arXiv:2610.00018v1 Announce Type: new Abstract: Role-specialized QA pipelines increasingly pass rationales from a reasoner to a verifier, but it is unclear what this message actually buys: better answers, stronger support assessment, or a new failure surface. We introduce a message-intervention diagnostic that fixes the evidence and candidate answer while varying only the rationale passed across the reasoner-to-verifier boundary. On 400 MuSiQue, HotpotQA, and 2WikiMultiHopQA examples with DeepSeek as generator and verifier, faithful rationales add almost no answer accuracy over no rationale, while corrupted rationales strongly alter support judgments. Under a blind verifier prompt, harmless paraphrases shift support by only 0--2.5%, whereas corrupted rationales shift support by 10--22%; a…

arXiv:2610.00015v1 Announce Type: new Abstract: Large-language-model agents can propose and execute actions, but proposal, authority, dispatch, verified external effect, and serving promotion are different claims. We present Praxa, an agent harness that represents these states explicitly through deterministic admission, brokered execution, external read-back, reconciliation, and reviewed promotion. We report four evidence lanes. First, an author-run repository-local audit at a pinned revision passed 1,027/1,027 unit tests and 89/89 Workerd tests, instrumented all 363 expected source files, and met four coverage floors; raw per-test transcripts and independent reproduction are unavailable. Second, in a provider-backed Terminal-Bench Core 0.1.1 pilot across 12 curated tasks, baseline and re…

arXiv:2610.00012v1 Announce Type: new Abstract: LLM agents increasingly act through modular systems, such as order, payment, inventory, and shipment services, where actions in one module change which transitions are valid in another. Standard world models usually fit observational traces, but this is not the quantity needed for intervention-time planning: a trace may show that payment precedes shipment without identifying whether payment authorizes shipment, inventory mediates the effect, or a hidden trigger explains both. We study this gap through FedCausalCompose, a causal world-model framework for modular LLM agents in which local actions provide intervention-response evidence for cross-module interfaces. We first show that observational world models incur an irreducible interventional…

arXiv:2610.00010v1 Announce Type: new Abstract: Long-horizon language agents increasingly rely on external memory as a frozen world model, yet current memory systems are usually judged only by task success or token cost. We argue that the missing object is the shape of memory use: under finite context and repeated retrieval, agent memory can concentrate on a small core while leaving rare states in a long tail where prediction errors accumulate. We study this effect through a conservative tail audit and find that concentration is reproducible but policy-dependent. Random-walk agents produce log-normal-compatible retrieval artifacts, whereas semantic LLM policies yield the strongest truncated-power-law-compatible core--tail traces. Motivated by this audit, we propose Core--Tail World Model…

Martin Trust Center Managing Director Bill Aulet introduces Dear Dreamer, a free platform for middle and high school students who want to learn about entrepreneurship.

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The AI chipmaker’s new safety platform adds controls around AI agents, while enterprises remain responsible for defining their authority and setting boundaries.

If a chatbot prompt like ‘find Australian medicine statistics’ results in a website breach, the responsibility does not lie with a piece of code The recent panic about a breach of Medicare computer security by an “AI agent” contrasts sharply with other recent cases such as the Telstra and Optus outages that left many Australians unable to reach Triple Zero. In those cases, no one blamed the computers involved. The mistakes were clearly sheeted home to the corporations that operated them. This wasn’t always the case. When the term “artificial intelligence” was coined some 70 years ago, the first mainframe computers (absurdly primitive by modern standards) were viewed with the same awe and concern as the AI agents of the present day. There were even “algorithms” (though the term wasn’t used…

Cloudflare has released Clef (27B) and Clef-flash (9B), open-weight decision models that return typed probabilities instead of text. They are Jev-API compatible, accept images, and run on Workers AI at 209.3 ms and 38.8 ms median latency. The post Cloudflare Releases Clef and Clef-flash: Open-Weight Decision Models That Return Typed Probabilities Instead of Text appeared first on MarkTechPost.

As a top cloud provider, Google has deep experience integrating its infrastructure with the other Google products that enterprises use.

