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Gemini Embedding: Powering RAG and context engineering
Explore how organizations leverage Gemini Embedding for context-aware AI systems improving performance, accuracy, and efficiency across diverse industries.
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 1,227 posts.
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What If We Had Bigger Brains? Imagining Minds Beyond Ours
Stephen Wolfram explores how the number of neural connections affects capabilities like language and abstraction. How far we could go accounting for neural nets and LLMS, the fundamental nature of computation, neuroscience and the operation of brains.
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Why today's humanoids won't learn dexterity
In this post I explain why today’s humanoid robots will not learn how to be dexterous despite the hundreds of millions, or perhaps many billions of dollars, being donated by VCs and major tech companies to pay for their training.
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A PM's Guide to AI Agent Architecture
A complete guide to agent architecture, orchestration patterns, trust strategies, and adoption plans for PMs building AI agents.
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Eleven Music
Studio-grade music generated with natural language prompts in any style and for countless uses
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AI helps ship faster but it produces 1.7× more bugs
We analyzed 470 open-source GitHub pull requests, using CodeRabbit’s structured issue taxonomy and found that AI generated code creates 1.7x more issues.
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Just talk to it – A way of agentic engineering
A practical guide to working with AI coding agents without the hype.
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State of AI: An Empirical 100T Token Study with OpenRouter
Read OpenRouter's 2025 State of AI report — an empirical 100 trillion token study of real LLM usage, model trends, and developer insights.
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Bamba: An open-source LLM that crosses a transformer with an SSM
The open-source LLM combines the sequence-modeling skill of a transformer with the inferencing speed of an SSM. IBM Granite will soon adopt key Bamba features.
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How to Train an AI Image Model on Yourself
It takes less than an hour and $3.
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Subliminal learning: Models transmit behaviors via hidden signals in data
We study subliminal learning , a surprising phenomenon where language models learn traits from model-generated data that is semantically unrelated to those traits. For example, a "student" model learns to prefer owls when trained on sequences of numbers generated by a "teacher" model that prefers owls. This same…
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AI is impressive because we've failed at personal computing
AI is impressive because we’ve failed at semantic web and personal computing | exotext
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Most AI value will come from broad automation, not from R & D
AI's biggest impact will come from broad labor automation—not R&D—driving economic growth through scale, not scientific breakthroughs.
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The new calculus of AI-based coding
A collection of posts by Joe Magerramov
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How Google built its Gemini robotics models
Robots powered by Gemini Robotics models can learn complex actions like preparing salads and even folding an origami fox.
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New antibiotic targets IBD and AI predicted how it would work
[...]Read More...
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Scamlexity: When agentic AI browsers get scammed
We Put Agentic AI Browsers to the Test - They Clicked, They Paid, They Failed
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We ran over 600 image generations to compare AI image models
We benchmarked OpenAI gpt-image-1, Google nanoBanana, and Seedream across 600+ real-world photo edits, see latency, cost, and quality by task
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Searching for DeepSeek's glitch tokens
A first attempt at identifying and cataloging DeepSeek's glitched tokens
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I announced my divorce on Instagram and then AI impersonated me
After maintaining a total stance of public silence for months, I recently publicly announced my unexpected divorce on Instagram. I shared a picture of the divorce cake that my friends got for me, and shared a brief essay I had drafted the day before about the news. I had to edit it down slightly from my original draft…
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People are just as bad as my LLMs
Last year I created a fun little experiment where I asked a bunch of LLMs to rank 97 hackernews users using their comment history based on whether they would be good candidates for the role of “software engineer at google”. (yes yes, seems silly I know, you can read part 1 and part 2 but […]
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Rethinking CLI interfaces for AI
We need to augment our command line tools and design APIs so they can be better used by LLM Agents. The designs are inadequate for LLMs as they are now – especially if you're constrained by the tiny context windows available with local models.
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When AI promises speed but delivers debugging hell
Lessons learned from building Codescribble with a little help (and a lot of frustration) from an AI
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Beyond Diffusion: Inductive Moment Matching
Inductive Moment Matching surpasses diffusion models in speed and sample quality.
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Intellect-2 Release: The First 32B Model Trained Through Globally Distributed RL
We're excited to release INTELLECT-2, the first 32B parameter model trained via globally distributed reinforcement learning. Unlike traditional centralized training efforts, INTELLECT-2 trains a reasoning language model using fully asynchronous RL across a dynamic, heterogeneous swarm of compute contributors.
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Getting DeepSeek-OCR working on an Nvidia Spark via brute force with Claude Code
DeepSeek released a new model yesterday: DeepSeek-OCR, a 6.6GB model fine-tuned specifically for OCR. They released it as model weights that run using PyTorch and CUDA. I got it running …