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RA-DIT, or Retrieval-Augmented Dual Instruction Tuning, is a method for fine-tuning both the LLM and the retriever in a RAG setup to enhance overall response quality

I just sat down this morning and organized all deep learning related videos I recorded in 2021. I am sure this will be a useful reference for my future self,...

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Understanding the current state of LLM scaling and the future of AI research...

Foundation models enable many new application interfaces, but one that has especially grown in popularity is the conversational interface, such as with chatbots and assistants. The conversational interface makes it easier for users to give feedback but harder for developers to extract signals. This post will discuss what conversational AI feedback looks like and how to design a system to collect the right feedback without hurting user experience.

Local LLMs making a comeback, Nvidia's personal supercomputer, Anthropic's $6B round, OpenAI working on robotics

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Learn AI skills in 100 days. Free, fun, and effective 30-minute bite-sized lessons delivered to your inbox daily to guide your AI learning journey.

A summary of completing the 100 days of AI challenge. Plus all the Tweeted content.

Learn Prompting offers a comprehensive, free guide on Generative AI and Prompt Engineering, perfect for beginners and advanced users alike. Start your AI journey now!

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Want to find out what artificial intelligence is all about and what it means for your world? Here are the best books on AI.

From GitHub Copilot to ChatGPT to Claude Artifacts, how Val Town borrowed the best of all the code generation tools

Get the full doc (for community members): https://dub.link/ai_engineering_patternsGreg’s Info:- Twitter: https://tiny.one/nxlgp5K- Newsletter: https://tiny.o...

Learning how to build AI powered products

Most guides to generative AI are shit, so I will try my hand at one for you.

Discover how Meta AI's Chain of Continuous Thought (Coconut) empowers large language models (LLMs) to reason in their own language.

Keep your users updated with real-time task progress. Now with LLM streaming support and increased limits.

Turn websites into LLM-ready data. Build better RAG systems and train AI models with clean, structured web data. DataFuel handles the complex parts of web scraping, so you can focus on your AI innovations.

In recent years, the spotlight in AI has primarily been on large language models (LLMs) and emerging large multi-modal models (LMMs). Now, building on these ...

Identify which essay was written by a large language model

Everyone's saying 2025 is the year of Agents but there aren't a lot of baseline on what is an AI Agents! This video is exactly to explain AI Agents for Begin...

Want to really understand how large language models work? Here’s a gentle primer.

Everything that went wrong trying to make our LLMs say less.

Structured input/output, prefilling, n-shots prompting, chain-of-thought, reducing hallucinations, etc.

The Stackblitz and Qodo CEOs dish on building production coding agents, from going viral as the hottest new consumer/low-code agent, to the gnarliest enterprise deployments for code/test agents.

How did Bolt.new get to $8M of ARR in 2 months by being a Claude Wrapper? Today's episode with Eric Simons from Bolt.new / Stackblitz and Itamar Friedman fro...