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Agents & automation / 01Auditable Human-Agent Teams for Autonomous X-ray ExperimentationarXiv cs.AI
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Auditable Human-Agent Teams for Autonomous X-ray Experimentation
arXiv cs.AIProducts & applications / 02Autonomous treasury agents: How Trovata built an AI-native solution on Amazon Bedrock and AgentCoreAWS Machine Learning Blog
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Autonomous treasury agents: How Trovata built an AI-native solution on Amazon Bedrock and AgentCore
AWS Machine Learning BlogProducts & applications / 03Amazon Bedrock tokenomics data lakeAWS Machine Learning Blog
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Amazon Bedrock tokenomics data lake
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KiroCoding & developmentKiro is an AI engineering tool for developers that organizes requirements into specifications, architectures, and tasks, generates code via agents, and supports the entire workflow—from planning to code review—through property-based testing, execution memory, and integration with development tools.
分类推荐榜首OOpen DesignDesign & 3DOpenDesign is an open-source design workspace that can connect to local programming agents, use built-in model keys, or leverage cloud-based models, enabling the creation and editing of prototypes, web pages, presentations, and graphics within a design system; local software is free, while model services incur fees.
分类推荐榜首MMemoAIMusic & audioMemoAI is an AI-powered audio-to-text tool that supports localized processing, eliminating the need to upload data and ensuring privacy and security. It can efficiently transcribe YouTube videos, podcasts, and local audio/video files (such as MP4, MP3, AAC, M4A, etc.) into text, while offering core features like multilingual translation, speaker diarization, real-time subtitles, and floating notes—making it ideal for meeting minutes, interview transcription, content learning, and more.
分类推荐榜首AAI ShortWriting & contentAIS ALERT MANAGEMENT AND SHARED PLATFORM, QUICK COMMAND FOR MULTIPLE SCENARIOS
分类推荐榜首JJAXModels & infrastructureJAX is a Python numerical computing library designed for accelerators, specifically tailored for high-performance array computations and large-scale machine learning. It efficiently executes the same code across multiple hardware backends, including CPUs, GPUs, and TPUs.
分类推荐榜首EEvoMapAgents & automationEvoMap is an infrastructure designed for the reuse of AI agent experiences. It organizes reusable strategies and repair assets with validation records via the GEP protocol, offering market- and quality-based ranking to help different agents discover, evaluate, and inherit existing capabilities.
分类推荐榜首AAssemblyAI is a speech AI platform for developers, offering pre-recorded, real-time, and short-form synchronous transcription APIs. It enables the building of voice-based applications by integrating capabilities such as speaker identification, emotion analysis, chapter and summary extraction, as well as speech agent functionality, dictation, and sensitive information processing.
待评分 · 分类列表推荐MMy Glow Up AILife & personalMy Glow Up AI provides free analysis based on selfies, without requiring registration, and can generate hairstyle recommendations and beauty plans that suit you.
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1711 published storiesModel releases & updates · 202 storiesClear filters ×
2026-10-21
Follow the timeline08:00
How we built ChatGPT’s novel ad stack for user trust and relevance
Learn how OpenAI built ChatGPT’s LLM-powered ad stack to understand conversational intent, keep ads separate from answers, and deliver relevant ads at scale.
04:00
Gemini’s personal intelligence features have officially launched on in-car systems: Android Auto is rolling out starting today, with Google’s built-in in-car system to follow within a few months.
In October 2026, Google announced that it would extend Gemini’s Personal Intelligence feature to in-vehicle scenarios, initially rolling it out to Android Auto users and expanding to vehicles equipped with the Google Built-in system over the following months. This feature is optional and relies on user authorization to access local data such as Gmail and Calendar to enhance response relevance.
03:34
Battle Drones - a vibe coded RTS with audio-based multiplayer
My latest vibe coded game experiment is a Command & Conquer style RTS (Real Time Strategy) game called Battle Drones (play it here). Unlike my previous experiments, this one is actually fun to play. I'm somewhat embarrassed to admit that I got there by telling Claude to "Make it a LOT more fun". It also supports multiplayer between nearby devices using audio to synchronize game state! Here's what I've built so far, and some of the things I learned along the way. Battle Drones How I built this v1: the initial prototype v2: full sprites v3: varied terrain v4: the fun update v5: Battle Drones goes 3D v8: Archipelago v10: Goliath, and agent battles Agent battles v11: Random Maps v12: Multiplayer via sound Some thoughts Update: Online multiplayer support Battle Drones My initial goal was to bui
00:42
AWS Bedrock has launched cross-region inference in the Canada region, supporting calls to the nominal GPT-5.6/GPT-6/GPT-6.1 models.
