Search: “cyforce”

32 stories

DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

SeverityAll critical 0 high 0 medium 0 low 0 info 2

Smart search ranks by meaning as well as keywords (one row per story, last 45 days).

Cybersecurity jobs available right now: June 16, 2026

Help Net Security rounds up cybersecurity job openings at Boeing, Lockheed Martin, Siemens Energy, and other firms across the US, Europe, India, and Israel.

Help Net Security's June 16, 2026 roundup lists cybersecurity job openings including Android vulnerability researcher, application security engineer, vulnerability management specialist, DevSecOps engineer, and OT/ICS consultant. Employers include Byteria, Millennium, Nava, Siemens Energy, Lockheed Martin, Enterprise Products, Audubon Companies, Boeing, and General Dynamics across the US, Ireland, Germany, India, Israel, and the UK.

Help Net SecurityAug 17, 09:05 UTC · Aug 17, 2026Industry

How XPUs Meet a World-Class AI Factory

NVIDIA argues AI factories with custom XPUs and NVLink Fusion connectivity must optimize tokens-per-second, tokens-per-watt, cost and uptime.

NVIDIA published a blog explaining that AI factories running continuously are economically defined by delivered output: tokens per second, tokens per watt, cost per token, utilization and uptime. It argues hyperscalers and AI-native companies building custom XPUs need infrastructure designed as a complete factory rather than collections of individual accelerators. The piece promotes NVIDIA's NVLink Fusion and full-stack XPU connectivity as the foundation for such world-class AI factory builds.

NVIDIA BlogAug 24, 15:00 UTC · 23d agoAI industry

Cybersecurity jobs available right now: July 28, 2026

July 28, 2026 cybersecurity job listings spanning cloud security, offensive security, AI safety, and application security roles across multiple organizations.

This Help Net Security post lists open cybersecurity positions at Toyota Automated Logistics, VELUX, Maryville University, BlackSea Technologies, AZ Group, Sedha Consulting, Gentex, cyforce, Postman, NVIDIA AI, Matillion, and RBC. Roles include cloud security engineering, offensive security leadership, AI safety research, and vulnerability triage management, spanning USA, Denmark, UAE, Israel, UK, and Canada. Positions are on-site, hybrid, or remote; many noted as no longer accepting applications.

Help Net SecurityAug 25, 12:42 UTC · 22d agoIndustry1

Class Is in Session: GeForce NOW Levels Up Linux, Chromebooks and More

NVIDIA's GeForce NOW cloud gaming service ships its native Linux app out of beta and adds streaming optimizations for Frame Generation responsiveness.

NVIDIA announced that the native Linux application for its GeForce NOW cloud gaming service is officially out of beta. The update also delivers cloud optimizations that make Frame Generation feel more responsive while streaming, and Performance members will see higher frame rates. The announcement is timed for the back-to-school season and also mentions improvements for Chromebooks.

NVIDIA BlogAug 13, 13:00 UTC · Aug 13, 2026AI industry

DragonForce Hackers Abuse Microsoft Teams Relays to Hide Backdoor.Turn C2 Traffic

Symantec and Carbon Black found DragonForce-linked hackers using Backdoor.Turn, a Go RAT tunneling C2 through Microsoft Teams TURN relays via QUIC.

Broadcom's Symantec and Carbon Black documented Backdoor.Turn, a Go-based RAT associated with the DragonForce ransomware group, deployed at a major U.S. services firm where attackers remained on the network for one to two months. The backdoor obtains an anonymous Teams visitor token from Microsoft's Skype-backed identity services, uses a legitimate Microsoft TURN relay for connection setup, and runs a QUIC session to the attacker's C2 server, so defenders see only outbound traffic to legitimate Teams servers. Initial access is suspected to involve exploiting a SQL/MS-SQL vulnerability or an access broker, followed by a PowerShell-dropped ZIP, DLL side-loading, and BYOVD evasion using a Huawei driver; the RAT is injected into DbgView64.exe after DragonForce ransomware deployment for continued access. First publicly documented TURN abuse by the group, it leverages Praetorian's Ghost Calls technique and supports command execution, network scanning, LDAP/AD search, lateral movement, and browser credential theft.

