Sign up to save your podcasts
Or
Share Episode 21: Deploying LLMs in Production: Lessons Learned
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Episode 21: Deploying LLMs in Production: Lessons Learned
Hugo speaks with Hamel Husain, a machine learning engineer who loves building machine learning infrastructure and tools đ·. Hamel leads and contributes to many popular open-source machine learning projects. He also has extensive experience (20+ years) as a machine learning engineer across various industries, including large tech companies like Airbnb and GitHub. At GitHub, he led CodeSearchNet (https://github.com/github/CodeSearchNet), a large language model for semantic search that was a precursor to CoPilot. Hamel is the founder of Parlance-Labs (https://parlance-labs.com/), a research and consultancy focused on LLMs.
They talk about generative AI, large language models, the business value they can generate, and how to get started.
They delve into
Where Hamel is seeing the most business interest in LLMs (spoiler: the answer isnât only tech);
Common misconceptions about LLMs;
The skills you need to work with LLMs and GenAI models;
Tools and techniques, such as fine-tuning, RAGs, LoRA, hardware, and more!
Vendor APIs vs OSS models.
LINKS
Our upcoming livestream LLMs, OpenAI Dev Day, and the Existential Crisis for Machine Learning Engineering with Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs): Sign up for free! (https://lu.ma/m81oepqe/utm_source=vghh)
Our recent livestream Data and DevOps Tools for Evaluating and Productionizing LLMs (https://youtube.com/live/B_DMMlDuJB0) with Hamel and Emil Sedgh, Lead AI engineer at Rechat -- in it, we showcase an actual industrial use case that Hamel and Emil are working on with Rechat, a real estate CRM, taking you through LLM workflows and tools.
Extended Guide: Instruction-tune Llama 2 (https://www.philschmid.de/instruction-tune-llama-2) by Philipp Schmid
The livestream recoding of this episode! (https://youtube.com/live/l7jJhL9geZQ?feature=share)
Hamel on twitter (https://twitter.com/HamelHusain)
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hugobowne.substack.com
They talk about generative AI, large language models, the business value they can generate, and how to get started.
They delve into
Where Hamel is seeing the most business interest in LLMs (spoiler: the answer isnât only tech);
Common misconceptions about LLMs;
The skills you need to work with LLMs and GenAI models;
Tools and techniques, such as fine-tuning, RAGs, LoRA, hardware, and more!
Vendor APIs vs OSS models.
LINKS
Our upcoming livestream LLMs, OpenAI Dev Day, and the Existential Crisis for Machine Learning Engineering with Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs): Sign up for free! (https://lu.ma/m81oepqe/utm_source=vghh)
Our recent livestream Data and DevOps Tools for Evaluating and Productionizing LLMs (https://youtube.com/live/B_DMMlDuJB0) with Hamel and Emil Sedgh, Lead AI engineer at Rechat -- in it, we showcase an actual industrial use case that Hamel and Emil are working on with Rechat, a real estate CRM, taking you through LLM workflows and tools.
Extended Guide: Instruction-tune Llama 2 (https://www.philschmid.de/instruction-tune-llama-2) by Philipp Schmid
The livestream recoding of this episode! (https://youtube.com/live/l7jJhL9geZQ?feature=share)
Hamel on twitter (https://twitter.com/HamelHusain)
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hugobowne.substack.com
View all episodes
By Hugo Bowne-Anderson
5
1111 ratings
Hugo speaks with Hamel Husain, a machine learning engineer who loves building machine learning infrastructure and tools đ·. Hamel leads and contributes to many popular open-source machine learning projects. He also has extensive experience (20+ years) as a machine learning engineer across various industries, including large tech companies like Airbnb and GitHub. At GitHub, he led CodeSearchNet (https://github.com/github/CodeSearchNet), a large language model for semantic search that was a precursor to CoPilot. Hamel is the founder of Parlance-Labs (https://parlance-labs.com/), a research and consultancy focused on LLMs.
They talk about generative AI, large language models, the business value they can generate, and how to get started.
They delve into
Where Hamel is seeing the most business interest in LLMs (spoiler: the answer isnât only tech);
Common misconceptions about LLMs;
The skills you need to work with LLMs and GenAI models;
Tools and techniques, such as fine-tuning, RAGs, LoRA, hardware, and more!
Vendor APIs vs OSS models.
LINKS
Our upcoming livestream LLMs, OpenAI Dev Day, and the Existential Crisis for Machine Learning Engineering with Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs): Sign up for free! (https://lu.ma/m81oepqe/utm_source=vghh)
Our recent livestream Data and DevOps Tools for Evaluating and Productionizing LLMs (https://youtube.com/live/B_DMMlDuJB0) with Hamel and Emil Sedgh, Lead AI engineer at Rechat -- in it, we showcase an actual industrial use case that Hamel and Emil are working on with Rechat, a real estate CRM, taking you through LLM workflows and tools.
Extended Guide: Instruction-tune Llama 2 (https://www.philschmid.de/instruction-tune-llama-2) by Philipp Schmid
The livestream recoding of this episode! (https://youtube.com/live/l7jJhL9geZQ?feature=share)
Hamel on twitter (https://twitter.com/HamelHusain)
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hugobowne.substack.com
They talk about generative AI, large language models, the business value they can generate, and how to get started.
They delve into
Where Hamel is seeing the most business interest in LLMs (spoiler: the answer isnât only tech);
Common misconceptions about LLMs;
The skills you need to work with LLMs and GenAI models;
Tools and techniques, such as fine-tuning, RAGs, LoRA, hardware, and more!
Vendor APIs vs OSS models.
LINKS
Our upcoming livestream LLMs, OpenAI Dev Day, and the Existential Crisis for Machine Learning Engineering with Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs): Sign up for free! (https://lu.ma/m81oepqe/utm_source=vghh)
Our recent livestream Data and DevOps Tools for Evaluating and Productionizing LLMs (https://youtube.com/live/B_DMMlDuJB0) with Hamel and Emil Sedgh, Lead AI engineer at Rechat -- in it, we showcase an actual industrial use case that Hamel and Emil are working on with Rechat, a real estate CRM, taking you through LLM workflows and tools.
Extended Guide: Instruction-tune Llama 2 (https://www.philschmid.de/instruction-tune-llama-2) by Philipp Schmid
The livestream recoding of this episode! (https://youtube.com/live/l7jJhL9geZQ?feature=share)
Hamel on twitter (https://twitter.com/HamelHusain)
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hugobowne.substack.com
More shows like Vanishing Gradients
View all
The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
538 Listeners
Making Sense with Sam Harris
26,332 Listeners
The a16z Show
1,087 Listeners
Super Data Science: ML & AI Podcast with Jon Krohn
302 Listeners
Founders
2,169 Listeners
The Prof G Pod with Scott Galloway
5,545 Listeners
Machine Learning Street Talk (MLST)
95 Listeners
Dwarkesh Podcast
501 Listeners
No Priors: Artificial Intelligence | Technology | Startups
131 Listeners
AI + a16z
35 Listeners
Prof G Markets
1,430 Listeners
Lightcone Podcast
21 Listeners
Training Data
39 Listeners
High Signal: Data Science | Career | AI
19 Listeners
Cheeky Pint
48 Listeners