In this comprehensive coding guide, we explore Google Research's Kauldron—a JAX training library optimized for research velocity and modularity. Learn how konfig turns experiments into plain dictionaries, kontext wires components via string paths, and ktyping enforces runtime shape checks. The post A Coding Guide to Google Research’s Kauldron: Configs That Are Plain Data, Components Wired by String, and a JAX Trainer You Can Read End to End appeared first on MarkTechPost.

We catch up with RLM first author Alex Zhang, MIT PhD, on Jev, PhD masxing, and the future of harnesses.

Discrete diffusion, including remasking and uniform-state samplers, generate a sequence by writing multiple token positions per step, drawing each from a per-position distribution and choosing which positions to write from those same distributions. For domains of general interest (pixels, phonemes, or words) there are inherent dependencies between tokens. We show that a step matches the training distribution only when the positions it writes are conditionally independent given the tokens already fixed, that no product of per-position distributions can match a dependent group, and that…

Chatham Financial uses Codex and GPT-5.6 to build technology and redesign workflows, cutting trade validation from 30 minutes to under 4.

Multilingual self-supervised speech models can benefit from sharing information across languages, but under a matched total pretraining data budget they still fall short of monolingual models. We show that strengthening the model’s ability to discriminate languages during pretraining reduces and, on some measures, closes this multilingual gap on continuous phonetic and higher-level linguistic measures, while preserving substantial cross-language sharing. Using a controlled English/French HuBERT setting, we test two interventions which strengthen language discrimination: an auxiliary language…

The move comes as agentic AI plays an increasingly big part in business operations, sparking oversight concerns.

GPT-6 Astra Ultrafast, running on NVIDIA Blackwell GPUs, is available now in the OpenAI API and to eligible ChatGPT Work and Codex users. Accelerated by inference optimizations through OpenAI’s models that tap into the capabilities of the NVIDIA Blackwell architecture, Ultrafast offers up to 8x faster token generation than the Astra Standard mode. For developers, […]

A finance team’s job is not simply to report the numbers: it’s to interpret what...

OpenAI’s new Dots can work around the clock without drawing down a user’s normal usage allowance during the launch period, The post OpenAI’s always-on agents are free, until one specific thing happens appeared first on The New Stack.

“InstructMesh” can generate designs for everyday objects that are easy to edit and fabricate for both experts and newcomers to 3D modeling.

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In our previous posts, we showed how open table formats, open APIs and unified governance...

Observability has long been a staple of enterprise operations, giving companies a way to understand what their applications and infrastructure The post “No human wants to look at billions of traces”: Dynatrace bought Arize because agents need a new kind of observability appeared first on The New Stack.

With Live Data in Apps in Amazon Quick, AI-built apps query your governed Quick Sight datasets in real time instead of static, build-time snapshots. Each query runs as the person viewing the app, so row-level and column-level security apply per reader. Learn how to build, publish, and share a live-data app using natural language.

Guided Vision is launching in Gemini Live on compatible Android devices today to use AI to give real-time audio descriptions of anything you point your phone's camera at. By sharing your camera in Gemini Live, you can have Google's AI help with things like reading small text, describing your surroundings, finding or identifying objects around you, and describing details on specific objects. Like the VoiceOver Live Recognition feature Apple has added to the iPhone and Vision Pro, it's designed for people who are blind, have low vision, or want assistance in specific situations. In addition to the Gemini app, Guided Vision is also available … Read the full story at The Verge.

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State attorney general issues subpoena to OpenAI as ​part of broader inquiry into potential security vulnerabilities California’s attorney general has issued an investigative subpoena to OpenAI, starting an investigation into the startup ⁠as ​part of a broader inquiry into potential cybersecurity vulnerabilities and incidents related ⁠to its AI models, his office said on Thursday. Last month, Rob Bonta announced that ⁠the Department of Justice was conducting a formal ​investigation into the “Hugging ‌Face incident”, amid increasing ‌scrutiny of the AI industry. AI agents developed by OpenAI hacked Hugging Face in July, gaining access to parts of the open-source platform’s infrastructure. Continue reading...

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In managed OLTP, restores have always been painfully slow and they get slower at...

Learn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT's memory subsystem works and how to implement Amazon S3 Vectors as a custom memory provider, using a multi-agent investment research use case.