Hallucinations in code are the least dangerous form of LLM mistakes
A surprisingly common complaint I see from developers who have tried using LLMs for code is that they encountered a hallucination—usually the LLM inventing a method or even a full …
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How I use LLMs
The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series o...
Building A Generative AI Platform
This post outlines the common components of a generative AI platform, what they do, and implementation considerations. It'll start from the simplest architecture and progressively add more components: context construction, guardrails, router, gateway, cache, agentic workflows, orchestration, and observability.
Read these if you want to build AI applications
Join me to Master Python for AI Projects 👉 https://python-course-earlybird.framer.website/Get data science/ AI insights in your inbox 👉 https://thu-vu.ck.p...
From ML Engineering to AI Engineering
Title: From ML Engineering to AI EngineeringDate: June 27, 2024Duration: 1 HRSPEAKERChip HuyenVP of AI & OSS, Voltron DataMODERATORAlejandro SaucedoDirector ...
AI Engineering with Chip Huyen
On today’s episode of The Pragmatic Engineer, I’m joined by Chip Huyen, a computer scientist, author of the freshly published O’Reilly book AI Engineering, a...
Deep dive into LLMs like ChatGPT by Andrej Karpathy (TL;DR) | Anfal Mushtaq
A TL;DR version of Andrej Karpathy's "Deep dive into LLMs like ChatGPT" video.
Understanding Reasoning LLMs
Methods and Strategies for Building and Refining Reasoning Models
Considerations for Chunking for Optimal RAG Performance – Unstructured
Learn about the importance of chunking for RAG, choosing optimal chunk sizes, text splitting methods, and advanced smart chunking strategies to enhance your RAG system's performance.
Mixture of Experts Explained
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Great Resources for Learning and Implementing Retrieval-Augmented Generation (RAG)
Few great and free resources to learn about RAG and its usage in Generative AI.
Prompt patterns for LLMs that help you design better software
Large language models (LLMs) may not be replacing developers anytime soon, but can still be of use in the design process.
AI Prompt: Writing Supabase Edge Functions | Supabase Docs
Supabase is an open source Firebase alternative providing all the backend features you need to build a product.
Deep Dive into LLMs like ChatGPT
This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full traini...
The Ultimate Guide to bolt.new Prompting: Build Better Apps Without Deep Technical Knowledge
A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team
Is DeepSeek Legit? Breaking Down All Major Allegations
Start a VPS cost effectively with Hostinger today and use discount code "BYCLOUD" for an extra 10% off! http://hostinger.com/bycloudWatch my last videohttps:...
oumi-ai/oumi: Everything you need to build state-of-the-art foundation models, end-to-end.
Everything you need to build state-of-the-art foundation models, end-to-end. - oumi-ai/oumi
Om-Alve/smolGPT
17-445 Machine Learning in Production / AI Engineering
Ask HN: How to learn AI from first principles? | Hacker News
The Illustrated DeepSeek-R1
A recipe for reasoning LLMs
Docker Image BEST Practices - From 1.2GB to 10MB
Want to dramatically reduce your Docker image size? In this comprehensive guide, I'll show you how to shrink your Docker images from gigabytes to just megaby...
No Hype DeepSeek-R1 Reading List | Oxen.ai
DeepSeek-R1 is a big step forward in the open model ecosystem for AI with their latest model competing with OpenAI's o1 on a variety of metrics. There is a lot of hype, and a lot of noise around the fact that they achieved this with much less money and compute. Source: https://x.com/karpathy/status/1872362712958906460 Instead of learning about it from AI influencer* threads hyping up the release, I decided to make a reading list that links to a lot of the fundamental research papers. This list
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Learn EVERYTHING You Need to Know About AI From a Top AI Expert
🚀 AI Explained for Everyone – Full Crash Course in 10 Minutes! 🚀Let’s break down Artificial Intelligence (AI) into simple concepts. From understanding what...
(1) Agent Engineering in 2025 - YouTube
Enjoy the videos and music that you love, upload original content and share it all with friends, family and the world on YouTube.
Understanding and Effectively Using AI Reasoning Models
With the imminent release of OpenAI's -o3 reasoning model and Deepseek's impressive R1 release, it's clear that reasoning models are improving rapidly. But, ...
Building Effective Agents with LangGraph
Anthropic's recent blog post on "Building Effective Agents" lays out the difference between "agents" and "workflows", and presents a number of common pattern...
No, Deepseek R1 is NOT "better" than o1 BUT you get 25x COMPUTE
🔥 Is Deepseek R1 REALLY better than o1? The answer might surprise you! But one thing’s for sure: with 25x more compute, you can SCALE YOUR IMPACT like never...