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Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 3,242 posts.
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AI predicts effective depression treatment based on brainwave patterns
Tracking brainwave patterns and symptoms in patients with depression, researchers used artificial intelligence to predict best treatment options.
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Robot hand could harvest blackberries better than humans
The soft robotic gripper developed at the U of A received a U.S. patent.
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The Warp Agent CLI
The Warp Agent is now available as a standalone CLI that you can use anywhere – Ghostty, iTerm 2, VS Code, built-in Windows and Mac Terminals – and provides a superior experience for developers who do heavy terminal workflows.
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Using the term 'AI' in product descriptions reduces purchase intentions
Companies may unintentionally hurt their sales by including the words “artificial intelligence” when describing their offerings that use the technology, according to a study led by WSU researchers.
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INTELLECT–1: Launching the First Decentralized Training of a 10B Parameter Model
We're excited to launch INTELLECT-1, the first globally-distributed training run of a 10-billion-parameter model, inviting anyone to contribute compute and participate. This brings us one step closer towards open source AGI.
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Voyage-code-3
TL;DR – Introducing voyage-code-3, our next-generation embedding model optimized for code retrieval. It outperforms OpenAI-v3-large and CodeSage-large by an average of 13.80% and 16.81% on a suite …
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Open SWE: An open-source asynchronous coding agent
Open SWE is an open-source, cloud-hosted coding agent that autonomously handles GitHub tasks—planning, coding, testing, and opening PRs.
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Turning the Tables on AI
How about using it not to think less but *more*?
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3D Face Reconstruction with Position Map Regression Networks
Position Map Regression Networks (PRN) is a method to jointly regress dense alignment and 3D face shape in an end-to-end manner. In this article, I’ll provide a short explanation and discuss its applications in computer vision. When I was a… Continue reading 3D Face Reconstruction with Position Map Regression Networks
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Advanced coding in low-resource programming languages
Learn how OpenAI is improving ChatGPT across low-resource programming languages, with new evaluations for software engineering, SQLite, and COBOL migration.
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SynthID – A tool to watermark and identify content generated through AI
SynthID is a tool to watermark and identify AI-generated content, helping to foster transparency and trust in generative AI.
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Most users cannot identify AI bias, even in training data
When recognizing faces and emotions, artificial intelligence (AI) can be biased, like classifying white people as happier than people from other racial backgrounds. This happens because the data used to train the AI contained a disproportionate number of happy white faces, leading it to correlate race with emotional…
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Leveraging AI for efficient incident response
We’re sharing how we streamline system reliability investigations using a new AI-assisted root cause analysis system. The system uses a combination of heuristic-based retrieval and large language m…
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How Underground Groups Use Stolen Identities and Deepfakes
The growing appearance of deepfake attacks is significantly reshaping the threat landscape. These fakes brings attacks such as business email compromise (BEC) and identity verification bypassing to new levels.
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We reproduced Anthropic's Mythos findings with public models
Anthropic framed Mythos and Project Glasswing as proof that frontier AI vulnerability research now needs gated access. We tested the public, patched cases with GPT-5.4 and Claude Opus 4.6 and found that the key building blocks are already accessible outside Glasswing, while reliable operationalization remains the real…
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MTIA v1: Meta’s first-generation AI inference accelerator
In 2020, we initiated the Meta Training and Inference Accelerator (MTIA) family of chips to support our evolving AI workloads, starting with an inference accelerator ASIC for deep learning recommendation models (DLRMs).
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Asymmetric Quantization: Near-Lossless Retrieval with 97% Storage Reduction
Late interaction makes retrieval more precise but turns every document into many vectors. Asymmetric quantization keeps query vectors precise and stores…
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PaperBench
We introduce PaperBench, a benchmark evaluating the ability of AI agents to replicate state-of-the-art AI research.
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Quantifying the performance of the TPU, our first machine learning chip
We’re releasing a study that shares new details on our Tensor Processing Unit (TPU) custom chips which have been running machine learning applications in our data centers since 2015.
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Inversion: Fast, Reliable Structured LLMs
We create the world's fastest and most efficient AI.
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Segment Anything Model and Friends
The Segment Anything Model (SAM) and its successors made a significant leap forward in computer vision, particularly in image and video segmentation. Along with SAM’s innovative approach to promptable segmentation, the literature rapidly evolved to address key challenges like computational efficiency and real-time…
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Continuous batching to increase LLM inference throughput and reduce p50 latency
In this blog, we discuss continuous batching, a critical systems-level optimization that improves both throughput and latency under load for LLMs.
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KumoRFM: A Foundation Model for In-Context Learning on Relational Data
Introduction to Kumo Relational — the relational foundation model for predictive AI on relational data
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Deal or no deal? Training AI bots to negotiate
Visit the post for more.