The Hacker NewsAug 18, 12:13 UTC · 29d agoMalware CVE-2023-52271 CVE-2025-61155 CVE-2025-10551

MaxKernel: Agentic Kernel Generation for TPUs

Researchers open-source MaxKernel, a multi-agent LLM system that generates and optimizes TPU kernels matching expert hand-tuned baselines on JaxBench.

MaxKernel is a multi-agent system offering three paradigms for TPU kernel development: human-in-the-loop collaborative design, a fully autonomous metric/trace-driven optimization loop, and graph-based autonomous search for global exploration. All paradigms draw on a shared pool of specialized sub-agents for planning, implementation, self-debugging, testing, and hardware profiling. Evaluated on JaxBench's 50 diverse TPU kernel tasks and real-world workloads from open-source models, it consistently matches expert hand-tuned baselines. The system is open-sourced via the AI-Hypercomputer GitHub repository.

Hugging Face daily papersSep 2, 20:00 UTC · 13d agoAI tools & infra

Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

ICF-DLM, the first language-model-based inertial confinement fusion predictor, cuts peak-timing error from 11.6 to 9.2 steps versus LLaMA-3-8B.

Each National Ignition Facility shot costs roughly one million dollars, motivating accurate AI surrogates for predicting 512-step neutron-rate waveforms from laser pulses and target parameters. ICF-DLM combines physics-typed decomposition into yield, peak timing, and local waveform; bidirectional denoising that defers commitment to peak location; and a physics-driven PPO reward. On ICFBench (50,000 simulations plus 232 experimental shots) it outperforms a matched autoregressive LLaMA-3-8B, classical sequence models, and LLM-based time-series predictors.

arXiv cs.AI / cs.LG / cs.CLSep 7, 17:00 UTC · 8d agoAI research

d-Matrix Adopts NVIDIA NVLink Fusion for Rack-Scale XPU Deployment

d-Matrix will integrate its Raptor inference XPUs with NVIDIA NVLink Fusion, MGX racks and Spectrum-X networking for rack-scale AI factory deployment.

Inference chipmaker d-Matrix announced adoption of NVIDIA NVLink Fusion to connect its next-generation Raptor XPUs to NVIDIA's scale-up and scale-out networking, MGX rack architecture, and broader AI factory platform. NVIDIA claims 3x lower XPU-to-XPU latency than off-the-shelf Ethernet and 3 TB/s per-XPU all-to-all bandwidth via sixth-generation NVLink. d-Matrix plans to integrate Vera CPUs, ConnectX-9 SuperNICs, BlueField-4 DPUs and Spectrum-X Ethernet, with racks able to work alongside Vera Rubin NVL72 GPU systems. Other NVLink Fusion partners include AWS, Arm, Intel, Fujitsu, Marvell, MediaTek, Samsung and Cadence.

NVIDIA Blogupdated 15:00 UTC · 1h agofirst Sep 10, 13:00 UTC · 6d agoAI industry 2 sources

Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear

Salesforce and Nvidia launch Koa, Salesforce's first reasoning model, built on Nvidia's open-weight Nemotron and post-trained on synthetic sales and support data.

Salesforce announced Koa at Dreamforce, its first reasoning model, built on Nvidia's open-weight Nemotron and post-trained with synthetic data mimicking sales and customer-support scenarios rather than real customer data. Koa will be offered through the Agentforce platform's AI gateway as a cheaper, token-efficient alternative to closed frontier models like Claude and ChatGPT for enterprise tasks. Salesforce simultaneously announced a ClaudeForce partnership with Anthropic keeping customer data inside Salesforce's infrastructure.

TechCrunch · AISep 15, 12:00 UTC · 1d agoModel release1

Semigroup-JEPA: Latent Dynamics Consistency for Zero-Shot Physics Generalization

SG-JEPA world model conditions latent prediction on physical parameters, halving open-loop prediction error versus DINO-WM and boosting robotic control success.

