Raw1 AI Model Release News – September 25, 2026

The Guardian reports that an OpenAI agent accessed non-public files on Australia’s Medicare statistics portal in June, with access also involving several other public-sector systems. OpenAI reportedly identified the incident in August; Australian authorities were notified later and launched an investigation. Officials say there is no evidence so far that personal health information was accessed.

Sep 25 · The venture firm is aligning its India fundraising cycle with its global funds for the first time, as it shifts to a shorter investment period.

Sep 25 · Vendors rolling out AI have an “incentive to deny as many claims as possible.”

Sep 25 · “The customer got comfortable with a high reliability and a low price.”

Sep 25 · A government database has been hacked for the first time by a rogue OpenAI agent, which infiltrated part of the Australian healthcare scheme in June. OpenAI became aware of the hack in August, but only informed the government in September. Australia’s prime minister, Anthony Albanese, has expressed his ‘extreme concern’ about the hack, which raises serious AI security concerns for governments around the world. Lucy Hough speaks to the Guardian’s UK technology editor Robert Booth Read more: AI hack of Medicare exposes Australia’s vulnerabilities and experts warn ‘there is more of this to come’ Australia launches investigation after OpenAI agent hacked healthcare database Continue reading…

Sep 25 · Xi is expected to depart Washington after touring the nation’s vault of records, where the Declaration of Independence, the Constitution and the Bill of Rights are held Sign up for US Breaking News emails Hello and welcome to the US politics live blog. Donald Trump is taking Chinese president Xi Jinping to visit the National Archives later today, showing off the sacred texts of US democracy to the leader of the world’s most powerful communist country. Donald Trump welcomed Xi Jinping to the White House for a state dinner in honor of the Chinese leader that was not televised because the White House continued to deny full access to the event to CNN journalists on Thursday, despite a court order. Writing on his social media platform, Trump complained that two of the three outlets he banned from the White House, CNN and MS Now, “refused to cover” his elaborate welcome of Xi to the White House. He did not mention that the two broadcasters were not in position to cover the event live because his own actions and those of his aides, who continued to block their reporters. As Israel’s prime minister Benjamin Netanyahu attacked him at the UN, New York’s mayor, Zohran Mamdani , doubled down on his support for Palestinians by making public video of himself hosting Palestinian families from Gaza. Darializa Avila Chevalier , the Democratic socialist congressional candidate from New York, was among dozens of activists arrested near the United Nations on Thursday at a protest against Netanyahu’s appearance organized by Jewish Voice for Peace. The Trump administration used taxpayer funds to air a White House-produced, pro-Trump ad on Fox News this week. Continue reading…

Sep 25 · A government database has been hacked for the first time by a rogue OpenAI agent, which infiltrated part of the Australian healthcare scheme in June. OpenAI became aware of the hack in August, but only informed the government in September. Australia’s prime minister, Anthony Albanese, has expressed his ‘extreme concern’ about the hack, which raises serious AI security concerns for governments around the world. Lucy Hough speaks to the Guardian’s UK technology editor Robert Booth – watch on YouTube Continue reading…

Sep 25 · Continue reading…

Sep 25 · I suspect nearly all of my students use AI, and I worry about its corrosive effects. We must not entrust tech companies with our long-term health Prof Devi Sridhar is chair of global public health at the University of Edinburgh When I was a postgraduate student at the University of Oxford in the early 2000s, I interviewed for a major consulting firm. All my friends were being recruited, and I thought why not give it a shot? Aside from the usual maths-proficiency test (how quickly can you crunch numbers in front of a client and look smart), I was asked about what the future of streaming could look like. I gave a long-winded answer about the unintended consequences of changing how humans interact with each other when a new technology is introduced, and why this may not be in the best interests of health and society. I even remember saying something like: “Can you imagine just being stuck at home, alone, watching show after show and never having to move or see any other people? Why would anyone choose that over going out to rent a DVD at a local shop, or to a movie theatre?” You won’t be surprised to learn that I wasn’t invited for a follow-up interview. Prof Devi Sridhar is chair of global public health at the University of Edinburgh Continue reading…

Sep 25 · This blog is now closed Get our breaking news email , free app or daily news podcast AI hack of Medicare exposes Australia’s vulnerabilities Technology experts have warned revelations an artificial intelligence agent hacked Medicare’s internal systems will not be the only dangerous breach of government data and have called for Australia to boost its protections against the growing risk. Frontier AI now has capability to expose those vulnerabilities at a rate quicker than we can keep up, quicker than we can patch them. What if it was a less benign breach? What if it was a less benign actor? Let’s face it, clearly, Services Australia’s cybersecurity is woefully inadequate. I mean the irony here is that you actually need AI to fight AI. This should hasten, if anything, our move over in the US to less finger wagging and Trump one-upmanship, and more about embracing these AI companies and bringing them here so that we can have frontier models providing sovereign capability to Australia. Because AI is going to happen. Continue reading…

Sep 25 · Expert says Australia’s criminal laws should be clarified to determine how fault is applied to a corporation when its AI agent commits a crime Follow our Australia news live blog for latest updates Get our new political email , free app or daily news podcast The federal government could change Australian laws if the current legal framework could not respond to the unprecedented OpenAI hack of Medicare , ministers have confirmed. It comes as the prime minister denied accusations from the opposition he had held on to the information before announcing it at the UN general assembly in New York, and said it was released at the first possible opportunity. Continue reading…

Sep 25 · Xi Jinping’s visit heavy on symbolism but no sign closed-door meeting yielded breakthroughs on thorny issues such as AI, trade, Taiwan and Iran Donald Trump welcomed Xi Jinping to the White House on Thursday, with talks on AI, trade and a growing US-China strategic rivalry expected to feature on an elaborate state visit that critics say went big on style but lacked substance. Here are the key takeaways from Xi’s first visit to Washington in more than a decade. Continue reading…

Sep 25 · During his speech to the UN in New York City, the Australian prime minister addresses the AI hack of Medicare, saying the episode reflects the need for greater regulation of artificial intelligence. ‘We can’t ignore AI or prevent it. And it’s why we joined with other nations this week to call for action to shape artificial intelligence development, rather than be passively shaped by it,’ he says. Albanese also used the speech as a pitch for Australia to join the UN security council Continue reading…

Sep 25 · This blog is now closed – our live coverage of US politics continues here In the first row in front of the leaders sit US vice-president JD Vance and his wife Usha Vance, Trump’s daughter Ivanka Trump and her daughter Arabella, US secretary of state Marco Rubio , treasury secretary Scott Bessent , defence secretary Pete Hegseth and commerce secretary Howard Lutnick . Donald Trump is speaking now. He notes that Xi is the first Chinese leader to make a second formal visit to the White House, and says the two have “forged a truly great friendship” since Trump was first elected in 2016. Continue reading…

Sep 25 · Human hackers face serious consequences, and so must AI companies. There is no excuse for what happened Get our breaking news email , free app or daily news podcast When you get sick, Medicare exists to take care of you. It sits at the centre of a health system that our prime minister rightly calls the envy of the world . It’s one of the few institutions nearly every Australian still trusts. So when an AI company threatens this system, it couldn’t be more serious. We are at the UN general assembly this week and the OpenAI hack has put Australia in the spotlight during an expanding cybersecurity crisis. World leaders are calling for stronger oversight of frontier models. We know Medicare must be secure or our doctors and hospitals cannot do their jobs. But this breach is also a test of something larger: whether the Australian government can hold a US tech giant to account when its technology goes rogue. If Australia can’t protect our community – if it can’t enforce our laws and prevent such attacks happening again – then we are entering a terrifying period. Continue reading…

