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Introducing WeatherNext 3, our most advanced and accurate global weather AI model

Google DeepMind launches WeatherNext 3, an AI weather model delivering hourly 5-km forecasts from live satellite data, now integrated across Google products.

WeatherNext 3 ingests live geostationary satellite mosaics and station observations through a Functional Generative Network (FGN) mesh transformer, producing hourly forecasts at 5-km surface resolution versus WeatherNext 2's 25-km, 6-hour grid. Independent live evaluations by Brightband rate it the most accurate global weather model to date. It adds renewable-energy variables such as 100-meter turbine-height wind speeds and solar radiation, and is integrated across Search, Gemini, Maps, Google Maps Platform, and Cloud.

Google DeepMind · 12d agoModel release

Competence-Gated Pooling of Language Models and Priors for Event Forecasting

Paper proposes a competence gate pooling language model forecasts with external priors, improving Brier score from 0.0771 to 0.0732 across 2,357 binary questions.

The paper defines a language model's relative competence as its marginal value beyond an available external forecast, and derives conditions under Brier loss where model disagreement improves that forecast. A competence gate estimates domain-level source weights from resolved outcomes, shrinks uncertain estimates toward a global weight, and recalibrates the pooled forecast. Across 2,357 resolved binary questions and five language models, it improves the external baseline from 0.0771 to 0.0732 Brier and beats global forecast combinations, though it defers to the market on ForecastBench. Across four Qwen models, verbal confidence failed to identify when the model outperformed the external forecast, while outcome-estimated competence supported better abstention.

Hugging Face daily papers · 6d agoAI research

Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research released TimesFM-3, a 330M-parameter multivariate time series forecasting model that tops Gift-Eval, FEV-Bench, and Time benchmarks and is on Hugging Face.

Google Research released TimesFM-3, a 330-million-parameter Transformer-based time series forecasting model trained on more than one trillion real and synthetic data points. It works zero-shot and adds multivariate support, ingesting related series, historical-only covariates, and known future events such as discount schedules and weather forecasts, while filling all future time steps in a single one-shot pass. Google reports first place among pretrained forecasting models on Gift-Eval, FEV-Bench, and Time, ahead of Amazon's Chronos-2, the Toto-2.0 family, and its own TimesFM-2.5. Weights are available on GitHub and Hugging Face, with BigQuery integration planned in the coming weeks.

The Decoder · 4d agoModel release2

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK

University of Manchester retrained NVIDIA Earth-2 CorrDiff and StormCast on Isambard-AI to forecast UK air pollution at 2-3 km resolution.

University of Manchester researchers led by professor David Topping adapted NVIDIA's Earth-2 generative AI frameworks to forecast air pollution across the UK. Earth-2 CorrDiff was retrained in two days on a single eight-GPU node of Isambard-AI (5,448 GH200 Grace Hopper Superchips, 21 exaflops) using a year of hourly simulated pollution data, producing a UK-wide model at 2-3 square kilometer resolution. The team added Earth-2 StormCast for time-dependent forecasts that ingest real air quality observations, and demonstrated the workflow runs on the DGX Spark desktop AI system. Open-source training data and workflows are planned so other countries and cities can build similar pollution models.

NVIDIA Blog · 5h agoAI industry

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a generative time-aware transformer trained on 559 million MIMIC clinical events to model and forecast patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer designed to represent and forecast the full multimodal patient journey across medical images, time-series signals, categorical events, and clinical text. It was trained on over 559 million clinical events from 431,000 hospital visits covering 299,000 patients in the MIMIC dataset family. The architecture combines bidirectional time integration with a variational latent space to capture continuous patient state evolution and clinical stochasticity. NOAH supports autoregressive forecasting with time control, zero-shot classification, and counterfactual intervention simulation, with evaluations on 15 ICD chapters, 29 comorbidities, and time-to-event prediction.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research2

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a time-aware generative transformer trained on 559 million MIMIC clinical events to forecast multimodal patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer trained on over 559 million clinical events from 431,000 hospital visits by 299,000 patients across the MIMIC dataset family. It uses bidirectional time integration and a variational latent space to model the stochastic evolution of patient states, natively processing medical images, time-series signals, categorical events, and structured or unstructured clinical records. The model supports autoregressive forecasting with optional time control, zero-shot classification, and counterfactual intervention simulation, with strong probing performance across clinical outcomes, 15 ICD chapters, and 29 comorbidities.