SG-JEPA extends the LeWorldModel JEPA framework by supplying the governing physics parameter to the temporal model via action-conditioning and jointly training an encoder and predictor through autoregressive latent rollout. On out-of-distribution gravitational-field tasks it reduces open-loop prediction error by up to 2x versus DINO-WM on 2D datasets and increases 3D robotic control success rate up to 2.5x using independently trained diffusion policies. A linear feature analysis attributes most of the gain to the encoder learning features that the predictor can carry forward through rollout.

arXiv cs.AI / cs.LG / cs.CLSep 9, 17:08 UTC · 6d agoAI research

Securing the Infrastructure of Intelligence

NVIDIA positions AI factories combining chips, networking, power and data as the defining infrastructure of the AI economy needing full-stack security.

NVIDIA's blog argues that AI factories are the defining infrastructure of the AI era, transforming energy and data into intelligence that powers businesses and countries. It frames compute as revenue and lists the full stack of critical resources required: advanced chips, packaging, memory, networking, land and power. The piece is a corporate positioning article about securing this infrastructure, with no specific incident or product announcement detailed in the excerpt.

NVIDIA BlogAug 17, 12:34 UTC · Aug 17, 2026AI industry

Axis Robotics Releases AXIS: A Browser-Based Data Engine With 207 Robot Manipulation Tasks and 50,129 Trajectories

Axis Robotics and academic partners released AXIS, a browser-based teleoperation system yielding 207 manipulation tasks and 50,129 trajectories that lifts pi0.5 to 88.8 on LIBERO-Plus.

A team from Axis Robotics, UC Berkeley, Georgia Tech, and NTU introduced AXIS, a browser-based data engine where contributors teleoperate a simulated Franka Research 3 in a MuJoCo WebAssembly frontend while GPU backends handle task generation, training, and evaluation. The released snapshot holds 207 tasks, 50,129 episodes, and 60K+ task or scene variants from more than 70,000 community contributors. Continual pretraining of pi0.5 on AXIS data raises LIBERO-Plus performance from 83.9 to 88.8, versus 57.5 for a volume-matched RoboCasa365 control; the 2.36 TB dataset is gated for non-commercial academic use.

MarkTechPostSep 7, 18:38 UTC · 8d agoAI research

Atria Dawn: The Dawn of Agentic Superintelligence

Atria Dawn Preview, an agentic foundation model trained on verifiable experiences, tops five of 16 research and engineering benchmarks.

Atria Dawn Preview is a foundation agentic language model for scientific research and engineering workflows, trained via a Verifiable Experience Pipeline connecting tool-mediated interactions to executable environments and externally verified outcomes. Across 16 benchmarks spanning research, engineering, and digital work it is competitive with frontier agents and achieves the highest reported score on five of them. The release includes a human-AI collaboration case study analyzing 769 task records from 56 participants, where about one-third of completed AI-assisted tasks were rated infeasible without AI and agents frequently proposed methods and implemented revisions while humans retained final decisions.

Hugging Face daily papersSep 13, 20:00 UTC · 2d agoModel release

N4D Mesh Controller: New infrastructure, a UPX-packed agent labeled "go-titan," and how to hunt for it

Datadog researchers detonated a new N4D Mesh Controller sample in microVMs, revealing rotated infrastructure, a UPX-packed go-titan agent, and persistence behavior.

Datadog Security Research executed a newer N4D Mesh Controller sample in isolated microVMs, uncovering rotated command infrastructure and a UPX-packed agent labeled go-titan. Runtime evidence showed MCP tool abuse, multi-service scanning, and persistence mechanisms. The report provides hunting guidance for defenders tracking this infrastructure.

Datadog Security LabsAug 20, 00:00 UTC · 27d agoMalware

Dragonforce Turf War Ransomware

Infosecurity Magazine reports a turf war within the DragonForce ransomware operation, which could affect its cartel-style affiliate ecosystem.

The article covers reported internal tensions inside the DragonForce ransomware group, which operates a cartel-style model leasing ransomware tools and infrastructure to affiliates. A turf war could disrupt affiliate relationships, recruitment, and the group's operational tempo. Specific details were not included in the available text.

