Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, etc). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
Capabilities of LLMs 🤯
Large Language Model (LLM) capabilities have reached new heights and are nothing short of mind-blowing! However, with so many advancements happening at once, it can be overwhelming to keep up with all the latest developments. To help us navigate through this complex terrain, we’ve invited Raj - one of the most adept at explaining State-of-the-Art (SOTA) AI in practical terms - to join us on the podcast.
Raj discusses several intriguing topics such as in-context learning, reasoning, LLM options, and related tooling. But that’s not all! We also hear from Raj about the rapidly growing data science and AI community on TikTok.
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Featuring:
- Rajiv Shah – Twitter, GitHub, LinkedIn, Website
- Chris Benson – Twitter, GitHub, LinkedIn, Website
- Daniel Whitenack – Twitter, GitHub, Website
Show Notes:
- Solving AI Tasks with ChatGPT and its Friends in HuggingFace | GitHub
- Generative Agents: Interactive Simulacra of Human Behavior
- Wolfram ChatGPT
- Comparing LLMs
- LangChain
- Learn about LLMs:
- Learning Prompting
- Getting Started with Transformers:
- Training your own LLM Models:
- Dolly blog post
- Illustrating Reinforcement Learning from Human Feedback
Something missing or broken? PRs welcome!
Timestamps:
(00:00) - Welcome to Practical AI
(00:43) - Rajiv Shah
(01:55) - AI on TikTok?
(03:31) - Community engagement on TikTok
(04:49) - Ever-growing mind-blowing moments
(06:24) - Reaching different audiences
(07:57) - What is in-context-learning?
(10:52) - Prompt engineering with better models
(13:01) - Growing productive users
(14:52) - The landscape of large language models
(18:16) - Sorting through this delightful mess
(19:46) - Hugging Face highlights
(23:06) - Practical fine-tuning
(26:00) - What are we talking about?
(28:29) - Where does AI fit into education?
(30:20) - A different kind of consumer
(31:54) - Talking to the average Joe about AI
(34:02) - What do you see through the looking glass?
(36:06) - Great Hugging Face resources
(37:08) - Outro