What changed
Lab announcements and releases, deduped and threaded into the timeline of the field.
<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1uga687/a_debugger_for_rl_reward_functions_that_detects/"> <img alt="A debugger for RL reward functions that detects reward hacking during training [P]" src="https://preview.redd.it/r5m95bf5cn9h1.gif?width=640&crop=smart&s=f9e1900b5e007ea3a72c74d4089c56fdeed22f49" title="A debugger for RL reward functions that detects reward hacking during training [P]" /> </a> </td><td> <!-- SC_OFF --><div class="md"><p>While ex
<p>Article URL: <a href="https://www.bloodinthemachine.com/p/the-ai-industry-is-pouring-hundreds">https://www.bloodinthemachine.com/p/the-ai-industry-is-pouring-hundreds</a></p> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48687483">https://news.ycombinator.com/item?id=48687483</a></p> <p>Points: 24</p> <p># Comments: 8</p>
In this post, you’ll build a server that extracts text from PDF files in Amazon S3 in real time. This protocol-based approach provides programmatic document access. You’ll walk through the architecture, set up the server, and run interactive document queries. Along the way, you’ll compare this approach with Amazon Textract so you can decide which tool fits your workload.
In this post, we explore how Cara, built in cooperation with AWS, addresses these challenges. We walk through the technical design decisions and the AWS services that support the solution. We also share measurable outcomes Cara has delivered for enterprise brokerages.
In this post, you learn how Stripe built a production-grade AI agent system for financial compliance. We cover the technical architecture of Stripe’s ReAct agent framework and the infrastructure decisions behind a dedicated agent service. We also discuss the role of human oversight in maintaining accountability, and key lessons about task decomposition, orchestration patterns, and cost optimization through prompt caching. By the end, you will understand how to design agentic systems that scale c
<!-- SC_OFF --><div class="md"><p>My question on live continual learning use cases was removed by moderators here because they think i asked basic level question about live continual learning which i thought is a frontier level research. But anyways. Is anyone interested in talking about continual learning (live) and catastrophic forgetting? </p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/fourwheels2512"> /u/fourwheels2512 </a> <br /> <span><a href="https:
It's been two weeks since Anthropic took its Mythos-class models offline after a Friday evening ultimatum from the Trump administration. The company sprang into action immediately, sending a barrage of executives to Washington, DC. But updates have been suspiciously lacking, with no resolution in sight. Anthropic declined to comment multiple times this week about the […]
<!-- SC_OFF --><div class="md"><p>I'm proposing a way to handle massive context longer than a model's context window by treating semantic compression as the noise function of a diffusion-like process. Instead of denoising masked tokens into coherent text (like DiffusionGemma or Nemotron-Diffusion do for generation), the model reads the source document in multiple passes at decreasing compression levels, heavy summary first, verbatim last all the while it iteratively refines an "integration
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Aseon Labs, which came out of Y Combinator's 2026 spring cohort, has raised $10 million from Crane Venture Partners and others.
<p>Article URL: <a href="https://alephneuro.com/blog/ultrasound-brain">https://alephneuro.com/blog/ultrasound-brain</a></p> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48685558">https://news.ycombinator.com/item?id=48685558</a></p> <p>Points: 63</p> <p># Comments: 16</p>
<p>Article URL: <a href="https://aditya.patadia.org/p/ai-and-cloud-costs">https://aditya.patadia.org/p/ai-and-cloud-costs</a></p> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48683588">https://news.ycombinator.com/item?id=48683588</a></p> <p>Points: 86</p> <p># Comments: 104</p>
<!-- SC_OFF --><div class="md"><p>I've been developing an AI product using LLM APIs (from OpenRouter) but want to deploy an open-source LLM in my own Prod env. which I can control. </p> <p>Few reasons behind this are:</p> <p>- I wanna own the complete stack around my product.</p> <p>- Second I wanna fine-tune the model around my usecase. </p> <p>So, what's the most affordable but a good platform for this? I'm not an AI engineer so don't wanna stuck in CUDA or Transformers hell, anything which ca
<!-- SC_OFF --><div class="md"><p>Sharing a project I have been working on called Third Eye. It does visual geolocation. Given a video, it figures out where it was filmed using only the image content, and draws the route on a map.</p> <p>Pipeline in short:</p> <ul> <li>per frame place recognition against a street imagery index</li> <li>a trajectory search that stitches the frames into one coherent path</li> <li>a geometric verification step to catch false matches</li> </ul> <p>per frame confiden
<p>Article URL: <a href="https://www.fernandoi.cl/posts/hackmyclaw/">https://www.fernandoi.cl/posts/hackmyclaw/</a></p> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48681687">https://news.ycombinator.com/item?id=48681687</a></p> <p>Points: 287</p> <p># Comments: 120</p>
OpenAI reportedly plans to share its newest model, GPT 5.6, with a select group of partners instead of with the broader public. The reason: the Trump administration told it to.