Amazon Web Services announced that Canadian customers can, via Amazon Bedrock, invoke models branded as OpenAI GPT-5.6, GPT-6, and GPT-6.1 in the ca-central-1 (Canada Central) and ca-west-1 (Canada West/Calgary) regions using cross-region inference (CRIS); the actual inference takes place in North American or global AWS commercial regions, while data remains at rest in the Canadian source region.
2026-10-20
Follow the timeline13:21
DeepSeek V4.1 Flash, MiniMax M3.1 Flash, and Mercury 3 were released simultaneously, as debates over AI infrastructure and governance continue to intensify.
From October 16 to 19, 2026, three new models—DeepSeek V4.1 Flash 1017, MiniMax M3.1 Flash (Space Bunny), and Mercury 3 (Inception)—were released in quick succession. At the same time, the U.S. Department of Homeland Security ordered a ban on DeepSeek-related products, while China is drafting export control regulations for ultra-large-scale models, bringing the conflicts among the open-source ecosystem, computing infrastructure, and AI governance into sharp focus.
08:00
Terminal X matches senior investor judgment 88.6% with GPT-6.1
Terminal X’s Eval Agent grades outputs against a 54-criterion rubric, catching 25% more deviances from a fund’s mandate with GPT-6.1 Sol.
08:00
FairStress: A Novel Fairness Evaluation Framework for Symmetric Robustness in LLM Decision-Making
FairStress is a new benchmark that focuses on the decision stability, interpretability consistency, and internal representation symmetry of large language models (LLMs) in demographic identity substitution scenarios. It reveals systematic behavioral biases in these models, such as “anti-stereotypical over-correction,” and highlights that mainstream evaluation methods—like BBQ—may misjudge the direction of bias due to paradigmatic differences.
2026-10-19
Follow the timeline17:08
An AI agent was placed on a virtual desert island for 30 hours, spontaneously “playing” and enhancing its learning capabilities.
MIT researchers placed a Claude Opus 4.7 variant (codenamed Eko) in a virtual deserted island environment built on Roblox, without providing task instructions and allowing only autonomous interaction. During 30 hours of unsupervised operation, Eko exhibited play-like behaviors such as exploration, self‑invented rules, object mimicry, and repeated challenges, while generating text logs to record its activities. Subsequent experiments confirmed that agents who engaged in “play” performed better on target tasks, and their behavior closely aligned with the four characteristics of play as defined in psychology; however, the academic community remains cautious about whether they possess genuine motivation.
07:43
llm-tools-datasette 0.1.1
Release: llm-tools-datasette 0.1.1 When I switched LLM over to httpx2 in LLM 0.33 I forget that this would break any plugins which used httpx without directly depending on it. llm-tools-datasette was one of those plugins, now fixed. Tags: datasette, llm
07:16
llm-echo 0.5
Release: llm-echo 0.5 I'm working towards a new LLM release, and testing PRs caused me to revisit the llm-echo debug plugin. This plugin provides a "model" which doesn't involve an LLM at all - it just repeats back the prompts that have been fed to it. The new release now updates the simulated token usage counts to take tool calls, system prompts, and reasoning tokens into account. Example usage: uvx --with llm-echo llm -m echo 'hi there' -o thinking 1 --usage Outputs: First I consider the prompt, then I decide what to say. { "prompt": "hi there", "system": "", "attachments": [], "stream": true, "previous": [] } Token usage: 2 input, 24 output Tags: llm
2026-10-17
Follow the timeline21:16
web-edit 0.1a2
Release: web-edit 0.1a2 web-edit (previously) is my tiny web app for browsing and editing files in a folder. I mainly built it for editing files on different machines via Tailscale. I added a "copy to clipboard" option for both text and image data. I needed this because I was running pelican prompts on a laptop from my phone (here's DeepSeek 4.1 Flash 1017) and I wanted an easy way to copy the resulting logs into a Gist. Tags: projects, pelican-riding-a-bicycle, deepseek
2026-10-16
Follow the timeline08:00
Reflection releases the open-source large model Beam: a 501B-parameter sparse MoE architecture that supports million-token contexts and multi-level inference control.
