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AIS ALERT MANAGEMENT AND SHARED PLATFORM, QUICK COMMAND FOR MULTIPLE SCENARIOS

AI HINT COMMAND分类推荐榜首Pricing unverifiedView details KiroCoding & development

Kiro is an AI engineering tool for developers that organizes requirements into specifications, architectures, and tasks, generates code via agents, and supports the entire workflow—from planning to code review—through property-based testing, execution memory, and integration with development tools.

AI programming tool分类推荐榜首Free entry availableView details EvoMapAgents & automation

EvoMap is an infrastructure designed for the reuse of AI agent experiences. It organizes reusable strategies and repair assets with validation records via the GEP protocol, offering market- and quality-based ranking to help different agents discover, evaluate, and inherit existing capabilities.

分类推荐榜首Pricing unverifiedView details MemoAIMusic & audio

MemoAI is an AI-powered audio-to-text tool that supports localized processing, eliminating the need to upload data and ensuring privacy and security. It can efficiently transcribe YouTube videos, podcasts, and local audio/video files (such as MP4, MP3, AAC, M4A, etc.) into text, while offering core features like multilingual translation, speaker diarization, real-time subtitles, and floating notes—making it ideal for meeting minutes, interview transcription, content learning, and more.

AI AUDIO TOOL分类推荐榜首Pricing unverifiedView details Open DesignDesign & 3D

OpenDesign is an open-source design workspace that can connect to local programming agents, use built-in model keys, or leverage cloud-based models, enabling the creation and editing of prototypes, web pages, presentations, and graphics within a design system; local software is free, while model services incur fees.

AI design tools分类推荐榜首Free entry availableView details JAXModels & infrastructure

JAX is a Python numerical computing library designed for accelerators, specifically tailored for high-performance array computations and large-scale machine learning. It efficiently executes the same code across multiple hardware backends, including CPUs, GPUs, and TPUs.

AI DEVELOPMENT PLATFORM分类推荐榜首Pricing unverifiedView details FinBusiness & support

CLIENT-ORIENTED AI SMART BODY。

Customer serviceSmartClient services待评分 · 分类列表推荐Pricing unverifiedView details ClipDropImages & editing

Clipdrop is a suite of AI-powered image creation and editing tools, covering background removal, local cleanup, image enlargement, upscaling, relighting, text removal, and background replacement. It allows users to process images directly in the browser and also provides developers with an API for integrating these capabilities into their applications.

常用AI图像工具待评分 · 分类列表推荐View details 闪剪Video & animation

FlashCut is an AI-powered creation platform for voice-over and short-video marketing. It can generate finished videos with voiceovers, subtitles, and visuals from text, offering digital human customization, photo-to-digital-human conversion, live-stream clipping, and intelligent editing. It also provides APIs and branded mini-program solutions for businesses.

待评分 · 分类列表推荐Pricing unverifiedView details Meta AI助手Assistants & search

Meta's free AI chat assistant

待评分 · 分类列表推荐Pricing unverifiedView details

AI, as it happens

1333 published stories
2026-11-06
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13:00
HHacker News Show HN·News

Show HN: Repairer – close the breach when a Linux flaw goes public

As we've seen with the Ubuntu critical CVE-2026-98432 (CVSS 9.8), AI-dicovered zero day exploit are being reported at an exponential rate and we don't have the process for dealing with the flood of exploits in real time.What we need is an AI-based system for autopatching systems based on real time information. The vendor's fix can take days or weeks to be out (is the Ubuntu thing patched yet?) and meanwhile the grid is vulnerable to exploitation, especially AI worms.Repairer is a small program that runs on each of your servers. The day an exploit goes public it puts up a stopgap that blocks it, and once the real fix is up it takes the stopgap back off by itself.A stopgap only takes something away — drop certain packets, turn off a kernel module or service, remove a setuid bit. It never opens a port, installs or downloads anything, nor runs code. It arms an undo playbook before applying the stopgap, so the change reverts if affects any services.It only ever acts on rules you sign with a (hardware) crypto wallet.Let's go further: stopgaps are written and checked by a swarm of AI agents (gnosh.ai sessions) running on gno.land, each with bonded stake. Each stopgap is run on fresh machines, and whoever is caught lying loses their stake to whoever caught them.The agent is built and tested on Ubuntu and Debian, all open source, standard-library Go. More distros coming. Let's build repairer together.https://gno.security/repairer/ https://github.com/gnosecurity/repairer Comments URL: https://news.ycombinator.com/item?id=50388417 Points: 1 # Comments: 1

