ZeroHour
DashboardNewsCVEsExploitsIncidentsAIBriefAnalyticsEntitiesWatchlistIOCsAsk the feedSourcesFeeds & APIKiosk mode

Search: “Montpellier Laboratory of Computer Science, Robotics, and Microelectronics”

30 stories

Searchkeywordsmart
DomainAllCyberAIWindow24h3d7d30dAllIn the wildImportant onlyShow duplicates
CategoryAllAI industry 1
SeverityAllcritical 0high 0medium 0low 0info 1

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

Discovery Foundation Models: Toward Open-Ended Discovery Intelligence

Paper defines Discovery Foundation Models with seven coupled capabilities for open-ended discovery, demonstrated via Zetema and GALILEO systems.

The paper formulates Discovery Foundation Models (DFMs) as general-purpose model systems for open-ended discovery, supporting seven coupled capabilities spanning problem discovery, formulation, representation construction, hypothesis formation, intervention, evidence-grounded revision, and continual improvement. It instantiates the framework with Zetema, which couples explicit research-state dynamics, verification and experimental gating, and cross-task Discovery Skill evolution. The framework is grounded with GALILEO, a real therapeutic-discovery system combining dry-lab reasoning with robotic wet-lab experimentation in a closed physical discovery loop; code is released on GitHub.

Hugging Face daily papersupdated · 1d agofirst · 2d agoAI research 2 sources

Askeal, the AI cybersecurity assistant that gives verifiable, expert-backed answers

AI security startup Askeal launches with $1.1 million pre-seed, pairing generative AI with 270+ vetted cybersecurity experts for verifiable answers.

Askeal, cofounded in August 2025 by Roxane Suau, launched an AI cybersecurity assistant that combines generative AI with a vetted community of more than 270 expert contributors and 178 public sources, backed by a $1.1 million pre-seed round. The tool answers natural-language security questions with evidence-backed, verifiable assessments, supporting CVE remediation guidance, URL, domain and hash lookups, and log analysis with IOC extraction. Its beta opened in February 2026, reaching 500 testers across 69 countries in two and a half months; the product is currently free, with paid plans and contributor revenue share planned. Its neuro-symbolic technology was developed with the Montpellier Laboratory of Computer Science, Robotics, and Microelectronics.

Help Net Security · 15d agoAI industry

Researchers Use Claude to Port Pre-Auth RCE Exploit From One PLC Model to Another

Forescout used Anthropic's Claude to port a working pre-auth RCE exploit for CVE-2021-31886 between WAGO PLCs, executing ARM shellcode on live hardware.

Forescout Vedere Labs used Claude interactively to port an RCE exploit for CVE-2021-31886, a CVSS 9.8 stack buffer overflow in the Nucleus FTP server's USER command, from a WAGO 750-852 to a WAGO 750-831 PLC, running attacker-supplied ARM shellcode. The final RCE stage cost $535.74 in API usage over 8 hours 32 minutes, and a follow-up attempt to build a C2 implant permanently bricked the device. CERT@VDE lists many Nucleus V1-based WAGO models as vulnerable with no updates available; Siemens plans no Nucleus NET remediation. The work follows a joint NSA/CISA/FBI/DOE/EPA advisory warning of AI-generated exploitation scripts targeting internet-exposed Siemens S7 PLCs.

The Hacker News · 14d agoResearchCVE-2021-318862

IntentFuzz: A Protocol-Aware Fuzzer for Automated Invariant Violation Detection in Intent-Based Cross-Chain Bridges

IntentFuzz protocol-aware fuzzer recovers bridge structure from unannotated Solidity and confirmed 22 invariant violations across 24 real-world deployments.

IntentFuzz formalizes a taxonomy separating invariant violations from settlement exposures in intent-based cross-chain bridges, then recovers a bridge's intent structure and deposit/fill function roles from unannotated Solidity source. It classified deposit and fill functions with 100% recall and 82% combined precision, and achieved 100% recall and precision on 23 planted-bug mutants. Across 24 real-world deployments it confirmed 17 genuine invariant violations with heuristic-only input generation, rising to 22 with its LLM-assisted tier, spanning eight vulnerable GitHub repositories with findings reproducible against public deployed bytecode.

arXiv cs.CR · 5d agoResearch1

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

OpenWAM releases an open modular stack for world-action model pretraining, plus OpenWAM-alpha trained on about 6,400 hours of egocentric and robot data.