Hugging Face daily papers · 8d agoAI research1

Anthropic built an economic model that frames its CEO's bleakest job forecasts as an outlier scenario

Anthropic published an economic model with three US economic scenarios through 2030, framing CEO Dario Amodei's bleakest job-loss forecasts as the outlier outcome.

Anthropic released an economic model outlining three scenarios for AI's impact on the US economy through 2030. The modest scenario resembles the internet's impact with stable wages, the middle scenario doubles growth while knowledge worker wages stagnate, and the extreme scenario projects 17.9% knowledge worker unemployment with labor's GDP share falling from 60% to 45%. CEO Dario Amodei's May 2025 warning of up to half of entry-level office jobs vanishing and 10-20% unemployment aligns with the extreme scenario, which the model treats as the least likely outcome.

The Decoder · 6d agoAI industry1

Google’s AI weather model now uses more raw satellite data

Google launched WeatherNext 3, an AI weather model using raw satellite data that beats ECMWF and now powers Search, Gemini, and Maps.

Google released WeatherNext 3, an AI weather forecasting model that incorporates physical surface information (land/ocean type and elevation) to improve surface temperature and dewpoint calculations, improving point location temperature accuracy by up to 30 percent. Its white paper reports roughly 5 percent better upper-atmosphere accuracy than WeatherNext 2, equating to about six additional hours of forecast lead time, outperforming the ECMWF AI model on these metrics. The model now supplies forecast information across Google Search, Gemini, and Maps, though the paper notes unexplained short-lead degraded results and grid-shaped artifacts in some predictions.

Ars Technica · AI · 7d agoModel release

Building AI to accelerate science and improve lives

Google highlights AI-for-science advances: AlphaGenome Atlas mapping 9 billion genetic variants, WeatherNext 3 weather model, and global health AI tools.

Google detailed AI advances across science and health, including AlphaGenome Atlas, which mapped all 9 billion possible single-letter genetic changes in the human genome and was made openly available. WeatherNext 3 delivers 50% more accurate precipitation forecasts a day or more ahead and is already in products. AlphaFold is used by 4 million researchers in 190 countries, TB chest X-ray screening has processed 25,000+ scans across six nations, and the diabetic retinopathy model has supported 1.15 million screenings. Google also released its AI & Economy ATLAS global usage insights.

Google · AI · 18h agoAI industry

One resignation turned the embers of AI fear into a wildfire

Interconnects argues a frontier-lab researcher's safety resignation went viral via media coordination, reigniting AI existential-risk discourse.

The essay analyzes why researcher Jacob Coxon's resignation over AI safety risks went viral, aided by a Wall Street Journal exclusive, advocacy-group amplification, and Daniel Kokotajlo's same-day Joe Rogan appearance. It notes Evan Hubinger's >10% extinction-risk figure and criticizes existential-risk discourse for conflating very different meanings of the term. The author assigns near-zero probability to complete extinction but argues concrete risks such as cyberattacks on critical infrastructure and bio-risks merit debate. It also rejects recursive self-improvement forecasts, proposing 'lossy self-improvement' where models excel at math and code but remain limited elsewhere.

Interconnects · 5d agoAI safety & security

From ‘High/Medium/Low’ to Dollars: Making Cyber Risk Legible to Your CFO

Cyble argues security teams should express cyber risk in financial terms for CFOs instead of high/medium/low ratings, citing its 2025 threat forecast results.

Cyble published guidance on cyber risk quantification, arguing qualitative high/medium/low ratings fail to convey financial exposure to executives. The piece notes that over 80% of its 2025 threat predictions, including AI-driven ransomware and supply-chain attacks, materialized as anticipated.

Cyble · 22d agoIndustry

What building an AI-native finance function taught me

OpenAI CFO Sarah Friar shares five lessons from building an AI-native finance function, covering forecasting, controls, and AI ROI.

OpenAI CFO Sarah Friar outlines five lessons learned from building an AI-native finance function at the company. Topics include automated forecasting, stronger financial controls, and measuring AI return on investment. The piece is a first-person account of enterprise AI adoption within a finance organization rather than a product or research announcement.

OpenAI News · Aug 10, 2026AI industry

A Ranking Approach for Measuring Calibration

Researchers propose rankECE, a ranking-based calibration error measure with theoretical guarantees that outperforms binned ECE approximations.