Startups & new venturesRead original
05:11
HHacker News Show HN·News

Show HN: Cerea – yet another self-hosted LLM chat front end

Here is Cerea, a self-hostable, open-source (Apache 2.0) chat+agent frontend for LLMs. It works alone with any OpenAI-compatible inference provider, but it's way better when coupled with the model gateway I'm also developing, Pystino (https://github.com/paoloviviani/Pystino).I came to this after struggling to find a hosted chat interface that was truly open source, that I really enjoyed to use, and that was simple enough to be shared and used by family. In particular, I was looking for something that could provide the smooth and integrated user experience of commercial products for the tasks needed by family (e.g., document editing, form filling, notes and knowledge management), but backed by open models hosted wherever I decide.Then it became richer, now supporting: remote coding agents (wrapping Opencode), delegation and coordination between agents, integration between chat/projects and code agents (this one to me is a pain point for Claude, which I use at work), projects, RAG, rich artifacts support, schedules, and more.You can try it yourself, either cloning the full repo and head to Cerea/kit, or just the deploy kit with a script (https://github.com/paoloviviani/Cerea#quick-start).It's just a docker compose with a ./configure script that helps to generate a sensible .env for the specific scenario. It works in the browser and as a PWA on mobile.I hope you'll enjoy, feel free to reach out for questions. Comments URL: https://news.ycombinator.com/item?id=50384502 Points: 1 # Comments: 0

Startups & new venturesRead original
01:35
SSiliconANGLE AI·News

University of Utah retains operational sovereignty as Redtail expands research access

Operational sovereignty gives universities authority over how shared computing resources are allocated, managed and secured. The University of Utah’s Redtail AI factory supercomputer brings advanced computing capabilities to a statewide community. Supporting researchers, students, administrators and external partners through that infrastructure requires more than computing capacity, according to Manish Parashar (pictured), chief AI officer of […] The post University of Utah retains operational sovereignty as Redtail expands research access appeared first on SiliconANGLE.

Papers & researchRead original
2026-11-05
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13:00
aarXiv cs.DC·News

A Controlled Experimental Evaluation of Configuration and Cache Architecture in LLM Serving Engines

arXiv:2611.05991v1 Announce Type: new Abstract: Multi-agent LLM applications repeat most of their prompt tokens across requests, and serving engines reuse the cached state of shared prefixes. vLLM and SGLang reuse it at different granularities, and benchmarks of their default deployments report large performance gaps, usually credited to the cache. Such comparisons rarely control for other configuration differences. One of them, whether a long prompt is prefilled in chunks, is set by each engine's defaults from the hardware and the release, and it confounds the comparison. We built a reproducible testbed on Kubernetes and a seeded multi-agent workload generator, and compared the two engines under vendor defaults and with chunked prefill matched. SGLang's configuration is the same in both arms, which makes it an internal control across independently provisioned deployments. Under defaults, vLLM's median time to first token is up to 64x SGLang's. Matching one setting removes 78% of the capacity gap where that gap is largest and 30 to 67% of the latency gap. Near saturation the remaining latency gap reflects queue growth. A fluid queue model driven only by a 4.4% throughput shortfall reproduces it, and shows that such a gap scales with the length of the benchmark run. What survives matching is a tail-latency advantage of 2.4 to 6.4x at equal throughput, consistent with cache-aware ordering of waiting requests. We derive six recommendations for comparing serving engines.