OpenWAM is an open research stack that factorizes World-Action Model pretraining into composable infrastructure, study, and model components with unified training, inference, and evaluation. Controlled experiments distill three principles on knowledge inheritance, world-action synergy, and out-of-domain generalization gains from embodied co-training. The resulting OpenWAM-alpha, pretrained on roughly 6,400 hours of egocentric human and robot data, achieves top-tier results across eight simulation benchmarks and real-robot tests spanning single-arm, bimanual, and dexterous embodiments. The full stack, including infrastructure, evaluation protocols, pretrained models, and data recipes, is released openly.

Hugging Face daily papers · 9d agoAI research

$536 and 8 Hours: AI Learns to Attack a Different PLC

Forescout used Claude to port a WAGO PLC exploit for $536 in 8 hours, and an AI-generated payload later permanently bricked the test device.

Forescout researchers used Claude Code with Ghidra, terminal access, and physical hardware to port CVE-2021-31886, a pre-authentication buffer overflow in the Nucleus FTP server, from a WAGO 750-852 PLC to the WAGO 750-831 without source code or debugger access. The final RCE development stage cost $535.74 in API fees over an 8-hour, 32-minute session (2.6k input and 1.3M output tokens) and required heavy researcher guidance. Claude produced working ICMP and UDP beacon exploits in 12 minutes after identifying that normal FTP command completion was overwriting its shellcode, fixed by omitting the CRLF terminator. A follow-up session extending the payloads toward a C2 implant wrote to flash-mapped memory and permanently bricked the PLC, underscoring the risks of autonomous agents operating against physical infrastructure.

Security Affairs · 14d agoResearchCVE-2021-318861

LLMs and Contextual Integrity

Bruce Schneier highlights two papers: the CIMemories benchmark shows frontier LLMs leak memory attributes up to 69%, and an RL method reduces inappropriate disclosures.

Bruce Schneier discusses contextual integrity in LLMs, referencing the CIMemories benchmark, which uses synthetic profiles with 100+ attributes per user to test whether models with persistent memory disclose sensitive information appropriately. Evaluation showed frontier models exhibit up to 69% attribute-level violations, with GPT-5's violation rate rising from 0.1% to 9.6% across 40 tasks and reaching 25.1% with repeated prompting, showing unstable leakage behavior. A second paper introduces a reinforcement learning framework trained on a synthetic 700-example dataset that substantially reduces inappropriate disclosure while maintaining task performance, with improvements transferring to the human-annotated PrivacyLens benchmark.

Schneier on Security · 29d agoAI safety & security

Former OpenAI researcher builds an AI model that judges options instead of writing text

TypeSafe AI launches Jev, a judgment-only model built by ex-OpenAI staff that classifies inputs with 70-500 ms latency instead of generating text.

Startup TypeSafe AI, co-founded by former OpenAI researcher and InstructGPT co-author Diogo Almeida, introduced Jev, a model that scores developer-defined answer options with probabilities rather than generating free-form text. The company claims 70-500 ms responses, parallel multi-question evaluation, and $0.042 per million input tokens with free outputs, targeting request routing, sales intent scoring, and assistant guardrail checks. Benchmarks are self-built and not independently verified, the 'no hallucination' guarantee only covers output structure, and access is currently via waitlist.

The Decoder · 56m agoAI industry

GPT-6 Astra appears to show a "step change" in spatial reasoning based on early benchmarks

Early StationeryBench robotics results show OpenAI's GPT-6 Astra far ahead of Ai2's MolmoAct2 at dual-arm manipulation, completing 7 of 100 tasks versus zero.

A new robotics benchmark called StationeryBench tested OpenAI's GPT-6 Astra against Ai2's MolmoAct2 on five desk-object tasks using identical dual-arm YAM robots over 200 trials. Astra fully completed 7 of 100 tasks with a median progress score of 46 out of 100, while MolmoAct2 completed zero with a median score of 12. Cornell and Google DeepMind researcher Yoav Artzi called the result a 'step change in spatial reasoning' and noted Astra approaches human-level accuracy on the unpublished REMAP benchmark. He speculated OpenAI trained the model on large amounts of 3D data such as Blender scenes, and OpenAI reportedly plans consumer robots.