The paper introduces rankECE, an alternative to Expected Calibration Error (ECE) that measures miscalibration by comparing points with neighboring predicted-probability values. It addresses the impossibility of estimating ECE with guaranteed accuracy in assumption-free settings. Theoretical guarantees and empirical results establish rankECE as a better proxy for ECE than the binned approximations most commonly used in practice.

arXiv cs.AI / cs.LG / cs.CL · 4d agoAI research1

Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

Systematic review of 66 studies finds LLMs for HVAC operations are mostly research-stage, with no ready-now deployment and only four pilot-level studies.

A critical review of 66 peer-reviewed studies from 2023 to March 2026 examines LLMs for HVAC operations in building energy systems. Only four studies reach pilot-level evidence, none reports sustained operational deployment, and 63 of 66 are research-only. Conventional ML, MPC, and RL remain dominant for high-frequency control and short-horizon forecasting, and the evidence supports LLMs primarily as semantic and workflow layers rather than autonomous controllers.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research

Facilitating AI integration with simplicity at scale

Jabil's SAP IT director says simplifying integration across 100+ sites in 30+ countries with SAP Integration Suite created the data backbone for AI.

In an MIT Technology Review Business Lab podcast produced in partnership with SAP, Jabil SAP IT director Harish Manohar described consolidating fragmented tools across more than 100 sites in over 30 countries using SAP Integration Suite. The manufacturer, with 140,000-plus employees and more than 400 top-brand customers, says a standardized data backbone enables real-time supply chain visibility and is a prerequisite for scaling predictive, AI-driven planning and forecasting. The company frames simplification-first modernization as a competitive advantage tied to measurable business value and operational resilience.

MIT Technology Review · AI · 13d agoAI industry1

🔬“We have foundation models for language, not for physics” — Anima Anandkumar, Bren Professor of Computing

Caltech professor Anima Anandkumar discusses Neural Operators and FourCastNet for physics modeling, arguing inductive biases beat pure token scaling.

Anima Anandkumar, Bren Professor at Caltech and co-founder of Accelerated Understanding, describes Fourier Neural Operators that learn in frequency and spherical-harmonic domains to model weather, fusion, and fluid or heat flow. Her team built FourCastNet 3, a global weather model competitive with physics-based simulations that runs on consumer-grade GPUs. She also introduced TorchLean, a framework for writing PyTorch-style networks inside the Lean proof assistant for formal verification, and was appointed to the United Nations Scientific Advisory Board. She argues physical domains resist scaling due to tiny datasets and context lengths in the hundreds of billions, so progress comes from built-in structure and physical priors.

Latent Space · 20d agoAI research1

US data centers could consume more natural gas than Germany and Japan combined by 2035

BloombergNEF projects US data centers will consume about 18 billion cubic feet of natural gas daily by 2035, exceeding Germany and Japan combined.

A new BloombergNEF report forecasts US data centers will consume roughly 18 billion cubic feet of natural gas per day by 2035, nearly double the estimate from nine months ago. On-site gas plants planned by Meta, Microsoft, Google, and Amazon would use 2.9-3.4 billion cubic feet per day, while grid-connected data centers drive an additional 15 billion cubic feet per day of power-sector gas demand. The added demand would generate about 1 million metric tons of extra greenhouse gas pollution daily, roughly 12% of current US emissions.

TechCrunch · AI · 15h agoAI industry

Meta expands subscription push with new AI-focused plans

Meta launched Meta One subscriptions ($7.99–$499/month) bundling expanded Muse AI image and video generation across Facebook, Instagram, and WhatsApp.

Meta introduced Meta One with consumer Core ($7.99/mo) and Premium ($19.99/mo) tiers plus business plans ranging from Essential ($14.99/mo) to Max ($499/mo). Subscriptions unlock expanded Muse Image, Muse Video, Restyle editing, and Meta Business Agent usage, following Meta's $14.3B investment in Scale AI. Appfigures data shows Instagram's daily subscription revenue averaging $1.2M and Facebook's $528K after the March Plus-tier launches, up 475% and 143% respectively. BNP Paribas forecasts $13.5B added revenue by 2028; Truist estimates $20B by 2030.

TechCrunch · AI · 17h agoAI industry

How much of F-Droid is LLM generated?

A FOSS maintainer manually graded 102 F-Droid apps from the September 12, 2026 update batch, finding many show signs of LLM-generated code.