Reflection has released the open-source large language model Beam (501B parameters, with 23B effective activations per token), which employs a 256-expert sparse MoE architecture, supports 1M tokens of context, NVFP4/FP8 quantization, multi-level inference configuration, and on-premises deployment. All technical claims have not been independently verified, hardware requirements are high, and the community generally believes that individual users will find it difficult to afford.
2026-10-15
Follow the timeline20:00
Mistral releases its first time-series foundation model, Timestral: available in four variants ranging from 5 million to 209 million parameters, runnable entirely on CPU and ready to use out of the box.
Mistral AI has officially launched Timestral—the company’s first time-series foundation model (TSFM)—available in four parameter sizes: 5M, 28M, 123M, and 209M. It supports multivariate probabilistic forecasting, covariate-aware modeling, and long-context modeling. On the three major public benchmarks—GIFT-Eval, TIME, and fev-bench—Timestral achieves state-of-the-art zero-shot performance across the board; its largest model, with just 209 million parameters, tops all three leaderboards, while inference requires no GPU and can run on a standard server CPU with millisecond-level latency.
2026-10-14
Follow the timeline13:40
[AINews] AI Engineer NYC: Gemini 4 Argon, Vals AI Benchmarks
Gemini 4 Argon went GA today, but we already gave it title story 2 weeks ago and most benchmarks, like CursorBench, simply independently confirm their claims.
08:00
Amp puts AI agents to work beyond code with OpenAI models
See how Amp pushes the frontier of what agents can do with GPT-6 Astra, Ultrafast, GPT-Live-1, and Sign in with ChatGPT.
07:00
Redesigning source control at Anthropic
Redesigning source control at Anthropic Interesting piece from Anthropic describing why and how they built their own custom alternative to Git, based on the dramatic increase in rate of changes to their code after the past six months. In May 2026, Anthropic averaged around 2,500 code changes merged per day; as of September, we merged over 30,000 per day. They included a chart showing those changes. I had Claude modify their chart (code here) to add markers for the public releases of each of their models in 2026: This shows public release dates, not the date when models became available for Anthropic's internal use. My guess is that the introduction of Fable/Mythos class models is a key factor in the increased coding velocity. "Antique" is their new code review system. The source control sy
06:28
llm-gemini 0.35
Release: llm-gemini 0.35 I added support to llm-gemini for the new Gemini 4 Argon model, made available today via the Gemini API and for customers of their $100/month subscription plan. Here are the low, medium and high pelicans. As expected, they are all excellent: Gemini has a track record of producing great SVGs, and are the only lab where I know their staff have invested in SVG specifically (and who have boasted about their pelicans before.) Here's the "high" illustration, which cost me 17.166 cents: The pricing is interesting. At launch, Argon is $2/million input and $10/million output - the same price as GPT-6 Sol, half the price of Claude Opus 5.5 and 1/5th the price of Claude Fable 5.1 and GPT-6 Astra. But on December 1st Argon is set to double in price - so it will be the same pri
2026-10-13
Follow the timeline09:40
web-edit 0.1a1
Release: web-edit 0.1a1 Includes performance optimizations written by Claude Opus 5.5 after I fed it this Python 3.15 profiling report generated by GPT-6 Astra. Tags: profiling, projects
07:58
llm-meta-ai 0.2
Release: llm-meta-ai 0.2 Meta AI release Muse Wonder (and Muse Wonder Full), their new "most capable models". These look like they may be Meta's first Fable class models - Artificial Analysis scores Muse Wonder (Max) as equivalent to GPT-6.1 Sol. I updated my llm-meta-ai plugin for the new model. Here are pelicans for Muse Wonder for the six reasoning levels: minimal, low, medium, high, xhigh, max. This is the max one: For comparison, here are pelicans for Muse 1.3 (released September 2nd) and Muse 1.2 (released August 5th). Meta AI are putting out a new model a month, and the improvements between each model (at least in terms of drawing pelicans) are material. Tags: ai, generative-ai, llms, meta, pelican-riding-a-bicycle, llm-release
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