The Decoder · 4d agoAI industry 2 sources1

🔬“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 · 21d agoAI research1

Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project Zero · 8d agoResearch1

Evaluating Verified Autonomy in Quantum Engineering

Quantum-Harbor lab and QIQCBench (49 tasks) expose wide performance gaps across 17 frontier agentic systems in verified quantum engineering.

Researchers built Quantum-Harbor, a virtual laboratory providing a controlled execution environment where scientific AI agents interacting with quantum systems can have both actions and conclusions directly verified. QIQCBench contributes 49 expert-authored tasks spanning calibration and control, error correction and compilation, and sensing and networking. Across 17 frontier agentic systems, verified performance varied widely, exposing a substantial gap between demonstrated capability and reliable autonomous operation.

arXiv cs.AI / cs.LG / cs.CL · 23h agoAI research1

Coop – Isolated VM Environments for Running Claude Code and Codex

Trail of Bits releases Coop, running Claude Code and OpenAI Codex agents inside isolated virtual machines for safer agentic coding.

Coop, published on GitHub by security firm Trail of Bits, provides isolated VM environments for executing AI coding agents such as Claude Code and Codex. Isolation contains the filesystem and network side effects of autonomous agent actions, reducing risk from unsupervised tool use. The project drew 61 points and 16 comments on Hacker News.

Hacker News · AI · 9d agoAI tools & infraHN 61↑ · 16 comments1

[AINews] OpenAI to reach AGI bar by end-2026

OpenAI chief scientist Jakub Pachocki says unreleased Astra model meets the 'Automated AI Research Intern' goal; Altman expects internal AGI declaration by December 2026.

OpenAI chief scientist Jakub Pachocki says the unreleased Astra model fulfills the September 2026 'Automated AI Research Intern' target. Sam Altman told TIME he expects OpenAI to declare AGI achieved internally by December 2026. The roundup also covers Zhipu's GLM-5.3-Flash (320B total parameters, 18B active, 1M context), Google's Gemini Omni 1.1 Flash video model topping the Text-to-Video Arena, and the $399 open-source Microduck biped robot from Pollen Robotics and Hugging Face.

Latent Space · 19d agoAI industry

MicroHasTEE: Bare-Metal Haskell for Type-Level Peripheral Ownership on Armv8-M

MicroHasTEE expresses TrustZone secure and non-secure firmware as one typed Haskell program, catching peripheral-ownership inconsistencies at compile time.

MicroHasTEE is a multiparty Haskell framework that models both TrustZone firmware images as participants in a single typed program, using type-level capability ledgers to track peripheral acquisition, configuration, transfer, and finalization. MicroHs compiles the shared program twice to produce separate bare-metal Secure and Non-secure firmware images. The framework rejects inconsistent resource use, post-configuration attribution changes, wrong-domain callbacks, and calls to unregistered Secure services. A door-lock case study on an STM32U5 Nucleo board produced images of 232.7 KiB and 228.4 KiB of flash with roughly 220 KiB of SRAM per domain.

arXiv cs.CR · 5d agoResearch1

I spent a day at a robot “carnival” in Shanghai. Here’s what I saw.

MIT Technology Review reports on China's humanoid robot industry push and embodied AI strategy from a Shanghai event.

A dispatch from a Shanghai humanoid robot 'carnival' describes China's push into embodied AI, embedding artificial intelligence into physical systems. Embodied AI is a key facet of China's latest five-year plan, and Chinese companies are already world leaders in humanoid robots. Nearly 90% of the market discussion centers on domestic adoption of the machines.

MIT Technology Review · AI · 22d agoAI industry1

[AINews] Jev: a “System One Model” that only decides/classifies/routes/scores — >100x faster, >200x cheaper than small frontier LLMs

TypeSafe launches Jev, an RLCD-trained decision model claiming 20-200x faster, 40-400x cheaper classification than frontier LLMs, alongside Gemini 3.8 Live and Neon.

TypeSafe's Jev is a 'System One' decision model trained with RLCD, claiming 20-200x faster and 40-400x cheaper classification and routing than frontier LLMs with free output tokens and no hallucinated text. Google launched Gemini 3.8 Live and 3.8 Live Extended Thinking, supporting 97 languages and async tool calls, debuting #1 on Artificial Analysis' speech-to-speech index at 82.6. Periodic Labs' Neon is a ~1T-parameter XRD analysis model trained with RL on proprietary lab data using 1,300 H200s, lifting FrontierXRD success from 2.7% to 55.3% and beating GPT-6 Astra at lower inference cost.

