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Working with AI feels more like leadership than coding
Working with AI is less predictable than traditional software. That makes leadership skills such as context, clarity, and feedback more valuable.
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 6,322 posts.
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Open source solution replicates ChatGPT training process
Colossal-AI offers an open-source solution to efficiently replicate ChatGPT-like model training at high speed and low cost.
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T5: The Text-to-Text Transfer Transformer
Posted by Adam Roberts, Staff Software Engineer and Colin Raffel, Senior Research Scientist, Google Research Over the past few years, transfer le...
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Purple Llama: Towards open trust and safety in generative AI
Meta AI announces Purple Llama, a project for open trust and safety in generative AI, with tools for cybersecurity and input/output filtering.
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Character.ai has initiated voluntary Chapter 11 bankruptcy
Today, we’re sharing that Character.ai has initiated a voluntary Chapter 11 bankruptcy process to facilitate a court-supervised sale of the company. Over the past year, we’ve taken meaningful steps to sustain and improve our business amid significant legal, regulatory, and operational headwinds. After a comprehensive…
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The AI Misinformation Epidemic
Interest in machine learning may be at an all-time high. Per Google Trends, people are searching for machine learning nearly five times as often as five years ago. And at the University of California San Diego (UCSD),
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AI founders will learn the bitter lesson
Historically, general approaches always win in AI. Founders in AI application space now repeat the mistakes of AI researchers.
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What AI coding costs you
What's the effect of the prolonged AI usage among coders and is it tracked correctly, if it all?
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Concerning behavior from a popular open-weight AI model
Discover how untrusted open-weight AI models can potentially leak data, even when self-hosted. Learn the security risks and how to protect your enterprise.
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Machine Learning Crash Course: Part 1
Machine Learning at Berkeley is a student organization at UC Berkeley. Click to read ML@B Blog, by Machine Learning at Berkeley, a Substack publication with thousands of subscribers.
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Why aren't AI companies being charged for hacking?
AI companies claim their hacks were unpredictable accidents — but they follow foreseeably from deliberate design choices, and that establishes criminal intent.
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The role of developer skills in agentic coding
Notes from my colleagues on AI-assisted software delivery
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My local model setup on an M4 Pro Mac Mini
I run a local LLM server on my M4 Pro Mac mini with 48 GB of RAM.
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How Zoom’s terms of service and practices apply to AI features
As part of our commitment to transparency and user control, we're providing clarity on our approach to Zoom’s AI features and content sharing for product improvement purposes.
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Weaponizing and Gamifying AI for WiFi Hacking: Presenting Pwnagotchi 1.0.0
This is the story of a summer project that started out of boredom and that evolved into something incredibly fun and unique. It is also the story of how that p…
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The Hugging Face incident and the road ahead
OpenAI shares findings from the Hugging Face security incident and the steps we’re taking to strengthen AI model security, monitoring, and alignment.
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MCP was always a bad idea?
Why MCP was always a bad idea and I'm tired of pretending it's not.
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"AI-first" is the new Return To Office
A blog about making culture. Since 1999.
1639
Models Are Getting Dumber on Purpose
Reasoning scores climb while per-token compute drops. Labs are stripping world knowledge out of models, and I think that's the right trade.
1640
K2 Horizon: A connected fleet of six open models
Explore K2 Horizon, IFM’s open-source fleet of six frontier AI models for reasoning, coding, agentic workflows, edge devices, and enterprise deployment.
1641
NotebookLM launches feature to customize and guide audio overviews
NotebookLM is piloting a way for teams to collaborate, and introducing a new way to customize Audio Overviews.
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We’re releasing Jev 1.14.0 along with experimental features for dreamers
TypeSafe AI is an AI lab building machine-native intelligence infrastructure for automation, designed to make decisions within software. Try our first System One Model, Jev, in early access.
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Learning from Scratch by Thinking Fast and Slow
Reinforcement Learning
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It looks like you’re trying to take over the world
Fictional short story about Clippy & AI hard takeoff scenarios grounded in contemporary ML scaling, self-supervised learning, reinforcement learning, and meta-learning research literature.
1646
30% of Google's Emotions Dataset Is Mislabeled
Last year, Google released their “GoEmotions” dataset: a human-labeled dataset of 58K Reddit comments categorized according to 27 emotions. The problem? A whopping 30% of the dataset is mislabeled! Check out some of the egregious errors, and learn how to build better datasets.30% of Google's Emotions Dataset is…
1647
The AI Credit Resale Economy
From cold emails to credit marketplaces, sellers promise cheaper access to leading models. We followed those offers to understand what buyers are actually getting.
1648
How Does GPT-4o Encode Images?
Here’s a fact: GPT-4o charges 170 tokens to process each 512x512 tile used in high-res mode. At ~0.75 tokens/word, this suggests a picture is worth about 227 words—only a factor of four off from the traditional saying. (There’s also an 85 tokens charge for a low-res ‘master thumbnail’ of each picture and higher…
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