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Introduction to Reinforcement Learning (2015)
Build AI responsibly to benefit humanity
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 3,240 posts.
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Prefrontal cortex as a meta-reinforcement learning system
Recently, AI systems have mastered a range of video-games such as Atari classics Breakout and Pong. But as impressive as this performance is, AI still relies on the equivalent of thousands of hours of gameplay to reach and surpass the performance of human video game players. In contrast, we can usually grasp the…
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What will our economic future look like?
The Anthropic Economics Team models the effects of AI on the economy of 2030.
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Apple Intelligence Foundation Language Models Tech Report 2025
We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and…
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Computer use in Gemini 3.5 Flash
A look at the built-in computer use tool in Gemini 3.5 Flash.
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Standardizing OpenAI’s deep learning framework on PyTorch
We are standardizing OpenAI’s deep learning framework on PyTorch.
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How does misalignment scale with model intelligence and task complexity?
Research done as part of the first Anthropic Fellows Program during Summer 2025.
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The future of deep learning
This post is adapted from Section 3 of Chapter 9 of my book, Deep Learning with Python (Manning Publications).
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Joint Statement on AI Safety and Openness
We are at a critical juncture in AI governance. To mitigate current and future harms from AI systems, we need to embrace openness, transparency, and broad access.
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New Map APIs from Google
Introducing new AI-powered products and tools from Google Maps Platform. Learn more
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AlphaFold 2 is here: what’s behind the structure prediction miracle
Nature has now released that AlphaFold 2 paper , after eight long months of waiting. The main text reports more or less what we have known for nearly a year, with some added tidbits, although it is accompanied by a painstaking description of the architecture in the supplementary information . Perhaps more importantly…
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LM Studio 0.3 – Discover, download, and run local LLMs
LM Studio 0.3.0 is here! Built-in (naïve) RAG, light theme, internationalization, Structured Outputs API, Serve on the network, and more.
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Announcing Wolfram Alpha Pro
Today I’m excited to be able to announce the launch of Wolfram|Alpha Pro —the biggest single step in the development of Wolfram|Alpha since its original introduction.
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Graph Networks for Materials Exploration
We share the discovery of 2.2 million new crystals – equivalent to nearly 800 years’ worth of knowledge. We introduce Graph Networks for Materials Exploration (GNoME), our new deep learning tool that dramatically increases the speed and efficiency of discovery by predicting the stability of new materials.
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OpenAI's GPT-6 Astra on ARC-AGI-3
OpenAI's GPT-6 Astra reaches state-of-the-art results on ARC-AGI-3
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MCP in LM Studio
New in LM Studio 0.3.17: Model Context Protocol (MCP) Host support. Connect MCP servers to the app and use them with local models.
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Meta's open AI hardware vision
At the Open Compute Project (OCP) Global Summit 2024, we’re showcasing our latest open AI hardware designs with the OCP community. These innovations include a new AI platform, cutting-edge open rac…
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Progress on provable inference for large language models
Sharing progress on a powerful type of cryptographic proof known as a zkSNARK, which is uniquely fit for provable inference.
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Figma AI
We’re introducing a suite of AI-powered features to help you push past creative blocks and bring your best ideas to life.
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Introducing Preemptible GPUs
In May 2015, Google Cloud introduced Preemptible VM instances to dramatically change how you think about (and pay for) computational resources for high-throughput batch computing, machine learning, scientific and technical workloads. Then last year, we introduced lower pricing for Local SSDs attached to Preemptible…
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Google search and search engine spam
Insights from Googlers into our products, technology, and the Google culture
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LM Studio 0.4
Server deployment, parallel requests with continuous batching, new REST API endpoint, and refreshed application UI
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Separating signal from noise in coding evaluations
A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.
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AI as Normal Technology
We articulate a vision of artificial intelligence (AI) as normal technology . To view AI as normal is not to understate its impact—even transformative, general-purpose technologies such as electricity and the internet are “normal” in our conception. But it is in contrast to both utopian and dystopian visions of the…
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3D Gaussian Splatting as Markov Chain Monte Carlo
Novel view reconstructions for (right) our method and (left) conventional 3D Gaussian Splatting with random initializations. Our method, even with random initialization, faithfully reconstructs the scene (e.g.. buildings at the back and the ground texture) providing much higher quality renderings.
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