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Ranking top AI chatbots over the past year by user experience, visibility, & momentum, v/OneLittleWeb: bit.ly/3HxnmM7 ChatGPT came in first, with Grok & Gemini rounding out the top three.
This paper didn’t go viral but it should have. A tiny AI model called HRM just beat Claude 3.5 and Gemini. It doesn’t even use tokens. They said it was just a research preview. But it might be the first real shot at AGI. Here’s what really happened and why OpenAI should be…
10 GitHub repos that will set you up for a career in AI engineering (100% free):
Anthropic is killing it with these technical posts. If you're an AI dev, stop what you are doing and go read this. It shows, in great detail, how to implement an effective multi-agent research system. Pay attention to these key parts:
AI agents are the future, but how well do you understand them? This one-page guide breaks down everything you need to know about AI agents: from how they work to where they're used 👇 1. Core Concepts That Power Agents Understand key ideas like Goal Decomposition,…
There’s a new breed of GenAI Application Engineers who can build more-powerful applications faster than was possible before, thanks to generative AI. Individuals who can play this role are highly sought-after by businesses, but the job description is still coming into focus. Let…
🚨 BREAKING: Microsoft just dropped an 18-episode series called "Generative AI for Beginners". Ideal for beginners, developers, and AI enthusiasts looking to build a solid foundation. Here’s a breakdown (Save this👇):🧵
Google literally published a 69-page prompt engineering masterclass
Microsoft launched the best course on AI Agents! AI Agents for Beginners The Free 10 lesson course is available on Github and will teach you the basics of building AI Agents
Writing software, especially prototypes, is becoming cheaper. This will lead to increased demand for people who can decide what to build. AI Product Management has a bright future! Software is often written by teams that comprise Product Managers (PMs), who decide what to build…
Machine Learning cheatsheets from Stanford's CS 229:
Machine Learning cheatsheets form Stanford's CS 229:
🚀 I'm excited to announce the future of prompt engineering: 𝚎𝚕𝚕. developed from ideas during my time at OpenAI, 𝚎𝚕𝚕 is light, functional lm programming library: - automatic versioning & tracing - rich local oss visualization tools - multimodality native Read on ⬇️
LLM Visualization This is actually pretty amazing! It helps to visualize the core components of LLMs like nano-gpt and GPT-3.
Python is powerful! 🔥 You can create an Audiobook in just a few lines of code! 🚀 Check this out👇
Replit Agents just changed the game. They can code full apps, install packages, configure databases, and even deploy software for you. 10 wild examples:
We've all dealt with activation functions while working with neural nets. - Sigmoid - Tanh - ReLu & Leaky ReLu - Gelu Ever wondered why they are so important❓🤔 Let me explain it to... 👇
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Exploratory Data Analysis (EDA) projects in Python programming for beginners here:
Microsoft Research introduces AutoGen Studio, a low-code interface for rapidly prototyping AI agents. It's built on top of the AutoGen framework and can also be used for debugging and evaluating multi-agent workflows.
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