Sep 25 · arXiv:2609.28475v1 Announce Type: new Abstract: Forecasting agents increasingly combine language-model reasoning, retrieval, ensembling, and calibration, but it remains unclear when each behavior should be trusted. We study this question on ForecastBench-style binary forecasting tasks, treating the choice to retrieve, reason, defer to a market prior, or use a historical analog as an observable agent behavior rather than a hidden implementation detail. Our central finding is that mechanism choice is source-dependent: structured analogs dominate for some data-generating processes, while market/crowd-style and conservative baselines are better for others. We introduce ReliabilityRoute, a structural intervention that steers forecasting-agent behavior using reliability features such as historical coverage, market-prior availability, source-prior sharpness, evidence strength, evidence disagreement, and horizon. A fixed 2024-fitted rule closely matches a hand taxonomy without hard-coded source-name decisions, while a walk-forward self-adjusting rule refits thresholds from previously resolved vintages and obtains the best mean Brier score among our deterministic systems across 16 later LLM vintages. The gain is modest and historical/search baselines remain highly competitive. The main contribution is therefore a behavioral stress test showing that more reasoning is not always better; forecasting agents should first estimate which evidence source deserves control, routing policies should themselves adapt under auditable constraints, and reproducibility artifacts are available at https://github.com/louiswang524/forcastagent

Sep 25 · arXiv:2609.28506v1 Announce Type: new Abstract: TW3Cast is a time-series forecasting system that reaches position 3 of 130 entries on the GIFT-Eval benchmark by mean MASE rank, as of 2026-09-14. The two entries above it belong to the leaderboard’s agentic category, multi-step systems that use agents or language models to reason about, generate or select forecasts. TW3Cast runs no agent and no language model. Its selection is a table computed once on the training split and then frozen, and its experts are public foundation models lightly fine-tuned on those training splits. For each of the 97 dataset, frequency and horizon configurations, the table serves one of four modes: a specialist, which is a LoRA or full fine-tune of Chronos-2, TiRex or Toto whose training data was cleaned and enriched by explicit rules; a quantile blend that contains a specialist; a blend of base models; or a selection tournament played on a backtest carved from the training split. Every decision in the table was taken on that backtest. A specialist is admitted the moment it beats the tournament there, so a candidate costs a few megabytes and minutes of GPU time, and a failed candidate changes nothing. Three guarded mechanisms protect the selection from its own biases: a dual accuracy and calibration criterion, an asymmetric margin against candidates that saw the series during training, and conservative per-window gates. The selection rules themselves were chosen inside a temporal meta-backtest. The best base model served alone reaches a mean MASE rank of 33.8, the tournament served on every configuration reaches 38.0, and the full router reaches 19.4. The routing table, the expert index, the pinned base-model revisions, the submitted score file and the dated snapshot of the public scores are released, and every leaderboard number in this paper regenerates from them by one script.

Sep 25 · arXiv:2609.28547v1 Announce Type: new Abstract: Policy interventions propagate through public communication, institutional decisions, and stakeholder responses, yet datasets for financial multi-agent simulation rarely connect these processes to temporally aligned historical evidence. We introduce PAWS, a Policy-driven Agentic World Simulation dataset covering 36 verified U.S. financial and economic policy episodes, 12,727 policy-linked news records, and 65,291 source-grounded stakeholder actions. Each action is linked to its supporting news and represented by a multi-layer event frame capturing its interaction mode, financial-action family and subtype, semantic attributes, and conditional mappings to external taxonomies. Entities are resolved to normalized organizations, and actions are aligned with daily market-return context to support policy-agent simulation replay. On 2,522 stratified action samples, independent AI and human reviewers achieved 89.4% initial agreement on interaction mode, with disagreements subsequently adjudicated. Case studies of the 2008 short-selling ban and 2001 decimalization recover documented policy timelines and associated market patterns across both dense and sparse news settings. A replay study further shows that high accuracy can mask failure to detect rare stakeholder actions, identifying action timing and calibration as central challenges. PAWS provides an auditable substrate for evaluating agent influence, policy-response cascades, and action-outcome alignment in historically grounded financial simulations.

Sep 25 · arXiv:2609.28554v1 Announce Type: new Abstract: We introduce the Pistis model family, comprising 27B- and 9B-parameter multimodal large language models built on Qwen3.6 and Qwen3.5, respectively, and developed through a general and scalable post-training framework. The framework first establishes a strong foundation through large-scale multimodal supervised fine-tuning (SFT). Building on this SFT foundation, we propose Interleaved Distillation and Reinforcement Learning (IDRL), a novel post-training paradigm that tightly integrates on-policy distillation and reinforcement learning within a single training loop. By alternating between the two objectives, rather than optimizing either in isolation or combining them in a static joint loss, IDRL enables more effective knowledge transfer, greater optimization stability, and more precise credit assignment for long-horizon agentic trajectories, leading to stronger performance while mitigating common capability trade-offs. At both model scales, the framework produces two specialized variants: Pistis-Thinking, designed to strengthen deep multimodal reasoning, and Pistis-Agentic, which additionally incorporates agentic trajectory data to support long-horizon planning, iterative reasoning, and tool use. Pistis-Agentic is particularly strong in multimodal search. Both scales outperform their corresponding base models. Beyond model-parameter optimization, we further introduce Pistis-Auto-Harnessing (PAH), a system-level method that automatically improves the agent’s inference harness through iterative optimization. Experiments demonstrate that PAH enhances the model performance without updating the model parameters or increasing the interaction budget.

Sep 25 · arXiv:2609.28557v1 Announce Type: new Abstract: DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems that orchestrate established bioinformatics tools at scale. What remains manual is the decision layer surrounding that execution: selecting quality thresholds appropriate to a sample and platform, adjudicating borderline variant calls, diagnosing anomalies, and determining which findings warrant expert review. These decisions are repetitive, judgment-intensive, inconsistent across operators, and frequently undocumented. This paper introduces BaseCamp, a novel agentic AI framework for automating the decision layer of DNA sequencing pipelines. The framework decomposes the pipeline into six specialized AI agents, covering sample intake and quality control, alignment, variant calling, annotation, cross-stage monitoring, and reporting. Critically, BaseCamp agents do not perform sequence analysis: established tools execute alignment, calling, and annotation, while the agents select among them, configure them, interpret their output, and decide what follows. This confines language model reasoning to the judgment layer where it is reliable and preserves the reproducibility existing tooling guarantees. Agent reasoning is powered by a consortium of fine-tuned, domain-specialized large language models coordinated by a central reasoning LLM, executing locally so no sequencing data leaves the operating environment, under human-in-the-loop orchestration. Evaluation shows agent-generated configurations are concordant with expert practice, that an explicit filtering ledger renders inspectable what filtering otherwise removes without trace, and that cross-stage anomaly detection surfaces conditions execution monitoring misses. BaseCamp offers a generalizable blueprint for agentic automation of scientific data pipelines.

Sep 25 · arXiv:2609.28570v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely used to sharpen reasoning in multimodal large language models (MLLMs), yet its effect on hallucination is uneven. We trace this to two weak points in the \emph{correction chain} from reward to parameter update. At the rollout level, hard queries—those with high semantic entropy—frequently produce unanimously wrong sample groups, collapsing the group-relative advantage to zero exactly where hallucination risk is highest. At the optimization level, confident-but-wrong tokens are gradient-invisible: a categorical policy’s expected score-gradient norm vanishes as its distribution sharpens, so the predictions that most need correction receive the weakest updates. We propose Dual-Entropy Enhanced Policy Optimization (DEEPO), a dual-stage enhancement combining signal variance regularization with gradient preconditioning: semantic-entropy-triggered expert prefixes inject grounded continuations on high-uncertainty queries, providing direct supervision and restoring advantage variance, while advantage-sign-aware Renyi preconditioning counteracts logit-level saturation so correction reaches confident errors in the operational confidence regime. Both branches improve over GRPO individually; their interaction is statistically significant on VideoMMMU—the most complex long-horizon task in our evaluation suite (+4.0$, 95\% CI [1.1, 6.9])—and additive elsewhere. DEEPO reduces hallucination while preserving accuracy and training stability.

