Beyond Prompt Engineering: The Multi-Layered Cake of GenAI Development
The layers of GenAI development
Recent Posts
Mitigating LLM Hallucinations: a multifaceted approach
(I recently turned this guide into a paper. You can find it here)
On open source LLMs, take two: The three laws of GenAI model evolution
In this post I summarize the main advances in the area of LLM models, and particularly open source LLMs (including Falcon, LlaMa2, and Free Willy). I describe different leaderboards and what their ...
Prompt Engineering 201: Advanced methods and toolkits
DALL-E 2: An old professor with a notebook in his hand talking to a futuristic looking robot. 4k. Professional photo. Photorealistic
Some of my favorite Recsys resources and links
Introduction to recommender systems: Basics and classic techniques Beyond the basics Ranking Factorization machines Explore/exploit Full page optimization Co...
Towards Reinforcement Learning with AI Feedback (RLAIF). What open-sourced foundation models, instruction tuning, and other recent events mean for the future of AI
A few weeks back I shared my thoughts on how things were going to evolve in the race to build better/larger/smarter generative AI models, and particularly LLMs. Here is what I had to say:
Blueprints for recommender system architectures: 10th anniversary edition
Ten years ago, we published a post in the Netflix tech blog explaining our three-tier architectural approach to building recommender systems (see below). A lot has happened in the last 10 years in ...