Latent Space · 5h agoModel release

Why I'm still bearish on LLMs after Navier-Stokes

Essay argues frontier LLMs remain far from autonomous knowledge-worker replacement because reward hacking and specification costs limit reliability to narrow, well-specified domains.

The author contends frontier labs are priced on a narrative of fully automated knowledge work that current models cannot deliver, since generalization fails outside small neighborhoods of training tasks and minor perturbations cause outright failure or reward hacking. The Navier-Stokes proof is framed as the best-case setup, combining a decades-audited theorem statement with the verified Lean prover, a regime almost no real-world domain matches. Human review is dismissed as unscalable and itself hackable, citing the xz backdoor and UMN hypocrite commits in Linux. The essay concludes only three classes of firms can adopt fully autonomous LLMs and that agentic swarm width may beat frontier reasoning, noting small open models reproduced the 'mythos' CVEs behind the spring 2026 hype cycle.

Hacker News · AI · 22h agoAI industryHN 50↑ · 13 comments

I wrote an AI textbook — how long until AI can do it better?

AI researcher Nathan Lambert argues LLMs remain weak at long-form technical writing, questioning whether models can autonomously organize scientific knowledge for breakthroughs.

Nathan Lambert describes writing a post-training textbook, Reinforcement Learning from Human Feedback, and finds today's LLMs weak at organizing long-form technical content despite becoming superhuman at coding and math. He notes GPT 5.5 Pro found deep typos across a 200-300 page manuscript while Claude models proved more useful as editors. He argues that compressing knowledge through writing is a prerequisite for autonomous scientific insight and tempers expectations for near-term AI-driven open science.

Interconnects · Aug 12, 2026AI research

Efficient Branch-and-Bound Testing and Verification of zkVMs

ZEBRA verifies zkVM constraint systems via branch-and-bound cardinality counting, finding 11 zero-day bugs across five real-world zkVMs and running 51.5x faster than SMT verification.

ZEBRA reduces zkVM correctness to a solution-set cardinality problem requiring that each constraint system admit exactly one valid execution trace, eliminating redundancies like null-row padding and non-deterministic permutations before counting. It lifts analysis from finite-field witnesses to an integer interval lattice, exploiting that constraints across 5 real-world zkVMs use only 14.0% of theoretical connectivity capacity on average, enabling tight interval propagation. A parallel branch-and-bound search produces concrete counterexamples or certifies absence of violations within a bounded region. ZEBRA discovers 11 zero-day bugs (6 independently confirmed, 3 fixed), is 51.5x faster than SMT-based verification, and verifies 16.5 percentage points more instances.

arXiv cs.CR · 2d agoResearch

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.

MarkTechPost · 8d agoAI research

Dr. Claw: An AI Scientist Workspace for Vibe Research

Researchers release Dr. Claw, an open-source auditable workspace that wraps coding agents like Claude Code for end-to-end AI-assisted research workflows.

Paper 2609.00365 presents Dr. Claw, an open-source workspace that wraps existing coding-agent executors such as Claude Code and Gemini CLI in a controllable, human-in-the-loop research workflow. It uses persistent state objects, a reusable skill library, and multi-executor coordination to make research decisions auditable and recoverable, rather than adding another autonomous agent. Holding the executor fixed, Dr. Claw scores higher on research completeness than a bare command-line agent while preserving an auditable process trail. The code is released under AGPL-3.0 on GitHub (OpenLAIR/dr-claw).

Hugging Face daily papers · 16d agoAI research1

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.CL · 6d agoAI research

Φ-Bench: Can Large Language Models Engineer the Infrastructure That Powers Them?

Researchers release Phi-Bench, a benchmark evaluating frontier LLMs on open-ended, long-horizon engineering and optimization of the LLM infrastructure stack.

Phi-Bench evaluates LLMs on open-ended engineering of the LLM infrastructure stack, derived from optimization problems studied in frontier research and grounded in real-world code repositories. Tasks range from localized kernel-level function completion to long-horizon implementation and end-to-end system optimization. Experiments on frontier LLMs reveal current capabilities and limitations on the path toward autonomous optimization of future AI infrastructure.

Hugging Face daily papers · 7d agoAI research1

EmbodiedSkills: A Unified Framework for Orchestrating, Training, and Deploying VLA Agents

Researchers introduce EmbodiedSkills, a framework treating VLA skill decisions as verified execution proposals, reaching 86.2% success on RoboTwin 2.0.