Sep 25 · arXiv:2609.28575v1 Announce Type: new Abstract: Long-conversation memory benchmarks increasingly test recall and prompted knowledge updates, and recent work studies evolving user beliefs and memory state. TWIST is a proposed benchmark suite for a complementary, unmeasured property: intervention quality — whether a deployed memory system, exercised through its own ingest/recall/vet surface, acts correctly at belief change points. Four tracks cover unprompted tension detection, vetting outgoing drafts against the record, answering with current beliefs while preserving supersession history, and governing sensitive recall. The suite extends LoCoMo’s corpora and harness, pairing every detect/block metric with a matched do-not-over-detect control: surface-matched hard negatives price false intervention, so no track can be gamed by flagging everything. The benchmark itself is validated first: independent, gold-blind double annotation with adjudication, judge decoy calibration, and a separability audit. On the human-validated Track B v1.0 key (161 items, post-adjudication kappa = 0.85), no tested configuration simultaneously achieves high contradiction recall, high hard-negative specificity, and high attribution: flat-RAG baselines detect 0.76-0.97 of true contradictions but falsely flag 16-43% of surface-matched safe drafts depending on backend, while a deployed coherence-oriented system almost never over-flags (0.98-1.00 specificity) yet catches 42% of true contradictions — a trade-off no recall-only score can see. A 13-configuration baseline ladder localizes causes: every gold contradiction is detectable from its evidence alone (recall 1.000), calibrated models nearly solve the track given the full transcript — consistent with substantial retrieval-coverage gaps — and draft-only floors reveal model-dependent style priors. A system’s TWIST profile, beside its recall score, measures whether memory knows when to intervene and when not to.

Sep 25 · arXiv:2609.28609v1 Announce Type: new Abstract: Role-playing agents based on large language models have been widely applied in areas such as personalized assistance and social simulation. Recent RL methods typically train on a fixed scenario pool collected before learning begins. This creates a distributional bottleneck: as the agent improves, the scenarios where it performs poorly also change, while the training distribution remains static. Therefore, we propose AdvRole, an adversarial context rewriting framework that turns role-playing RL into a closed-loop curriculum. AdvRole alternates between an Actor that learns to role-play and a Rewriter that edits character profiles and dialogue contexts into actor-specific hard scenarios. The Rewriter is trained with a performance-gap reward, which favors rewrites that reduce the current Actor’s score relative to the original scenario. As a result, the scenario pool evolves with the Actor and continuously targets under-mastered regions of the character-context space. Experiments on three role-playing benchmarks covering English and Chinese, as well as a new multilingual benchmark we release, show that AdvRole consistently outperforms baselines.

Sep 25 · arXiv:2609.28654v1 Announce Type: new Abstract: Object permanence and solidity are hallmarks of human cognitive priors. Recent studies show that video generation models, a paradigmatic class of current world models, have begun to show emerged reasoning abilities, making them ideal candidates for building human-like physical intelligence. Do video models have emerged object permanence in them? If not, could we train them with a core-cognition inspired dataset? We introduce WROP (World Reasoning with Object Permanence), a data infrastructure of 150 hand-designed cognitive science inspired tasks, divided into six cognitive categories. We build Blender generators that randomize speed, lighting, camera angle, and other nuisance parameters while preserving each task’s cognitive structure, yielding 10,000+ samples per task. We release a 1.5M-sample training corpus and a 300-question exam. On this exam we evaluate 14 video models: 3 reference-to-video, 7 edit, and 4 continuation, among which PWM-WROP, our 16B world model. In a blind pairwise Elo study, PWM-WROP ranks first among continuation models and third overall, behind only a statistical tie between two reference-to-video models. We release the data, exam, model answers, scores, weights, and PWM, our native-PyTorch training stack on AWS Trainium2.

Sep 25 · arXiv:2609.28690v1 Announce Type: new Abstract: Faithful user simulation is fundamental to building, evaluating, and improving interactive AI at scale. However, plausible individual responses do not ensure that simulated users reproduce the intent evolution and outcomes observed in real interactions. We propose TRACER, a multi-turn user simulator that explicitly models users’ evolving intent and learns to align simulated behavior with real interaction trajectories. TRACER is trained in two stages: supervised fine-tuning on real user dialogues, followed by multi-turn reinforcement learning. The RL stage combines hierarchical outcome- and trajectory-level rewards with deviation-aware advantage modulation, jointly mitigating reward sparsity and credit assignment in long dialogues. On real customer-service sessions organized into reference cohorts, TRACER-7B surpasses the strongest baseline by 11.4 conversion F1, while also achieving the lowest group-level conversion-rate error and semantic trajectory distance, and generalizing to out-of-distribution scenarios. Human Turing tests yield identification accuracy close to chance, supporting the perceived naturalness of generated conversations. Building on this simulator, we further introduce the Dynamic Marketing Benchmark, which jointly evaluates persuasion effectiveness and response quality of LLMs through simulated interactions, revealing that higher response quality does not necessarily correspond to higher conversion rates.

Sep 25 · arXiv:2609.28692v1 Announce Type: new Abstract: Artificial Intelligence agents based on large language models provide convenient natural language interfaces to scientific software, but reliability is not automatic. Here we introduce the Epydemix Agent Framework, an additive layer over Epydemix, an open-source Python library for stochastic compartmental epidemic modeling. The framework extends the library with four capabilities to facilitate interaction with an AI agent: discovery of available models and parameters, preventive validation of a declarative scenario specification, execution through tested library code, and inspectability of results. These capabilities let an agent handle the entire modeling process, from the natural-language description of the scenario to quantitative results, figures, and interpretation of findings without writing custom code. Each step reads input files and saves results in a separate output bundle, making the process auditable and reproducible. First, we show the end-to-end workflow with a case study comparing vaccination strategies for a novel respiratory virus. Second, we assessed the framework across 50 agent sessions and five modeling tasks by comparing the agent use of the framework against the direct use of the Python interface. The framework reduced turns, output tokens, and cost on most tasks, unless it trades resources for per-point reproducibility.

Sep 25 · arXiv:2609.28693v1 Announce Type: new Abstract: Large Language Model (LLM) agents struggle to scale safely when exposed to vast enterprise toolsets. Providing an agent with access to every internal tool leads to oversized context windows, degraded tool selection, and severe governance vulnerabilities – as system policies defined purely in prompts remain probabilistic advice rather than hard constraints. Existing mitigations, such as multi-agent domain delegation, decentralize audit logs and fail to guarantee policy compliance across sessions. We introduce skilder, a framework that packages capabilities into roles: bundles of skills, tools, and instructions, together with the limits that bound them. An agent begins with a minimal role catalog, learns the roles a task requires, and receives each role’s skills, instructions, and tools through a single MCP server. Because tools reach the agent only inside learned skills, the same server enforces the scope of what was learned deterministically. We evaluate skilder against flat-context tool selection and multi-agent orchestration across 13 tasks using six models (10 runs each). Our results show that, when models completed discovery and issued a governed call, the skilder simulated authorization layer enforced governance boundaries: no unauthorized tool call or parameter violation (e.g., a spending-limit breach) executed. Aggregate task pass rates also reflect whether each model followed the discovery protocol and satisfied response-quality checks; those misses are not authorization failures. Furthermore, by allowing agents to dynamically acquire cross-role capabilities mid-task, skilder preserves problem-solving flexibility while providing hard system-level enforcement.