<p>Liquid AI, founded by former MIT computer scientists, today released its smallest AI language model yet, <a href="https://www.liquid.ai/blog/lfm2-5-230m">LFM2.5-230M</a>, and enterprises would do well to consider it for their uses in data extraction and local deployment on smartphones, laptops and robotics.</p><p>This is a 230-million-parameter foundation model explicitly designed for on-device agentic workflows, and as Liquid states in its release blog post, that small size makes it possible
<!-- SC_OFF --><div class="md"><ol> <li><p>source files + final paper pdf.</p></li> <li><p>ZIP containing the source files and final paper.pdf.</p></li> </ol> <p>Where does the supplemental materiel get uploaded? Because in that email it says include it in a "supplementary_materiel" folder.</p> <p>this is all very confusing. can someone clarify?</p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/redskydawns"> /u/redskydawns </a> <br /> <span><a href=
The Trump administration, apprehensive of potential security issues, has reportedly asked OpenAI to stagger the release of its next big-ticket model, GPT-5.6. The Information reported that OpenAI CEO Sam Altman told employees Wednesday in a company Q&A that it would release GPT-5.6 in limited preview form - granting access only to a small group of […]
<p>Article URL: <a href="https://unconv.ai/blog/introducing-un-0-generating-images-with-coupled-oscillators/">https://unconv.ai/blog/introducing-un-0-generating-images-with-coupled-oscillators/</a></p> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48679007">https://news.ycombinator.com/item?id=48679007</a></p> <p>Points: 176</p> <p># Comments: 42</p>
Agent-testing startup Patronus AI, founded by former Meta AI researchers, is experiencing nearly insatiable demand, its investor says.
<!-- SC_OFF --><div class="md"><p>I've been experimenting with a compiler/runtime project that I'm not entirely sure is a good idea, so I'd love some feedback from people who've worked on deployment systems.</p> <p>The idea is to compile an exported PyTorch model into a self-contained package that contains:</p> <ul> <li>graph</li> <li>binary weights</li> <li>backend kernels (currently WGSL)</li> <li>runtime metadata</li> </ul> <p>A lightweight runtime loads that package and executes it directly
Notion is "going all in on using agents to run your inbox."
It took 20 years, but the Finance app arrives just in time to be packed full of AI.
Alibaba allegedly used 25,000 accounts to mine Claude over 28.8 million exchanges.
In this technical collaboration between AWS and the authors, we present a pragmatic solution: agentic overlays. Agentic overlays are thin wrapper layers that transform traditional REST-based services into agents capable of participating in A2A interactions. They also expose REST APIs as tools compatible with the Model Context Protocol (MCP). Together, they let enterprises add A2A capabilities to existing REST services without rewriting business logic, without duplicating code, and without runnin
<p>Giftlink: <a href="https://www.bloomberg.com/news/articles/2026-06-25/apple-to-skip-high-end-m6-mac-chips-to-launch-m7-pro-m7-max-m7-ultra-instead?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc4MjQwNTU2MCwiZXhwIjoxNzgzMDEwMzYwLCJhcnRpY2xlSWQiOiJUSDM4OFJUOTZPU08wMCIsImJjb25uZWN0SWQiOiJDNEVEQ0FFMUZBMDU0MEJFQTI0QTlGMjExQzFFOTA4MCJ9.3RpcTAgL-JUz9iWRQYzyWaSzoOhLU50chTDHkeU0GTI" rel="nofollow">https://www.bloomberg.com/news/articles/2026
Despite ChatGPT's commanding market lead, consumers who pay for AI have been increasingly choosing Anthropic's Claude, data shows.