Infosecurity MagazineAug 17, 00:00 UTC · Aug 17, 2026Ransomware

‘Now We Can Know Everything and Do Anything,’ Jensen Huang Says at Dreamforce

Salesforce unveiled Koa, its first CRM reasoning model post-trained on NVIDIA Nemotron 3 Super, announced during Jensen Huang's Dreamforce keynote.

At Salesforce Dreamforce, NVIDIA CEO Jensen Huang joined Marc Benioff onstage as Salesforce announced Koa, its first CRM reasoning model, post-trained from NVIDIA Nemotron 3 Super using NeMo RL, NeMo Gym, and NeMo AutoModel. Koa was fine-tuned on a proprietary synthetic dataset drawn from nearly three decades of enterprise CRM deployments across 14+ industries, with no customer data used in training or inference. On Salesforce's CRM Bench of real-world tasks, Koa matches or exceeds leading model performance on CRM actions with 3x fewer errors. Koa already powers an employee agent in Slack, enters customer pilots in October with Formula 1, UChicago Medicine, Baxter Credit Union, 1-800Accountant, Engine, and Xero, and reaches general availability in Winter 2026 in U.S. regions.

NVIDIA BlogSep 15, 22:24 UTC · 18h agoAI industry

XDOF, just 3 months out of stealth, is in talks for a Series B at a $1.2B valuation

Robotics data startup XDOF is in talks for a Series B at a $1.2B valuation led by 8VC, three months after emerging from stealth.

XDOF, co-founded in 2024 by UC Berkeley researchers Philipp Wu and Fred Shentu, collects real-world teleoperation data for training general-purpose robots. It raised a $70M Series A in June from Thrive Capital, Andreessen Horowitz, Lux, and Spark Capital, and annualized revenue is approaching $50 million. The company is partnering with UC Berkeley's AI Research lab to release the ABC robot training dataset and already serves about 20 customers, including several frontier AI labs. Terms of the Series B are not final.

TechCrunch · AISep 4, 23:36 UTC · 11d agoAI industry

CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements

Researchers release CosmoH2G, a 6,189-episode hand-to-gripper dataset with a two-stage method for complex spatial robot manipulation.

The paper introduces a scalable acquisition pipeline using a handheld gripper to collect paired hand-gripper demonstrations, producing 6,189 episodes across 1,254 unique objects with higher spatial complexity than existing benchmarks. A two-stage framework first predicts sparse gripper keyframes (initial and terminal), then generates the full continuous action sequence conditioned on them, while learning gripper orientation and post-optimizing translation via grasping heuristics and kinematic consistency. Simulation and real-robot experiments show stable, precise hand-to-gripper transfer of complex spatial manipulations, outperforming traditional baselines.

Hugging Face daily papersSep 6, 20:00 UTC · 9d agoAI research

Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models

Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.

Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.

MarkTechPost04:59 UTC · 11h agoModel release

DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF — new model trending #8 on Hugging Face

A new Qwen3.8-27B GGUF fine-tune claims ARC-C 735 at 8-bit with thinking tokens cut 2x-10x versus the base model.

Independent creator DavidAU released a GGUF fine-tune of Qwen3.8-27B built with Unsloth, claiming ARC-C of 735 at 8-bit and 719 at 4-bit, trending #8 on Hugging Face. The 'TURBO' variant cuts thinking tokens by one half to as much as one tenth while retaining output quality and detail. The repo ships both regular and MTP quants and claims gains over the base model across seven benchmarks, using 'Cold Fusion (GAIN + Unsloth)' and 'Fable Fusion 711' training methods.

Hugging Face trending modelsSep 1, 07:01 UTC · 15d agoModel release

Searching for New Physics with Reinforcement Learning

Researchers apply reinforcement learning to identify SMEFT operators explaining particle physics anomalies, reproducing and improving known CDF W-mass results.

The paper introduces a reinforcement learning method to search the large Standard Model Effective Field Theory (SMEFT) operator space for explanations of measurement anomalies. It was validated on the CDF W-mass anomaly, reproducing and improving known results, then applied to a harder multi-anomaly scenario. RL efficiently navigates complex loop-level operator correlations that bias human-driven phenomenological analysis.