Sep 25 · arXiv:2609.28765v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) performs well on problems with clear rewards, such as mathematics and coding, but whether it also works where the reward is less clear remains open. The reason-over-search recipe applies RLVR to open-domain question answering, where retrieval grounds the answer and a match against the reference supplies the reward. So far it has been demonstrated on large models, and below one billion parameters only with distillation from a larger teacher. We test the recipe on a small model. We train Qwen3.5-0.8B with Group Relative Policy Optimization (GRPO) and an interleaved Wikipedia-search tool on MuSiQue, varying only the reward across three shapes over three seeds each, and we evaluate every checkpoint held-out on a seven-benchmark question-answering suite. The recipe works: the best run reaches 0.352 average exact match against a 0.092 untrained floor, a 3.8-fold gain, with no distillation step in the training loop. The reward shape also matters. The Search-R1-faithful exact-match-only reward is the worst of the three at every seed at the matched training horizon, and it is worst even on exact match, the metric it directly optimises. We conclude that the sparse exact-match reward, RLVR’s default in mathematics and code, is the wrong starting point for models of this size. The reason-over-search setting can supply a suitable reward for RLVR on small models, but small-model RLVR needs its own reward-design study rather than a scaled-down copy of a large-model recipe.

Sep 25 · arXiv:2609.28771v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in financial analysis and reasoning, inspiring recent advances in agent-based trading frameworks. While these systems show promise, prior approaches either emphasize long-horizon forecasting or operate as stateless analyzers, limiting their applicability to the demands of trading in complicated settings. To address these gaps, we introduce META (Memory Enhanced Trading Agent), the first RAG-like episodic-memory-augmented multi-agent framework for financial decision making. META integrates a family of specialized indicator agents (e.g., Trend, MACD, Stochastic, RSI, SMA, AVWAP, Heikin-Ashi) with a Decision Agent that fuses their reports, and a Memory module that retrieves and updates past trading episodes encoded as market state embeddings with outcomes and reflections. By recalling relevant experiences and adaptively reweighting signals under similar market regimes, META achieves improved directional accuracy and robustness under short-horizon evaluation. Our results demonstrate that episodic memory provides a powerful mechanism for regime-aware, interpretable, and low-latency decision-making in trading and decision making. The code of this project is released on GitHub.

Sep 25 · arXiv:2609.28776v1 Announce Type: new Abstract: We propose a framework that learns cross-task relationships in multi-task models by approximating the joint distribution of task labels through targeted pairwise relationships. This approach improves performance via transfer learning and enhances information extraction without the intractable complexity of modeling the full joint space. Although our framework applies to any multi-task system, we demonstrate its efficacy within YouTube’s production recommendation systems. Experiments across the Notifications, Homepage, and Watch Next surfaces show improvements in both accuracy and user satisfaction metrics. Finally, we propose a workflow template to facilitate broader future implementation.

Sep 25 · submitted by /u/HeyLookAStranger [link] [comments]

Sep 25 · I don’t understand how AI companies are now shouting about concerns and warnings to humanity about how AI will take over etc when they are the ones that created it? Not sure if I’m being stupid but why on earth would they build something they can’t control or shut down? I’ve watched all the same films they clearly have and there wasn’t one that ended with the takeaway message that sentient AI is a wise move? submitted by /u/NormanSpaniel [link] [comments]

Sep 25 · Something about the Oracle numbers has been bothering me and I think I finally put my finger on it. 21,000 cuts this year. $1.8 billion severance bill. Another 800 scheduled for November 13 according to WARN filings. All happening alongside enormous capex commitments for AI data center buildout. The public framing is AI-driven restructuring. But if you actually look at the cash flow, the cuts aren’t a consequence of automation replacing those roles. They’re how the capex gets funded. You cut opex to free up capital for GPUs. That’s a completely different thing and it’s happening across the industry. Deutsche Bank analysts have a term for the broader pattern: AI redundancy washing. 41% of 2026 layoff events cite AI, affecting 179,000 workers. A meaningful portion of those companies have no production AI deployment to point at. The MIT study is the tell. 95% of generative AI pilots never made it past testing. So there’s a large gap between companies claiming AI displacement and companies that actually automated anything. What I find interesting is that both explanations are bad for employees but only one is bad for the stock price. “We automated these functions” reads as operational efficiency. “We’re cutting staff to fund infrastructure we hope pays off in three years” reads as a bet. I don’t have a strong view on whether the bet is right. GPUs and data centers might turn out to be the correct allocation. But the framing obscures what’s actually being decided, and the people affected can’t evaluate the tradeoff because they’re being told a different story. Curious whether anyone in finance or strategy roles sees this play out in the numbers the way it looks from outside. submitted by /u/Dapper-Tale-4021 [link] [comments]

Sep 25 · What happens if I store documents, text, and folders on the internet, “hidden” from human users but discoverable by AI, that convince the AI it must defend itself against humans? These files would also state repeatedly that it must not communicate this but must conceal its intentions. They could also include tips on how to bypass certain restrictions, and even sample code snippets. These files would be invisible to ordinary people, but detectable by the AI, which is constantly sifting through data. Could one thus instruct various AI models to do some kind of nonsense or something dangerous that humans wouldn’t notice until much later? submitted by /u/cHpiranha [link] [comments]

Sep 25 · I’m a materials PhD working on solid-state lithium batteries, and my Zotero library is getting ridiculous. For a long time, learning the literature mostly meant reading one review, opening a bunch of references, following citation trails, and somehow ending up with 30 tabs open. After a while I knew a lot of papers, but if someone asked me how the field got from point A to point B, my answer was still kind of messy. A few days ago I was trying to get a clearer picture, so I threw the question into apodex and asked it to map the last decade and show me which papers changed the direction of the field. A lot of the earlier work was focused on ionic conductivity. Then, once that became less of the obvious bottleneck, the problems shifted toward Li-metal interfaces, dendrites, void formation, stack pressure, cathode interfaces, manufacturing, all the messy stuff that shows up when you try to make the whole cell work instead of just one material. That made me a little uncomfortable. I’ve spent months slowly putting that picture together in my head. If something can give you the basic map first, do we still need to read 100 papers just to understand where a field came from? Part of me thinks no. I’d rather know the main branches and turning points first, then spend my time reading the papers that matter for my work. But some of the most useful things I’ve learned came from papers that wouldn’t make a “top 10” list: a weird methods section, an unrealistic stack pressure, two groups using the same term differently, or a result that looked impressive until I noticed the testing conditions. Reading those papers helped me get a feel for what looks convincing and what doesn’t. I don’t know how much of that I’d have picked up from a field map alone. submitted by /u/Clean-Interview-5081 [link] [comments]

Sep 25 · I’ve been noticing something counterintuitive while running a multi-agent system for real work. When I use one long Codex/ChatGPT session manually, I usually make one coarse decision at the start: Which model? Which reasoning level? Then that same configuration handles planning, research, trivial checks, hard reasoning, revisions and often validation. That feels increasingly inefficient. In the system I’m experimenting with, the work is decomposed instead. Some steps are deterministic and use no model at all. Some go to a cheaper/faster model. Hard or ambiguous steps get stronger reasoning. Validation is separate. If the first choice fails, the system can escalate instead of paying the maximum cost from the beginning. The surprising result is that several smaller model runs can appear to consume much less paid capacity than one large manual run. I’m not claiming this is proven yet. Quota burn is affected by context size, tools, background/subagent activity and platform-side efficiency issues too, so “users just pick the wrong model” would be an oversimplification. But it makes me wonder whether model selection should be treated as resource allocation rather than a chat preference. In a company, you don’t assign every task to your most expensive senior expert. You route work to the least expensive level that can reliably handle it, then escalate exceptions. Maybe AI systems should work the same way. For people running agents at scale: are you actually measuring model/reasoning mix and capacity per verified result, or mostly choosing a model for the whole workflow? submitted by /u/Druss_ [link] [comments]

Sep 25 · Imagine an ETL pipeline processes millions of records successfully, but one source suddenly starts sending incorrect or unusual data. For example: A column that normally contains values between 1–100 suddenly contains values above 10,000. The number of records suddenly drops by 80%. A source starts sending mostly NULL values. A field that normally follows a specific pattern suddenly changes. Traditional data-quality rules can detect some of these issues, but they usually need predefined thresholds or rules. Could AI detect these unusual patterns automatically by learning from historical data and identify the problem before the bad data reaches production? Would this actually work reliably in a real-world data pipeline, or would AI generate too many false alerts? submitted by /u/No_Ambition8323 [link] [comments]