<!-- SC_OFF --><div class="md"><p>In the recent Springer/Meteor email, it says:</p> <blockquote> <p>The deadline for the upload of the camera-ready manuscripts and source files is 30 June. This is a hard deadline and will not be extended.</p> </blockquote> <p>However, in the same email, the Meteor submission line for my paper says:</p> <blockquote> <p>submission due: June 27, 2026</p> </blockquote> <p>A previous email from the ECCV Program Chairs also stated that the camera-ready deadline had be
<!-- SC_OFF --><div class="md"><p>What if there was a new programming language where the meaning of each token was so dense (or perhaps so specific) that an LLM could write robust code with fewer tokens and faster inference?</p> <p>Assuming there’s enough training data, do you think something like this allow an LLM to write better code faster?</p> <p>Rationale:</p> <p>1) It would allow for faster inference. Fewer tokens required to do the same thing in Python = finish faster.</p> <p>2) It would
<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1ufgpnh/r_compiling_agentic_workflows_into_llm_weights/"> <img alt="[R] Compiling Agentic Workflows into LLM Weights: Near-Frontier Quality at Two Orders of Magnitude Less Cost" src="https://external-preview.redd.it/q3evP6JeDpAC2MdSQHWYxnCYTqbJkElIQsLFqVSdkss.png?width=640&crop=smart&auto=webp&s=de730fbf7ecace6df0036b21470c16a2d4feacfb" title="[R] Compiling Agentic Workflows into LLM Weights: Near-Frontier Qu
<p>Article URL: <a href="https://www.ycombinator.com/companies/besimple-ai/jobs/yWfhhOR-strategic-projects-lead-audio-data">https://www.ycombinator.com/companies/besimple-ai/jobs/yWfhhOR-strategic-projects-lead-audio-data</a></p> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48676256">https://news.ycombinator.com/item?id=48676256</a></p> <p>Points: 0</p> <p># Comments: 0</p>
General Intuition has raised $320 million to scale AI trained on millions of hours of gameplay, betting action data can help AI develop something closer to human intuition.
Un-0 is an image-generation system tool that shows for the first time how the company's technology can replicate conventional AI systems.
This post shows you how to configure training jobs on Amazon SageMaker AI to get the most out of Blackwell’s architecture on AWS. You learn how to select batch sizes and sequence lengths that take advantage of Blackwell’s expanded memory, choose the right precision format for your model size (1B to 64B parameters), and apply activation checkpointing strategically. By the end, you have a practical framework for tuning your training configuration and launching distributed training jobs on P6-B200
In this post, we demonstrate how to implement video upscaling using SeedVR2 on SageMaker AI. We cover the solution architecture, walk through the deployment steps, and show performance comparisons that highlight the quality improvements and processing efficiency you can achieve. By the end of this post, you’ll have the practical knowledge needed to implement this super resolution solution.
In this post, we show you how to build Chaplin (Customer Health and Planned Lifecycle Intelligence Nexus), an open source solution that uses AI agents exposed through the Model Context Protocol (MCP) to provide self-service health event analytics.
This post shows how to build a governed, serverless data mesh on AWS that provides the secure, scalable data foundation production agentic AI requires.
<!-- SC_OFF --><div class="md"><p>Worried recruiters see "ML/AI engineer" on a resume and assume zero security depth, even with real hands on work in the space. Anyone hired into security from a non-traditional background like this — how'd you frame it?</p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/Xorphian"> /u/Xorphian </a> <br /> <span><a href="https://www.reddit.com/r/MachineLearning/comments/1uff20h/does_ml_background_help_or_hurt_when_appl
<p>Hi HN, Nick here. We’re launching OpenKnowledge (<a href="https://openknowledge.ai/" rel="nofollow">https://openknowledge.ai/</a>), a “what you see is what you get” markdown editor that has direct integrations with Claude, Codex, and other agents. Available as MacOS app or Web UI+CLI. Fully free/local and OSS.<p>We built this because we wanted a Notion-like experience for writing and sharing markdown files across our team. Obsidian is the best alternative we tried, but found it doesn’t have a
The Google Finance logo, surrounded by elements of the user interface
<!-- SC_OFF --><div class="md"><p>Hello,</p> <p>I'm currently working on my dissertation and feel like I could really use some advice from someone who looks at the problem with fresh eyes. I appreciate all input.</p> <p>The Problem:<br /> Multi Agent Path Finding is the problem of finding paths for several agents to their destinations. Lifelong MAPF is the same, but upon task completion an agent is assigned a new task. For my dissertation (and usually in research) agents move on a grid-like grap
<p>Preprint: <a href="https://scrollprize.org/pdf/main.pdf" rel="nofollow">https://scrollprize.org/pdf/main.pdf</a><p><a href="https://github.com/ScrollPrize/villa" rel="nofollow">https://github.com/ScrollPrize/villa</a></p> <hr /> <p>Comments URL: <a href="https://news.ycombinator.com/item?id=48675179">https://news.ycombinator.com/item?id=48675179</a></p> <p>Points: 1494</p> <p># Comments: 320</p>
Netris provides software that runs on network switches, and offers a platform that helps neocloud operators reduce the time it takes to go live.