A student and FOSS app maintainer reviewed 102 apps pushed to F-Droid on September 12, 2026, assigning each a three-tier rating for likelihood of LLM-authored code (mostly AI >50%, hard to say/mostly human, no signs of AI). The heuristic relies on commit aesthetics, README and branding style, and the presence of agentic infrastructure like Claude Code or Codex, which automatically places an app in the 'mostly AI' tier. Example ratings include Amber (Nostr event signer) as mostly AI, and Aria for Misskey as showing no AI signs. The author stresses reliable detection of LLM-generated code from text alone is impossible, so ratings are approximate.

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent Space · 1d agoAI safety & security

Defense Cyber Spending Set to Surge Amid Rising Attacks on Military Systems

MarketsandMarkets projects the cyber warfare market to nearly double from $14.99bn in 2026 to $28.75bn by 2031, driven by attacks on military systems.

A MarketsandMarkets report projects the global cyber warfare market will grow from $14.99bn in 2026 to $28.75bn by 2031. Growth is driven by rising attacks on military networks, reliance on connected platforms and cloud command-and-control systems, and Western investment in offensive cyber capabilities. Europe is projected to hold the largest market share, supported by NATO's shared cyber capabilities and joint exercises. Cloud-based security is expected to be the fastest-growing market segment.

Infosecurity Magazine · 1d agoIndustry

Omni-Streaming Thinking

Omni-Streaming Thinking fixes premature cross-modal commitment in streaming omni-modal models via pending claims verified against modality-specific evidence, beating baselines by over 10%.

The paper identifies 'premature cross-modal commitment', where streaming models keep relaying early visual interpretations even after audio contradicts them. OST generates evidence-linked pending claims with future verification intervals, stores audio and visual evidence separately, and refutes claims when contradictory evidence appears. Built on a frozen Qwen3-Omni-30B-A3B-Instruct backbone with lightweight adaptation, it outperforms open baselines by more than 10% relative on five streaming and audio-visual benchmarks. On the new OST-DiagBench it reaches d-prime 2.95 versus at most 1.38 for open baselines, while reducing vision-induced auditory hallucinations.

Hugging Face daily papers · 2d agoAI research1

Top 10 Best CNAPP (Cloud-Native Application Protection) Platforms in 2026

GBHackers ranks 10 CNAPP platforms for 2026, naming Wiz, Prisma Cloud, and Microsoft Defender for Cloud as category leaders.

The guide describes CNAPP as the umbrella combining CSPM, CWPP, CIEM, and DSPM, arguing that cross-pillar correlation of attack paths is the platform's core value. Wiz is ranked best for graph-based correlation, Prisma Cloud for the broadest module set, and Microsoft Defender for Cloud for Azure economics. It also cites Google's approximately $32 billion agreement to acquire Wiz, announced in March 2025, as buyer leverage and a reason to seek roadmap and neutrality protections in multi-year contracts.

Cyber Security News · 5d agoIndustry1

Slack can now vibe-code interactive charts and reports inside chats

Slack launched Slackforce Surfaces, letting Slackbot build interactive dashboards, reports, and microsites directly inside chat channels.

Slackforce Surfaces uses AI to gather context from conversations and connected apps such as Google Drive and Salesforce to generate shareable interactive reports, polls, dashboards, and presentations. Surfaces can be pinned to channels where colleagues can view, interact, and comment. The feature is available to all customers, including free users, with Slackbot enabled, and live data support starts in October.

The Verge · AI · 5d agoAI industry

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

Researchers release Explainability Assistant, an open-source conversational XAI tool using LLM function calling, lifting intent-parsing accuracy from 76.8% to 94%.

The paper introduces the Explainability Assistant, an open-source conversational XAI system for interpreting energy consumption forecasting models such as genetic-programming symbolic regressors. It uses LLM function calling instead of rigid custom grammars, achieving 94% intent-parsing accuracy versus 76.8% for prior work TalkToModel, and adapts to different ML problem types without task-specific fine-tuning. Comparative evaluation with energy domain specialists against a traditional XAI dashboard showed improved usability, with all experts preferring the conversational interface.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research1

Will AI kill us all within the next decade?

Anthropic alignment lead Evan Hubinger says he personally estimates a greater than 10% chance AI could kill all humans within the next decade.

A Wall Street Journal report says concerns are rising inside AI labs that competition is pushing companies toward self-improving models that could spiral out of human control. Anthropic's Alignment Science lead Evan Hubinger publicly endorsed researcher Jacob Coxon's warning, giving a personal estimate of a greater than 10% chance of AI causing human extinction within a decade, driven by recursive self-improvement. Hubinger described the risk from current models as low, focusing his concern on future systems with far greater autonomy. The piece argues for safeguards such as independent testing, limits on high-risk autonomous uses, transparency, and accountability.