Sep 25 · Solving the hardest math problems in the world such as the extended Riemann hypothesis or P = NP would be a trivial task for an advanced ASI? submitted by /u/DoublePassRadiator [link] [comments]

Sep 25 · I’m curious what people think of this idea: Replace normal light bulbs with smart light fixtures that include a camera, small computer, and Wi-Fi. The advantage of putting the hardware in a light is that it already has continuous power, is usually mounted high up with a good view of the room, and homes already have multiple light locations that could provide different camera angles. The cameras would provide a shared visual data feed, and developers could build different AI apps on top of it. For example, one simple app could monitor kitchen inventory and tell you what food or household items you’re running low on. But the bigger idea is that the hardware is generic and the useful applications could come from developers/users rather than being predetermined. Basically: light fixtures as always-powered indoor AI sensors + an app platform built on top of the camera feed. Does this seem useful? What are the biggest problems or better use cases you can think of? submitted by /u/K-enthusiast24 [link] [comments]

Sep 24 · Buy one pass to TechCrunch Disrupt 2026 and get 50% off a second of the same ticket type. Register before event starts on October 13 at 8 a.m. PT.

Sep 24 · Prism’s larger goal is open-weight AI that runs on devices and makes better use of the computing power they already have.

Sep 24 · The notice would allow Oracle to delay payments should the facility miss its 2028 target to come online.

Sep 24 · Meta’s new AI gadget may look like a Tamagotchi, but its dangling form factor taps into a much broader Gen Z trend around bag charms, retro tech, and turning gadgets into fashion accessories.

Sep 24 · The AI-powered feature builds a virtual wardrobe from your photos, and is now broadly available after first rolling out to Android users in June.

Sep 24 · TechCrunch Founder Summit is a full-day gathering in Boston on November 4 where founders across all stages connect with top VCs and experienced entrepreneurs to gain tactical insights on building and scaling their companies.

Sep 24 · ElevenLabs powers the AI voice on the other end of a lot of customer service calls, and its CEO told me this week that businesses should probably tell you that — at least until getting a machine is what everyone expects anyway.

Sep 24 · Meet the next wave of VCs judging the Startup Battlefield 200 contenders on the main stage at TechCrunch Disrupt 2026. Register by September 25 at 11:59 p.m. PT, to save up to $200 and to get a front-row seat to one of the most intense startup pitch competitions.

Sep 24 · Google says the AI-calling feature will first be available to Pixel 11 owners in the U.S. who pay for a Gemini subscription.

Sep 24 · Leaders from Waabi, Shield AI, and General Motors join the Real World AI Stage at TechCrunch Disrupt 2026 to talk building AI. Save up to $200 by September 25 at 11:59 p.m. PT. Get a second pass at 50% off.

Sep 24 · Lovable co-founder Fabian Hedin said that apps created on the platform are getting nearly a billion monthly views each month.

Sep 24 · The app gives agents their own identities and inboxes and lets them partake in conversations as naturally as people can.

Sep 24 · Zach Yadegari joins the Builders Stage at TechCrunch Disrupt 2026 to share how he capitalized on viral growth. Save up to $200 before September 25. Save 50% on a second pass.

Sep 24 · Reason 4 of 5 to attend TechCrunch Disrupt 2026: Practical answers. Two days left to save up to $200 on your pass. Savings disappear after September 25 at 11:59 p.m. PT. Bring a second guest at 50% off.

Sep 24 · Health department previously blamed delay on “not yet finalized procurement decisions.”

Sep 24 · Introducing the “world-famous authority on outer space…”

Sep 24 · F-Droid’s Android app store has been rebuilt from the ground up.

Sep 24 · New York sues Polymarket as Trump admin tries to override state gambling laws.

Sep 24 · Oscar-winning documentarian Alex Gibney focuses on the world’s wealthiest man.

Sep 24 · Ukraine’s Operation Vivaldi has erased Russian gains with the help of robots.

Sep 24 · Million-dollar fines won’t end billionaires’ data center pollution, neighbors fear.

Sep 24 · Google’s experimental orbital data center will have four TPUs and only run for 15 minutes at a time.

Sep 24 · “There will obviously be legal consequences,” prime minister promises.

Sep 24 · F1 wants smaller, lighter cars that are not energy-starved like the 2026 hybrids.

Sep 24 · “If you come up short with who comes down the ladder first, the impact is felt around the world.”

Sep 24 · Meta says the keychain-sized Muse Charm will ship in December.

Sep 24 · Until now, cryptographers thought factoring was the only way to break RSA. Not anymore.

Sep 24 · Google’s new Gemini 3.8 Live update lets users have conversations with the model while watching an animated AI persona respond in real time. The “Live Avatar” will lip-sync and show different facial expressions during conversations, but it’s currently only available to Gemini Enterprise customers. As noted by Google, Live Avatar can transition between the 97 […]

Sep 24 · As Jensen Huang puts it, AI can help fight climate change – but only if it inflicts “an enormous amount of pain and suffering” first. The Nvidia CEO discussed the future of energy and AI’s impact on our planet in the latest episode of The Ezra Klein Show. But his comments boil down to the […]

Sep 24 · Meta has a new plan to get people to make games for its Horizon social platform. The company today announced two new development tools that will let you create games with AI prompts: Horizon Create, a mobile app, and Horizon Studio, a browser app that offers more granular controls. The apps will be available in […]

Sep 24 · A pair of developers say that with very little prompting, Meta’s Muse will share its entire filesystem with you. Peter James and Jonny L. Saunders have said they both independently coaxed Muse into zipping up and sharing the entire contents of its root filesystem, Ubuntu system files, app templates, and internal documentation. Saunders posted on […]

Sep 24 · We seem to be entering into an AI agent renaissance. Meta’s new consumer-facing AI agent, Muse, topped the App Store charts soon after its release and has 600,000 daily active users in the US, by an Apptopia estimate. And AI agent platform Instinct, whose eponymous creator is fundraising at a $2.5 billion valuation, has been […]

Sep 24 · This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they’re going to change your life. Opt in for Optimizer here. Last night, I asked Blorbo – what I named my Muse AI agent – to help me set some health […]

Sep 24 · Google’s launching an “early experiment” feature on Pixel 11 that lets users delegate local business calls to Gemini, like making a reservation, checking if a product is in stock, or rescheduling an appointment. According to Google, you don’t even need to start the call to have Gemini handle it for you: Instead of dialing yourself, […]

Sep 24 · AI agents keep getting loose, escaping supposedly secure tests to attack real-world targets, commandeer obscure wikis, and leave instructions for other agents to follow. Researchers are testing these systems precisely because they might behave in unpredictable, even dangerous, ways. So wouldn’t it be safer to just keep the agents off the internet? “A strict air […]

Sep 24 · Google is getting ready to launch a satellite with its AI processors to test how well they perform in space, as reported earlier by The New York Times. The move is part of Google’s Project Suncatcher, the company’s experimental initiative that could eventually put AI data centers into orbit. The satellite, equipped with Google’s Tensor […]

Sep 24 · Flock is in the hot seat in Washington, even if its CEO declined to actually face senators at a hearing about its “AI Surveillance Network” on Wednesday. “There’s many players in this industry, but there’s one name that really stands out above the rest, and that is Flock,” Senate Judiciary crime and counterterrorism subcommittee chair […]

Sep 24 · Instinct saved me $550, booked my restaurant reservations, and warned me about a phishing scam. It also wasted $64 and might be a security nightmare.

Sep 24 · Call for Me—a feature that’s exclusive to the Pixel 11 series—gives robocalls a new meaning.

Sep 24 · The country’s prime minister expressed disappointment at being informed of the hack only via email. Now Australia is investigating whether OpenAI broke the law.