The EmbodiedSkills framework treats each vision-language-action skill decision as an execution proposal, checking prerequisites before execution and verifying outcomes afterward via a shared executable-skill interface. It connects high-level skill selection, bounded low-level VLA execution and post-action verification in a single agent loop, and logs structured trajectories for supervision and optional online adaptation. Instantiated with Qwen3-VL and OpenPI/pi0.5, task-adapted policies achieve 86.20% average success across 50 RoboTwin 2.0 tasks and 97.40% across the four LIBERO suites, with 12.5% on memory-dependent RMBench tasks.

Hugging Face daily papers · 15d agoAI research1

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 papers · 9d agoAI research

Graph Machine: Towards Better Pretraining via Edges

Researchers propose Graph Machine, an O(n)-state sparse architecture that replaces 75% of Qwen3-0.6B dense layers with only slight loss change.

The paper introduces the Graph Machine (GM), an architecture that maintains an O(n)-sized state accessed through sparse, dynamic routing via pointer-like edges updated differentiably by a referral mechanism resembling pointer chasing. The authors replaced 75% of dense Transformer layers in Qwen3-0.6B with GM sparse layers and pretrained from scratch on 15.7B tokens. Retrieving 2 of 4,096 tokens per KV head in each sparse layer degrades loss only slightly, while retrieving 4 marginally improves loss over the dense baseline.

Hugging Face daily papers · 14d agoAI research

RobResilience: Implementing and Evaluating a Resilience Framework for Cyber-Physical Embodied Systems

RobResilience implements a runtime resilience framework for robots in Webots/ROS2, evaluating tolerable disruption, degradation, and mitigation feasibility across eight attack scenarios.

The paper implements a formal resilience framework for embodied cyber-physical systems using a PR2 robot and ROS2 in a Webots simulation. At runtime it evaluates three predicates — tolerable disruption (δ), tolerable degradation (γ), and mitigation feasibility (μ) — over a compromised device set derived from IDS confidence scores, triggering mitigation strategies when resilience is lost. Eight attack scenarios systematically covering the full predicate state space confirm runtime behavior matches theoretical definitions. The work addresses 'graceful failure paralysis,' where autonomous systems cannot distinguish safe degraded states from catastrophic hazards during attacks.

arXiv cs.CR · 1d agoResearch

Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models

A seven-person independent team trained open-weight agentic cyber models via a data-centric post-training framework, ranking 10th on CyberGym and first at comparable scale.

The paper presents Feyospace-v1, a data-centric post-training framework combining five systems: Choulea (hidden reasoning analysis), SkyReal (teacher-sampling cost reduction), Hongzwang (bypassing teacher API restrictions), PSBreakup (restoring capabilities weakened by model merging), and Kreator (converting expert interventions into trainable reasoning). The data engine builds resettable coding, vulnerability, CTF, kernel-history, full-exploit, firmware, and device-backed environments, retaining only execution-verified and evidence-audited trajectories, yielding 164,269 trajectories for long-context supervised fine-tuning. Three checkpoints improve over their starting models by an average of 23.76% on the full CyberGym suite and 10.49% across pooled CTF suites. As of September 1, 2026, Feyospace-s1 achieves a 63.24% verified success rate, ranks 10th on the official CyberGym leaderboard, and all three checkpoints rank 1st among models at comparable parameter scales.

Hugging Face daily papers · 8d agoAI research

Nous Research Adds One-Click Local Model Setup to Hermes Desktop

Nous Research's Hermes Desktop now offers one-click local model setup that reads hardware, picks a fitting quantization, downloads weights, and configures llama.cpp automatically.

Hermes Desktop, the MIT-licensed build of the open-source Hermes Agent, now sets up local models in one click: it reads the machine's hardware, selects a model that fits, downloads weights, and configures the inference runtime. It manages a pinned llama.cpp build with CUDA, Metal, Vulkan, HIP, and CPU backends, and shows green/amber/red memory-fit verdicts per catalog model before download. Quantization floors at 4-bit, and recommended models guarantee at least a 64K context window protected by ordered RAM offload (expert weights first, never the attention cache). It runs on macOS 12+, Windows 10/11, and Linux with no account required for local models.

MarkTechPost · 10d agoAI tools & infra1