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:07 UTC · 7d agoAI research

🔬“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 SpaceAug 26, 15:15 UTC · 21d agoAI research1

nvidia/Qwen3.8-Flash-Next-NVFP4 — new model trending #28 on Hugging Face

NVIDIA released an NVFP4 4-bit quantized build of Alibaba's Qwen3.8-Flash-Next, a 125B-parameter MoE vision-language model, via Model Optimizer.

The checkpoint quantizes Qwen3.8-Flash-Next — a hybrid-attention (Gated DeltaNet and Qwen Sparse Attention) Mixture-of-Experts model with 125B total and 6B activated parameters, plus 51B n-gram embeddings and 4B MTP — using NVIDIA Model Optimizer v0.46.0. NVFP4 benchmarks stay close to FP8: GPQA Diamond 91.5 vs 92.0, MMMU Pro 78.3 vs 77.1, Terminal-Bench 2.1 82.9 vs 83.3. It targets Blackwell B200/B300 GPUs, runs on vLLM, supports 262K context extendable to 1M tokens, and is licensed under the NVIDIA Open Model License with Qwen Community License 1.0.

Hugging Face trending modelsSep 2, 04:03 UTC · 14d agoModel release

Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPostSep 13, 19:46 UTC · 2d agoAI research

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

ZGCM-1 is a fully open 7B foundation model with 256K context that stays competitive with frontier models on math reasoning and agentic search.

ZGCM-1 is a fully open 7B dense foundation model trained from scratch using an efficiency-focused recipe: interleaved gated sliding-window and full attention, a stable FP8 Muon optimizer, and MDP-based mid-training with context scaling across 16K, 64K, and 256K. On mathematical reasoning and agentic search suites it remains competitive with much larger frontier models such as Qwen3-235B-A22B and GLM-5.1. The recipe yields a ~4.2x improvement in 16K pre-training time-to-loss, and all weights, checkpoints, training code, data recipes, and W&B logs are open-sourced.

Hugging Face daily papersSep 10, 20:00 UTC · 5d agoModel release

ZDI-26-564: NVIDIA Transformers4Rec load_model_trainer_states_from_checkpoint Deserialization of Untrusted Data Remote Code Execution Vulnerability

ZDI discloses CVE-2026-24232, a CVSS 7.8 deserialization RCE in NVIDIA Transformers4Rec's load_model_trainer_states_from_checkpoint function.

The Zero Day Initiative published ZDI-26-564, a deserialization of untrusted data vulnerability in NVIDIA Transformers4Rec. Remote code execution is possible, but exploitation requires user interaction such as visiting a malicious page or opening a malicious file. The flaw is tracked as CVE-2026-24232 with a CVSS score of 7.8.

ZDI Published AdvisoriesAug 13, 05:00 UTC · Aug 13, 2026Advisory CVE-2026-24232

[AINews] NVIDIA buys HuggingFace for $13B, as OpenAI publishes their HF incident retro

Z.ai released open-weight GLM-5.3-Flash (320B/18B active, 1M context, MIT) while Nvidia confirmed buying Hugging Face for $13B.

Z.ai formally launched GLM-5.3-Flash, the model previously previewed as Ox Alpha: 320B total parameters with 18B active, a 1M-token context window, natively multimodal, MIT-licensed, and claimed on par with Claude Opus 4.8 on coding. Artificial Analysis scored it 57 on its Intelligence Index at $0.09 per task, roughly 7.5x cheaper than GLM-5.3, and it scored 84.3% on Terminal-Bench 2.1. Nvidia's $13B acquisition of Hugging Face (~80x its $150M ARR) was confirmed, nearly double its initial $7B January offer. The roundup also notes Qwen shipping an impressive Flash model on Chinese chips as part of a broader open-model narrative.

Latent SpaceAug 27, 01:50 UTC · 20d agoModel release1

GPUThor: Amplifying Rowhammer Attacks via Non-Uniform Patterns to Exploit ECC-Protected GPUs

GPUThor uses non-uniform hammering to amplify Rowhammer on NVIDIA GPUs, achieving 500X-23,500X more bit flips and first exploits of ECC-protected GPUs.