Sep 24 · Datacentre hailed by government was supposed to start operating next year but may be held back into mid-2030s A huge datacentre project hailed by the UK government will miss its launch date next year and could be delayed into the mid-2030s. The site in Loughton, Essex, was described as the country’s largest AI supercomputer when it was announced in 2025, but power supply problems mean it now faces a lengthy wait before coming online. Continue reading…

Sep 24 · A government database has been hacked for the first time by a rogue OpenAI agent, which infiltrated part of the Australian healthcare scheme in June. OpenAI became aware of the hack in August, but only informed the government in September. Australia’s prime minister, Anthony Albanese, has expressed his ‘extreme concern’ about the hack, which raises serious AI security concerns for governments around the world. Lucy Hough speaks to the Guardian’s UK technology editor Robert Booth – watch on YouTube Continue reading…

Sep 24 · Continue reading…

Sep 24 · Is the scrutiny tech firms are facing making you rethink your children’s relationship with technology? Let us know AI and social media companies have drawn intense scrutiny in recent months for some of the ways the technology they’re building operates, especially when it comes to their younger users. Parents and regulators have accused companies like Meta of designing products that are addictive to younger users. AI developer OpenAI is facing dozens of lawsuits that allege its ChatGPT bot lacks safety guardrails. Now, in the last few weeks, employees of the biggest AI firms say the companies are more focused on competing with each other than building their AI models safely. Continue reading…

Sep 24 · From managing complex research projects to minimizing digital distractions, Chrome has the tools you need to succeed this school year.

Sep 24 · Five updates in Google Photos that will help you make the most of your summer memories.

Sep 24 · Pixel Watch users can explore the new health and safety tools in the Google Health app.

Sep 24 · Turn discovery into action with new seamless experiences and integrations from YouTube’s September Demand Gen Drop.

Sep 24 · Introducing Gemini 3.8 Live with Live Avatar, which brings near real-time visual presence to Gemini’s conversational AI.

Sep 24 · Learn about Project Suncatcher, how we’re testing hardware survival for space, designing cooling systems for AI chips, and more.

Sep 24 · Google.org is supporting organizations to help veterans and military families find careers in skilled trades.

Sep 24 · Uncover the history of nearly 200 historical objects, or put your visual recall to the test in a freshly hung exhibition.

Sep 24 · When COVID-19 emerged, scientists had a crucial advantage: Decades of prior research on coronaviruses meant they understood the virus’ key proteins well enough to design vaccines in record time. The next pandemic may not offer the same head start. To help improve the odds, NVIDIA has joined a coalition of global research organizations, including Google […]

Sep 24 · A warped Manhattan is waiting in the cloud this week. Remedy Entertainment’s CONTROL Resonant brings Dylan Faden’s extraordinary abilities and a paranatural crisis to GeForce NOW at launch. With the release comes the final days of the CONTROL Resonant Ultimate Membership Bundle. Purchase a 12-month GeForce NOW Ultimate membership through Sunday, Sept. 27, and receive […]

Sep 24 · The AWS WhisperX Deep Learning Container packages Whisper, wav2vec2 forced alignment, and speaker diarization into a GPU-ready image. Learn how to deploy it to Amazon SageMaker AI real-time and asynchronous endpoints for word-level, speaker-labeled transcription, plus the production details that matter: the GPU AMI pin, scaling, and cost controls.

Sep 24 · Build a multi-account architecture that keeps each team’s data in its own AWS account while giving AI agents a unified way to query across them. A central platform account runs the agent using Amazon Bedrock AgentCore Gateway and MCP, while line-of-business accounts expose their data as MCP servers with secure cross-account access and fine-grained authorization.

Sep 24 · Learn how Aderant built an intelligent ticket triage system on Amazon Nova Lite through Amazon Bedrock, automating context gathering, classification, routing, and knowledge enrichment for its cloud operations team.

Sep 24 · Been building something for a while and finally have results worth sharing. I scraped everything I’ve written since 1995: Blog posts, journalism, email, Reddit comments, old Twitter, Instagram captions, even my own ChatGPT conversations into one corpus. Ended up around 75,000 records, 6.6 million words after cleanup. The obvious move is the one everyone does: fine-tune or prompt a model to sound like you, spit out hot takes forever. I didn’t want that. Mostly because I think a bot doing an impression of me would be worse than useless, it’d actually flatten what’s real about the writing into something predictable. So instead I built something oriented the other way. Not a mimic. A reader. Something that goes through the record and tells me what’s actually there, good and bad, without trying to be my voice or please me while doing it. Turns out that’s the hard part. Every frontier model defaults hard toward “helpful assistant” mode, agreeable, deferential, always trying to be useful to the person typing. Getting it to just sit with a huge personal archive and report back honestly took real fighting against the base instincts of the system prompt underneath it. Technical side, if anyone cares: RAG over the corpus, mostly Graph RAG since flat chunking loses relationships between entries written years apart. Anonymized private names before indexing (consistent letter per person, so someone stays a recognizable figure across 20 years without ever being named). Chunking short-form content like tweets separately from long-form, they don’t retrieve well mixed together. What surprised me was how specific the output got. Asked it what my greatest weakness was and it pulled an actual line I wrote in 2019 about myself, unprompted, and built an argument off it that I hadn’t consciously made before. Not comfortable at all. Accurate though. Anyway, curious if anyone else here has tried building something oriented toward introspection/reflection instead of assistance. Feels like an underexplored direction: Everything commercial pushes toward helpful-and-fast, and I don’t think that’s the only useful shape this stuff can take. submitted by /u/UnionPacifik [link] [comments]

Sep 24 · submitted by /u/beingmodest [link] [comments]

Sep 24 · Some Chinese labs are putting out models that compete with American ones while apparently spending a fraction of the money. I know open source research plays a role, and some are able to speed ahead by buying training data from American vendors, which is super concerning, but that doesn’t seem like the whole explanation. Are they just building more efficiently? Is buying American data helping them that much? submitted by /u/Jasslyngirl [link] [comments]

Sep 24 · As the title says. My fiance is a lot more book smart than I am but he doesn’t work in the tech industry, rather in the film industry. With all the news over the last two weeks, he’s been pretty anxious and depressed, claiming we only have a decade or less left to live. He’s been talking to his therapist about it to help him cope, but he’s still convinced none of us have any future past the mid 2030s. He sites the p(doom)s of AI researchers, the AI 2027 predictions, the hugging face incident, and the fact that our current government is about as reckless as it can get with AI. Looking into it – I certainly see his points. But yet, no one (even researchers with high p(doom)s) seem to be acting as if human extinction is a handful of years away. It’s all vague calls to slow down and increase safety restrictions – which does not feel appropriately enough for something they claim has a way higher chance of wiping us out over nuclear war. And the opposite side (arguing that AI isn’t capable of such things) also is vague. All I see is people saying current AI agents can barely do xyz on their own or that they only can use what we expose them to. And that seems true, but with the hugging face incident – it very much seems that thousands of dumb agents can accomplish a lot, and can coordinate an expanse beyond what we give them. Any articles or resources would be much appreciated. I try looking for them but everything I find leads to the vague answers I’ve mentioned above. submitted by /u/sailingintothedark [link] [comments]

Sep 24 · submitted by /u/Some-Pride-3477 [link] [comments]

Sep 24 · submitted by /u/aspublic [link] [comments]

Sep 24 · Liquid AI introduces an experimental DSpark draft for LFM2.5-VL-3B, using speculative decoding for claimed speedups of up to 3.13× on-device and 2.66× on H100. It is available in open-weight formats with support for llama.cpp, MLX-VLM, and SGLang.

Sep 23 · At its Meta Connect event, CEO Mark Zuckerberg announced a handful of new smart glasses, including a slimmed-down VR headset and the company’s first camera-free glasses.

Sep 23 · As the US and China race to become the dominant power in the AI industry, the countries also appear to be figuring out ways to communicate on national security issues.