Artificial intelligence is rapidly reshaping retail, but not in the ways consumers might immediately notice. The biggest transformation may not be flashy virtual try-ons or chatbot shopping assistants, but in how decisions are made behind the scenes: how products surface in search results, how inventory moves through supply chains, how engineers ship code faster, and…
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Adobe said that it will integrate Topaz Labs' tools across its apps.
Summer savings are heating up. From the Steam Summer Sale to GeForce NOW membership discounts, this week’s GFN Thursday delivers double the deals and more ways to get the most value from cloud gaming. Plus, Dark Scrolls joins the growing Devolver lineup, alongside Square Enix’s The Adventures of Elliot: The Millennium Tales. They lead the […]
<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1uf8thw/calhippo_mapping_neurons_and_glial_cells_in_the/"> <img alt="CALHippo - Mapping neurons and glial cells in the human brain hippocampus in 3D using SOTA segmentation and density estimation models [R]" src="https://preview.redd.it/m8eyacfmbf9h1.gif?width=640&crop=smart&s=1a9d654de34977e02d4c3b3a30f0f9e2d36a5c35" title="CALHippo - Mapping neurons and glial cells in the human brain hippocampus in 3D using SOT
Amazon’s latest India investment comes as global tech companies race to expand AI infrastructure in the country.
To celebrate its new status as No. 1 in JD Power's initial quality ranking among mainstream automakers, Ford is opening up about the challenges it has faced in recent years, especially around its reliance on automated systems in production and design. It turns out that those automated systems were not as robust as previously assumed, […]
IBM’s nanostack transistors could boost chip performance or energy efficiency.
Meta is bringing back the Facebook Creator Studio page manager, now "reimagined" as a standalone AI companion app. The new app aims to make it easier for creators to connect with their audiences and show them "exactly how to grow on Facebook," according to Meta's announcement. Meta's AI Creator Assistant is a central focus of […]
A new OpenAI research paper shows how AI agents are transforming work, enabling longer, more complex tasks and expanding productivity across roles.
As ASML CEO Christophe Fouquet told TechCrunch in May, what China can currently buy are older-generation deep ultraviolet tools — gear first shipped about a decade ago — the same machines the MATCH Act would now put off-limits.
Backed by Mayfield and Aramco Ventures, Vishal Sikka’s new venture brings together veterans from SAP, Infosys, and VianAI.
In its first earnings report since going public, the AI chipmaker forecast a narrower gross margin in its core business, scaring investors.
The silicon race is heating up amid the struggle to keep up with demand.
While AI dominates the layoff narrative, engineers are actually making up a larger share of new hires, according to SignalFire data.
Top AI researchers Jonas Adler and Alexander Pritzel are leaving Google for Anthropic, following departures from top scientists Noam Shazeer and John Jumper.
Revenue quadrupled to $41.45 billion compared with the same period a year ago. The company's profit, meanwhile, rose from $1.88 billion to an incredible $28.2 billion year-over-year.
The tokenmaxxing era was brief. We now appear to be entering the era of token rationing.