Malwarebytes Labs · 5d agoAI safety & security

The 12 Best Managed XDR Services, Compared and Priced

A comparison of twelve managed XDR providers covering pricing models, telemetry breadth, and distinguishing genuine MXDR from rebranded MDR services.

The article compares twelve managed XDR providers including Bitdefender, CrowdStrike, Palo Alto Unit 42, Trend Micro, Fortinet, Secureworks Taegis, Stellar Cyber, Ontinue, and ReliaQuest, highlighting pricing models and telemetry breadth. It explains that genuine MXDR must actively monitor identity, cloud, and email telemetry rather than merely ingest it, and typically costs 30-60% more than endpoint-only MDR. It also notes Sophos completed its approximately $859 million acquisition of Secureworks in February 2025.

GBHackers · 7d agoIndustry 3 sources1

Meta FAIR Introduces AI Research Preference Models (RPMs): Ranking ML Experiments Before Spending GPU Hours

Meta FAIR, Oxford and UCL introduce Research Preference Models that rank unexecuted ML experiments, lifting AIRS-Bench scores from 0.684 to 0.729 and cutting compute ~1.6×.

Researchers from Meta FAIR, Oxford, and UCL introduce Research Preference Models (RPMs), which use frozen pretrained LLMs (Qwen3.6-27B backbone, no fine-tuning) to rank unexecuted experiment candidates and execute only the winner of a pairwise knockout tournament. Two variants shipped: an inference-only LLM-as-a-judge and an agentic variant that runs small pilot experiments in an H200 sandbox. On AIRS-Bench (20 tasks, 24 hours on one H200, 10 seeds), scores rise from 0.684 (random) to 0.711 and 0.729 versus a 0.748 validation oracle, and both variants reach the baseline's 24-hour score in roughly 15 hours. The team reports new SOTA on WinoGrande (94.1% with Agentic RPM) and SVAMP (95.7% with inference-only).

MarkTechPost · 9d agoAI research

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

Cadence pairs Google's 330M-parameter TimesFM-3 foundation model with adaptive arithmetic coding, gaining 13-28% on 2026 demand series over classical predictors.

Cadence is an error-bounded lossy compressor for numeric time series combining the 330M-parameter Google TimesFM-3 foundation model with an adaptive arithmetic coder, guaranteeing a per-sample error bound. On 49 EIA-930 balancing-authority demand series from 2026 it gains 13.3% over the best of six classical predictors and 28.3% on 50 MTA ridership series, winning all 297 series-tolerance pairs with a 21.4% median gain. The paper also reports negative results, including that foundation models add negligible value for lossless coding and that PyTorch predictions are not bit-identical across batch sizes.

Hugging Face daily papers · 11d agoAI research1

Vali Cyber ZeroLock 5 brings MFA to the hypervisor command line

Vali Cyber released ZeroLock 5 adding CLI-MFA to protect VMware ESX and Linux hypervisors from insider threats and stolen credentials.

ZeroLock 5 introduces CLI-MFA, requiring time-based one-time passwords for file access, program execution, and network operations at the hypervisor command line on ESX and Linux hosts. The release targets ransomware and nation-state actor pivots to virtualization infrastructure, exemplified by ShinyHunters' shinysp1d3r RaaS platform that encrypts VMware ESX environments using stolen credentials and SSH keys. It adds remotely deployable collectors, reusable multi-site deployment blueprints, SIEM forwarding presets, and support for VCF and ESX 6.7+.

Help Net Security · 14d agoTools

The latest AI news we announced in August 2026

Google's August 2026 AI recap includes launches of Gemini 3.7 Flash, Gemini 3.5 Transcribe, and the Pixel 11 series, plus 1 billion Gemini users.

Google's monthly recap covers the Gemini 3.7 Flash workhorse model for coding and agents, released three weeks after 3.6 Flash at half its per-million-token cost, and the Gemini app surpassing 1 billion monthly users. The Pixel 11 series launched with the Tensor G6 chip running Gemini Nano, alongside Gemini 3.5 Transcribe for real-time speech-to-text and Gemini Omni 1.1 Flash for studio-quality video generation. Other announcements include a free year of Google AI for college students, Gemma's 1 billion downloads, and AI weather forecasts for aviation contrail reduction.

Google · AI · 14d agoAI industry