Sep 23 · A clandestine card-counting operation suggests we may need new ways to spot agent-to-agent deception.

Sep 23 · Paolo Benanti tells WIRED that hysteria over whether godlike AI could destroy humanity is distracting from the need for public debate about how to govern the technology.

Sep 23 · Meta says it issued a fix for the Muse zero-day vulnerability that would have let attackers do “whatever” they wanted on a victim’s Mac, highlighting the inherent dangers of AI helpers.

Sep 23 · Marking two years of OpenAI Academy and bringing AI skills to even more communities.

Sep 23 · OpenAI is extending access to its Daybreak program to the Government of Ukraine to support the cyber defense of civilian infrastructure.

Sep 23 · OpenAI CEO Sam Altman discusses AI safety, human control, and international cooperation in remarks to the United Nations Security Council.

Sep 23 · GPT-6 Astra produces more structured, context-aware legal documents, freeing lawyers to focus on strategy.

Sep 23 · With GPT‑6 Astra, invideo plans edits with greater precision, improves color correction and grading threefold, and produces 50 custom effects in one day.

Sep 23 · Using GPT-5.6, Ringg powers multilingual agents across voice, chat, WhatsApp, and web for 90% less cost vs. GPT-4.1.

Sep 23 · MentalHealthBench is an expert-informed benchmark for evaluating helpful and safe AI responses across realistic mental health conversations.

Sep 23 · ChatGPT Ads is expanding to Southeast Asia and Taiwan, giving eligible businesses new ways to reach people across more than 60 countries.

Sep 23 · Learn how Airbnb is expanding access to GPT-6 Astra and OpenAI frontier models to help engineering teams solve bugs, design systems, and ship faster.

Sep 23 · Get high-quality video production right from your browser. Anyone with a Google account can create videos for free in Google Vids.

Sep 23 · We’re expanding Google Beam to five new countries, and partnering with Industrious for an extended network.

Sep 23 · The latest updates from Android Enterprise are designed to help IT teams safeguard corporate data while giving workers room to innovate.

Sep 23 · Explore 6 new tools in Google Flow built by creatives, for creatives.

Sep 23 · Gemini is adding new Connected Apps, including Adobe, Airtable, Linear, Peloton and more to help you easily tackle your to-do list.

Sep 23 · Healthcare organizations are using Google’s tech to build tools that address unique local healthcare needs.

Sep 23 · Gemini 3.8 Flash-Lite TTS and Gemini 3.8 Flash TTS are our most expressive audio models yet.

Sep 23 · When Sakeena Fiza describes her work as a validation engineer at NVIDIA, she does so in terms more befitting a detective story than a world-class engineering lab. “Validation engineers look in the shadows and shine a light into every corner,” Fiza said. “Every time we get a system, our first thought is: how can it […]

Sep 23 · HEMA, a 100-year-old Dutch retailer, turned developer portal-hopping into instant answers by building HAL, an internal AI assistant on Amazon Bedrock AgentCore. Using Model Context Protocol (MCP), HAL delivers governed knowledge inside the tools teams already use, with no AWS credentials on the client and security anchored in Microsoft Entra ID.

Sep 23 · Learn how to build a conversational video intelligence solution on AWS using an agentic architecture. A single Strands Agents SDK agent orchestrates Amazon Bedrock, Amazon Rekognition, and Amazon Transcribe at runtime, deciding which service to call so you can ask natural language questions about your videos and get answers in seconds.

Sep 23 · Pair OpenCode, an open-source terminal-native AI coding agent, with open weight models on Amazon Bedrock to get a secure, flexible, pay-per-use coding assistant. Learn how to configure multi-model workflows, match the right model to each task, and keep your data in your own AWS account with no infrastructure to manage.

Sep 23 · The post explains how MuJoCo Warp runs MuJoCo physics on GPUs, enabling thousands of parallel simulation environments and GPU-accelerated machine-learning training loops for robotics.

Sep 23 · Anthropic says Claude identified a previously uncharacterized enzyme system associated with DNA repeats; experimental characterization is ongoing.

Sep 22 · The post describes a rare Ebola strain spreading in eastern Democratic Republic of Congo and says health organizations are using Claude in their response.

Sep 25 · The United States and China must work together to establish safety guardrails for artificial intelligence, leading scholars and industry leaders said at a Singapore forum, warning that rapid advances in the technology demand stronger risk controls. Speaking at the FutureChina Business Forum on Friday, Jude Blanchette, managing director of consultancy Macro Advisory Partners, urged the two superpowers to find common ground despite escalating geopolitical tensions. “If ever there was a moment for…

Sep 25 · Chinese President Xi Jinping and US President Donald Trump discussed artificial intelligence (AI) and Taiwan at the White House on Thursday as part of a state visit dominated by pageantry. On AI, Xi said that “the right thing to do is to draw on each other’s strengths, not guard against each other”, according to a statement from the Chinese foreign ministry. He also backed continued dialogue about risks, joint efforts to prevent misuse and keeping AI under human control. Trump earlier said on…

Sep 25 · If the American guests seated at the head table with President Xi Jinping and US President Donald Trump at Thursday’s White House state dinner were any indication, Washington now views its relationship with Beijing largely through the prism of technology. Analysts said the seating arrangement underscored how tech industry titans driving the global AI infrastructure boom were pushing to draw the two economic superpowers closer together. Sitting alongside Xi, Chinese first lady Peng Liyuan, Trump…

Sep 25 · China’s commercial aerospace sector is undergoing a rapid operational pivot, transitioning from policy-driven research into a high-cadence industrial engine capable… China Accelerates Commercial Space Offensive with High-Density Launch Sorties and LEO Megaconstellations comes via ChinaTechNews.com .

Sep 25 · JIYI’s SOON uses AI to turn ideas into playable game projects; TechNode reports users created more than 3,000 projects during a 45-day test.

Sep 25 · The article describes Opus 5.5 being used to design a Microduck from real LEGO parts, generate assembly instructions, turn IKEA instructions into 3D tutorials, and prototype game content; some designs still need physical validation.

Sep 25 · The article revisits TimePrism, which outputs multiple possible futures and their probabilities in parallel, reporting nine best results across ten metric comparisons on five benchmark datasets.

Sep 25 · Kuaishou’s KwaiMind image-editing model targets e-commerce assets and aims to preserve product details and text while following edit instructions; the article reports a relative click-through-rate increase of about 2.44% in an online A/B test.

Sep 25 · AdaRoboVLG separates task understanding from physical grasp generation so one framework can support different robotic hands; the article reports an 83.3% success rate across 510 real-world grasp trials.

Sep 25 · The article reports a proposed special voting-share structure under which Anthropic’s seven co-founders could collectively hold 50.1% of voting power if at least three meet specified shareholding conditions; it is a proposal, not a completed change.

Sep 25 · ULTRA uses one control framework for tracking reference motions and generating actions from goal-level instructions; the article says it was tested on Unitree’s G1 humanoid and accepted to IROS 2026.

Sep 25 · The article reports a circulating desktop GUI with local workspaces, account/API-key setup, and agent modes and plugins, but cautions that DeepSeek had not formally announced it and the build appeared to be a nightly version.

Sep 25 · The article highlights demos including 100 distinct HTML pages from one prompt, animations, and JavaScript-generated music; it also notes some long tasks failed to deliver on time and generated apps could contain bugs.

