Practical AI: Machine Learning, Data Science
Technology
Daniel and Chris explore the intersection of Kaggle and real-world data science in this illuminating conversation with Christof Henkel, Senior Deep Learning Data Scientist at NVIDIA and Kaggle Grandmaster. Christof offers a very lucid explanation into how participation in Kaggle can positively impact a data scientist’s skill and career aspirations. He also shared some of his insights and approach to maximizing AI productivity uses GPU-accelerated tools like RAPIDS and DALI.
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Timestamps:
(00:00) - Welcome to Practical AI
(00:41) - Christof Henkel
(01:57) - What is Kaggle?
(07:34) - How has Kaggle helped?
(09:38) - Deep Learning 5-6 years ago
(11:05) - What were the changes like?
(14:10) - Sponsor: Changelog++
(15:09) - How Kaggle compares to real life
(21:56) - Any Kaggle highlights?
(24:04) - How to climb the Kaggle ladder?
(26:39) - Accelerated GPUs in Kaggle
(30:25) - Speeding up my process
(34:37) - What comes up in the discussions?
(37:36) - Getting started
(41:06) - What's next for Christof
(42:57) - Outro
AI in the U.S. Congress
First impressions of GPT-4o
Full-stack approach for effective AI agents
Autonomous fighter jets?!
Private, open source chat UIs
Mamba & Jamba
Udio & the age of multi-modal AI
RAG continues to rise
Should kids still learn to code?
AI vs software devs
Prompting the future
Generating the future of art & entertainment
YOLOv9: Computer vision is alive and well
Representation Engineering (Activation Hacking)
Leading the charge on AI in National Security
Gemini vs OpenAI
Data synthesis for SOTA LLMs
Large Action Models (LAMs) & Rabbits 🐇
Collaboration & evaluation for LLM apps
Advent of GenAI Hackathon recap
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