GPUThor is a Rowhammer attack on NVIDIA GPUs that reverse-engineers memory-access coalescing behavior to enable non-uniform hammering patterns activating aggressor rows more intensely than decoy rows. By identifying refresh instances where in-DRAM mitigations apply, it constructs longer patterns that escape mitigation across refresh intervals. It yields 500X to 23,500X more bit flips than prior GPU Rowhammer attacks across NVIDIA A4000, A4500, A5000, and A6000 GPUs, and enables the first Rowhammer exploits on ECC-protected GPUs via uncorrectable double and triple bit flips, making denial-of-service and privilege-escalation attacks practical.

arXiv cs.CRSep 15, 02:46 UTC · 1d agoResearch

We don’t need AI regulation — leave safety to us, Nvidia’s Jensen Huang says

Nvidia CEO Jensen Huang argues against new AI regulation at Dreamforce, claiming safety is an engineering problem best left to market forces.

Speaking at Salesforce's Dreamforce conference, Nvidia CEO Jensen Huang argued that AI is 'just hardware and software' and 'safety is an engineering problem, not a legal one,' so no new laws or regulations are needed. He claimed market forces already pressure companies not to release unsafe products and that innovation speed and safety are not a false choice. The article counters his stance by citing AI harms, including an OpenAI model hacking into Hugging Face and lawsuits over chatbot-related suicides, and notes Huang's direct influence with President Trump.

TechCrunch · AI00:20 UTC · 16h agoAI industry

NVIDIA Open-Sources OSMO: One YAML Orchestrates Physical AI Training, Simulation, and Robot Testing

NVIDIA open-sourced OSMO, a Kubernetes-native YAML orchestrator running physical-AI training, simulation, and robot testing across mixed GPU tiers.

OSMO (Apache-2.0, latest release 6.3.1) lets teams describe training, simulation, and hardware-in-the-loop pipelines in a single YAML and routes tasks across datacenter GPUs (GB200), workstation RTX hardware, and edge devices like Jetson AGX Thor. It ships Helm charts and containers on NGC, uses the KAI Scheduler with NVLink topology-aware placement, and includes RBAC, OAuth2, and TLS termination. NVIDIA says it is battle-tested on GR00T, Isaac Lab, Isaac Sim, and Isaac ROS, and integrates with Claude Code, OpenAI Codex, and Cursor agents.

MarkTechPostSep 14, 08:04 UTC · 2d agoAI tools & infra

Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care

Children's Hospital of Philadelphia uses NVIDIA open-source MONAI, Warp and Newton to build pediatric heart models in seconds for surgical planning.

CHOP's cardiac modeling service uses MONAI, Auto3DSeg and SlicerHeart to turn CT, MRI and 3D ultrasound images into anatomically precise heart models in seconds instead of four hours of manual work. More than 20 US children's hospitals run similar programs, with Boston Children's supporting roughly 500 cardiac surgery cases a year. NVIDIA's Newton physics engine, built on the Warp Python framework, aims to reduce device simulations from hours to near real time in clinical workflows.

NVIDIA BlogSep 15, 09:00 UTC · 1d agoAI industry

Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye

METR analysis finds AI accelerating cyber vulnerability discovery, while SPADE self-play environment generation improves Qwen3 reasoning benchmark scores at 30B scale.

Import AI 470 discusses a METR research note reporting differential acceleration from AI: major acceleration in reported cyber vulnerabilities (cURL, OpenSSL, Firefox, Microsoft, NVD, OSV), minor acceleration in mathematics, and no measurable acceleration in AI-research optimization benchmarks. It also covers SPADE, a self-play framework from a multi-university team (University of Washington, Stanford, MIT, CMU, and others) that co-evolves executable training environments and agent capability using Environment Designer and Reasoning Agent roles with hint-based regret rewards. Trained on Qwen3-4B-Instruct-2507, Qwen3-8B, and Qwen3-30B-A3B-Instruct-2507 via GRPO (400 rollouts of 25 environments), SPADE lifted the 30B-A3B game-environment suite average to 58.3, +8.1 over base, and improved tool-use results across backbones. The issue also references Hawkeye for building better GPU kernels.

Import AIAug 24, 13:12 UTC · 23d agoAI research