logo
đź”’

Member Only Content

To access all features, please consider upgrading to full Membership.

AI Ecosystem Intelligence Explorer

AI Fundamentals

21 of 85 articles

A Practical Guide to Implementing DeepSearch/DeepResearch

QPS out, depth in. DeepSearch is the new norm. Find answers through read-search-reason loops. Learn what it is and how to build it.

Research
AI Fundamentals
 
2/25/2025

GitHub - smartaces/Anthropic_Claude_Sonnet_3_7_extended_thinking_colab_quickstart_notebook

Contribute to smartaces/Anthropic_Claude_Sonnet_3_7_extended_thinking_colab_quickstart_notebook development by creating an account on GitHub.

LLM
AI Fundamentals
 
2/25/2025

Aman’s AI Journal • Natural Language Processing • Attention

Aman’s AI Journal | Course notes and learning material for Artificial Intelligence and Deep Learning Stanford classes.

AI Fundamentals
 
2/23/2025

Aman’s AI Journal • Primers • Agents

Aman’s AI Journal | Course notes and learning material for Artificial Intelligence and Deep Learning Stanford classes.

AI Fundamentals
 
2/23/2025

The Ultra-Scale Playbook - a Hugging Face Space by nanotron

The ultimate guide to training LLM on large GPU Clusters

AI Fundamentals
 
2/20/2025

AI Mistakes Are Very Different From Human Mistakes

We need new security systems designed to deal with their weirdness

Harm and Risk
AI Fundamentals
 
2/18/2025

GitHub - saurabhaloneai/Llama-3-From-Scratch-In-Pure-Jax: This repository contain the simple llama3 implementation in pure jax.

This repository contain the simple llama3 implementation in pure jax. - GitHub - saurabhaloneai/Llama-3-From-Scratch-In-Pure-Jax: This repository contain the simple llama3 implementation in pure…

AI Fundamentals
 
2/17/2025

LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU

Full explanation of the LLaMA 1 and LLaMA 2 model from Meta, including Rotary Positional Embeddings, RMS Normalization, Multi-Query Attention, KV-Cache, Grou…

AI Fundamentals
 
2/17/2025

On word embeddings - Part 3: The secret ingredients of word2vec

Word2vec is a pervasive tool for learning word embeddings. Its success, however, is mostly due to particular architecture choices. Transferring these choices to traditional distributional methods makes them competitive with popular word embedding methods.

AI Fundamentals
 
2/17/2025
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only
Members Only