Başak got into the field. We then talk about Marvelous MLOps and her new course: "End to end MLOps with Databricks". Başak finally shares more about her current role at Booking with a focus on building feature stores. If you enjoyed the episode, please leave a 5 star review and subscribe to the AI Stories Yout...
Our guest today is Max Mergenthaler, Co-Founder and CEO of Nixtla: one of the most popular libraries for time series forecasting. In this conversation, Max first explains how he got into AI and the lessons he learned from building a couple of tech startups. We then dive into Nixtla and forecasting. Max explains how he founded Nixtla and the different libraries available to build stats, ml and deep learning forecasting algorithms. We also tallk about TimeGPT, Nixtla's closed-source foundat...
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 st...
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 ...
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 ...
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 architecture...
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 en...
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 Youtub...
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 them...
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 ...
1Our 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 le...
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 epis...
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