Rep. Anna Paulina Luna (R-FL) says her staff used AI for "spellcheck" in an amendment summary for a major defense bill, but denies it was used for the bill text itself and says "NO Legislation is ever drafted with AI." Luna issued the response after accounts on X began sharing screenshots of an amendment summary […]
<p>Alibaba's Qwen team released Qwen-AgentWorld on Tuesday — two models trained not to act inside agent environments, but to predict what those environments return. The release covers seven domains under a single architecture: MCP, Search, Terminal, Software Engineering, Android, Web, and OS. </p><p>The release extends Alibaba's recent push into autonomous agents.<a href="https://venturebeat.com/technology/alibabas-proprietary-qwen3-7-max-can-run-for-35-hours-autonomously-and-supports-
<!-- SC_OFF --><div class="md"><p>Hi everyone,</p> <p>For the past couple of weeks I have been working on a simulator project considering the shortcomings of MuJoCo. There are things that people like and also don't like about MuJoCo, like the CPU dependency on MuJoCo which makes the simulation not parallelizable beyond a certain limit (depending on the hardware). I know there exists MJX which is GPU accelerated, however, it is not really made for vision based RL pipelines and training. There is
In this post, we walk through how Huntington built a scalable AWS solution to detect and redact Personally Identifiable Information (PII) and Payment Card Industry (PCI) data from over 400 million documents, reducing processing time from years to just a few months while achieving 95%+ redaction accuracy.
In this post, you will learn how to build a voice agent that handles appointment reminder conversations using Amazon Nova 2 Sonic and Amazon Bedrock AgentCore. The agent authenticates patients by voice, manages appointments (confirm, cancel, or reschedule), collects pre-visit health information, and escalates to human staff when needed. You handle routine calls at scale, which can help reduce no-show rates. This sample focuses on the agentic side of the problem: voice conversation and tool orche
In this post, you will learn how to build an end-to-end integration between Snowflake semantic views and Amazon Quick. The sample data is user review data for a media company. You start by loading movie review data from Amazon Simple Storage Service (Amazon S3) into Snowflake, define a semantic view in SQL to add business meaning, explore it with natural-language queries through Cortex Analyst, and then generate an Amazon Quick dataset and dashboard. The dataset can be created manually or with a
<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1uelcm9/high_dimensional_dynamic_rotary_positional/"> <img alt="High Dimensional, Dynamic Rotary Positional Embedding [P]" src="https://external-preview.redd.it/Go7zlxhewkLxNN5-ZvZe623w5Zrdi3SXYEIr0JeEGQk.png?width=140&height=75&auto=webp&s=2d3a7ad647024e077a4b7f7b5746c806eba71b8a" title="High Dimensional, Dynamic Rotary Positional Embedding [P]" /> </a> </td><td> <!-- SC_OFF --><div class="md"><p>At the end
The expensive, $27 million political proxy war between Anthropic and OpenAI came to a draw last night when Alex Bores, a New York state Assemblyman whose popularity surged after being targeted by a pro-AI super PAC, narrowly lost the Democratic primary to represent New York's 12th Congressional district. Prior to the race, Bores, a former […]
The new app, which is currently being tested with select creators, will have Facebook's recently launched AI creator assistant built into it.
In this post, we demonstrate the architecture and approach Loka used to solve a common frustration: robotic, slow voice assistants that cause customers to hang up, damaging brand reputation and driving up support costs.
Agility Robotics, the humanoid robotics startup that spun out of Oregon State University in 2015, expects to generate $620 million in proceeds.
<!-- SC_OFF --><div class="md"><p>Hi, I've created an overview of the most important OCR benchmarks, along with the top open models, and links to their paper and code: <a href="https://paperswithcode.co/tasks/ocr">https://paperswithcode.co/tasks/ocr</a>.</p> <p>This week, new OCR models were released by Baidu and Mistral. </p> <p>Baidu released <a href="https://paperswithcode.co/paper/2606.23050">Unlimited OCR</a>, a 3B-parameter model that introduces a key innovation called Reference Sliding Wi
<!-- SC_OFF --><div class="md"><p>Hi everyone,</p> <p>I trained a self-play RL agent for <a href="http://Generals.io">Generals.io</a> that reached superhuman-level and ranked #1 on the human 1v1 leaderboard.</p> <p>It began as my master's thesis where the goal was to beat a prior algorithm based agent. We succeeded using behavior cloning, RL fine-tuning and reward shaping, but the agent was still consistently beaten by the top players.</p> <p>So I gave it a round two and fixed the largest bottle
Figma's update adds a new code layer, support for motion and shaders, and the ability to create custom plug-ins for various tasks using AI.
Figma has revealed some new design and coding product updates at its annual Config conference that aim to help creatives "push their ideas further" and automate tedious tasks with AI. Part of this is a reimagined canvas that's now optimized for full-stack development, according to Figma, bringing teams, AI agents, tools, and materials "together in […]