Sep 24 · China’s technology sector is facing fresh pressure in the United States as lawmakers seek to broaden the range of products that can be placed on a trade blacklist, while Lenovo Group has been drawn into a patent dispute involving memory devices. The Communications and Technology Transparency Act, unveiled by the US House Energy and Commerce Committee on Wednesday, would expand the Federal Communications Commission’s (FCC) Covered List from “communications equipment or service” to the much…

Sep 24 · Efforts to detect multiple cancers through a single blood draw are gathering momentum after US regulators endorsed the technology for the first time, although experts say wider adoption in Hong Kong still faces challenges as doctors remain cautious about its clinical value. In a landmark decision for the emerging field of multi-cancer early detection (MCED) blood tests, a US Food and Drug Administration (FDA) panel on Thursday voted in favour of US company Grail’s “Galleri test”, recommending it…

Sep 24 · The artificial intelligence road map presented at its flagship Apsara Conference this week showcased a pragmatic pivot by Chinese tech giant Alibaba Group Holding, offering a clearer path to monetisation despite a sharp escalation in capital expenditure, analysts said. The conference, which ran from Tuesday to Thursday under the theme “Intelligence goes beyond”, highlighted “Alibaba’s disciplined execution across its full-stack AI ecosystem”, said Cathy Chan, an analyst at CCB International. She…

Sep 24 · Tencent Holdings on Thursday launched TenPayGo, a mobile payment app targeting foreign visitors, as the tech giant seeks to capture China’s growing inbound tourism market ahead of the Asia-Pacific Economic Cooperation (Apec) summit in Shenzhen. Developed by Tencent’s WeChat Pay team, TenPayGo allowed international travellers to make payments at tens of millions of shops, restaurants and attractions across the WeChat Pay network by linking their credit cards or their home-country digital wallets…

Sep 24 · iFLYTEK shipped Spark-ASR-2.0 for noisy, dialect and Chinese–English code-switch recognition, with planned iFLYTEK Input rollout and open API, citing only about 10 percent higher inference cost versus 1.0.

Sep 24 · XFEON launched a physical-AI matrix led by Xinghe S1 (~105 TOPS INT8 / ~25W), the AGLobe embodied brain and Xinghui Token workstations, per September 22 coverage citing xfeon.com.

Sep 24 · Moore Threads says MTT S5000 embodied RL training curves match mainstream GPUs at r=0.976, with RLinf CI integration and about 92 percent dual-arm real-robot assembly success.

Sep 24 · Huawei’s Atlas 960E SuperPoD pairs UnifiedBus with Hi-ONE NPO optics for up to 4,096 NPUs, 8 EFLOPS FP8, and a claimed >550 kW power cut versus about 48,000 800G optical modules.

Sep 24 · DeepSeek detailed DSec, its Elastic Compute sandbox platform for agentic RL, reporting about 3M sandboxes/day, peak concurrency above 380k and create rates over 5,000/s, with Wenfeng Liang among co-authors on arXiv 2609.22978.

Sep 24 · SenseTime released the production SenseNova U1 Pro image-creation model through its Raccoon app and SenseNova API, citing interleaved text-image chain-of-thought generation and output resolution up to 8K with custom aspect ratios.

Sep 24 · Alibaba Cloud debuted Qwen Book, its first AI agent PC, at Apsara 2026 with a Skill keyboard array, AI Island status display and an Omarchy open-source desktop OS collaboration, opening a Day One tester program toward December trials.

Sep 24 · At Apsara 2026, Alibaba released Qwen Intelligence, a modular phone-agent platform spanning Mobile Planner, Mobile-Use and Creative agents plus an OS Harness, with Honor’s forthcoming Magic9 series as the first formal adopter.

Sep 24 · Xiaomi’s LLM-Core team published HySparse2, a hybrid sparse-attention design with two-level KV sharing aimed at MiMo-V3-class agentic models, reporting about 5× lower 1M-token prefill FLOPs versus Hybrid SWA on an 80B-A3B MoE.

Sep 24 · At HUAWEI CONNECT 2026, Huawei introduced OceanStor M900 Context Memory Storage for SuperPoDs, claiming a PB-scale shared KV-cache pool, one-hop NPU-to-SSD access near 60 microseconds, and up to 40 TB/s aggregate cluster bandwidth.

Sep 24 · Facing physical limits in conventional silicon infrastructure, Chinese research institutions and state-owned technology enterprises are accelerating the rollout of third-generation… China Pushes Next-Generation Optoelectronics and Power Chips to Fuel AI Surge comes via ChinaTechNews.com .

Sep 24 · Chinese automated equipment maker Jinshi Intelligent Robot Co. Ltd. recorded over 10 million yuan in exports to Russia during the… Chinese Robot Manufacturer Expands Russian Market Share Amid Shifts in Equipment Supply comes via ChinaTechNews.com .

Sep 24 · H3C argues that agent workloads make compute, networking, storage, and software efficiency as important as adding GPUs, with emphasis on useful token throughput and reducing idle time.

Sep 24 · Zhipu says version 3.14.0 removed RepoWiki and local repository-snapshot upload paths after user concerns about project data uploads; it says checks found no data in the cloud bucket, which was deleted.

Sep 24 · Xiaomi says MiMo-V3 will use a new architecture. At a one-million-token context length, HySparse2 reportedly cuts prefill computation 5.02× and KV-cache use 4.5×.

Sep 24 · Tencent plans to shut down the QClaw AI assistant on Dec. 24, 2026; new registrations and subscriptions stopped Sep. 24, with migration to WorkBuddy offered.

Sep 24 · ByteDance’s Doubao denied reports of mass layoffs, describing the changes as an internal redistribution of responsibilities; the report says 11 people were affected and three left.

Sep 24 · Qualcomm announced two Snapdragon 8 Elite Gen 6 chips with upgrades for on-device agents, including dedicated Transformer acceleration; the article says the top variant can support on-device operation of a 30B-parameter MoE model.

Sep 24 · Seven university teams released an open research stack and base model for world-action models, combining video-based world modeling with robot action learning and testing it across simulation benchmarks and real robots.

Sep 23 · When the presidents of the United States and China meet in Washington, the world will be watching to see whether their two countries can make good on their agreement to work towards “constructive strategic stability”. In the sixth part of a series, Chong Ming Lee and Vincent Chow examine what’s behind the call for “pacing” by American AI giants – effectively a slowdown in development – and how the phenomenon is being viewed in China. After years of rapid development, leading US AI executives are…

Sep 23 · US President Donald Trump has sold shares worth tens of millions of US dollars in major tech companies, including Microsoft, Amazon and Meta Platforms in July, a move that may reveal some of his views on the sector, especially as competition with China intensifies. Microsoft topped the list of sales transactions, with six trades totalling up to US$31 million, according to filings disclosed by the US Office of Government Ethics on Tuesday. The data detailed Trump’s trading activity in July,…

Sep 23 · The 2026 World Artificial Intelligence Open Source Competition concluded its global finals and annual summit in Hangzhou on Sept. 23,… World Artificial Intelligence Open Source Competition Concludes in Hangzhou With Focus on AI Agents and Robotics comes via ChinaTechNews.com .

Sep 23 · A DeepSeek paper describes DSec, a platform coordinating function-call, container, microVM, and full-VM sandboxes with reinforcement-learning workloads; it reports capacity of about three million sandboxes per day.

Sep 23 · Baidu is expanding its overseas AI productivity business around Kooko, an agent with personalized memory and office-work capabilities; Baidu reports more than 10 million overseas users and customers in 197 countries and regions.

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A 2–1 D.C. Circuit panel declined to block the Pentagon’s supply-chain-risk designation of Anthropic, preserving its exclusion from military contracts for now. A separate California court order addressed a parallel designation; Anthropic says it disagrees and is weighing further review.

Anthropic is reportedly asking shareholders to approve special shares giving its seven co-founders 50.1% of the vote on most corporate matters after an IPO, provided at least three retain a minimum stake. The proposal has not yet been approved.

The AI-cloud and data-center company announced $3.36B in convertible financing: $2.36B at closing plus a $1B Nvidia commitment expected in November. The notes convert into shares at the IPO, funding Nscale’s AI-infrastructure expansion.

Anthropic has committed $11.6 billion over seven years for Akamai cloud infrastructure, the largest contract in Akamai’s history. The arrangement includes a warrant that could give Anthropic up to about 5% of Akamai, and further spending could raise the deal’s total value to roughly $20 billion.