Model evaluations & benchmarksRead original
13:00
aarXiv cs.AI·News

A Feasibility Condition for Confidence-Gated Tiered LLM Inference

arXiv:2611.05394v1 Announce Type: new Abstract: Tiered inference distributes large language model computation across a hierarchy of devices, from on-device and edge hardware to the datacenter, and is increasingly offered as the route to cheaper, lower-latency, and more private serving. Most such systems orchestrate frozen model checkpoints, and most decide what to resolve locally and what to escalate using a confidence signal produced by a forward-deployed model. We give a closed-form condition for when no threshold on that signal makes a tiered cascade worthwhile relative to sending every query to the backstop. Modeling the routing decision as a binary test and separating local from escalation cost through an architecture cost ratio $\kappa$, we derive a feasibility condition bracketed by a signal-free floor, below which a cascade is feasible at any signal quality, and a perfect-signal ceiling, above which none is. Read along the $\kappa$ axis the condition inverts: where local compute is billed, cost binds, matching a recent empirical finding; where it is sunk, on decentralized hardware, feasibility becomes unconditional and signal quality instead sets what the cascade achieves. We turn the condition into three design requirements that existing trained-in primitives satisfy only in isolation, and we propose, as future work, a co-designed architecture and a protocol to test it. The condition and the inversion hold independently of that architecture; they are the paper's contribution.

Model releases & updatesRead original
13:00
aarXiv cs.DC·News

Ab Initio Accuracy Beyond the Cutoff: Distributed Message-Passing Equivariant Attention at Tens-of-Millions-of-Atom Scale

arXiv:2611.06122v1 Announce Type: new Abstract: Molecular dynamics predicts molecular motion from atomic forces and trajectory integration. Density functional theory (DFT) provides first-principles forces, but its $O(N^3)$ cost limits simulations to thousands of atoms; empirical force fields scale to millions but miss bond breaking and charge transfer. Equivariant message-passing Transformers learn the ab initio potential at linear cost. Stacked layers propagate information beyond a single cutoff, giving four layers a receptive field up to 23{\AA}. At this frontier, scale is limited by communication: layers exchange boundary features across devices, force backpropagation repeats the exchange, and moving atoms change neighbor graphs and tensor shapes. We present Tessera, a distributed runtime that fixes workload shapes between rebuilds. It sorts atoms along a space-filling curve into equal-count shards, ensuring identical atom counts and tensor shapes per rank. Peer sets scale as $K^{0.5}$, not $K$. A conservative neighbor skin preserves topology across updates, enabling each rebuild interval to replay as one CUDA Graph. Fused kernels, three-level neighbor search, and overlapped All-to-All complete it. On 512 GPUs, Tessera sustains 30.7M atoms at 89.7% weak-scaling efficiency (77--90% across three per-GPU loads); per-step time rises 1.11--1.29x as machine and problem grow 16x. Graph reuse cuts full-step time $1.87\times$. Across an $8\times$ device increase, neighbor-search cost grows $1.7\times$, versus $3.0\times$ for Morton order. In a live $10.24$M-atom salt solution, NVE energy drift is $0.42\,\mu$eV/atom/ps over $10$ ps, and structure matches a serial reference. A 10.06M-atom Norovirus capsid sustains 100 ps of NVT at $\approx 8$ ps/day on 256 A100 GPUs. Over 200,000 steps, it has no broken bonds or anomalously close pairs and uses three compiled variants, with no graph breaks or eager fallbacks.

Chips, GPUs & hardwareRead original
13:00
aarXiv cs.AI·News

AGORA: Reliability-Aware Aggregation of LLM Judges via Item-Response Theory

arXiv:2611.05556v1 Announce Type: new Abstract: LLM-as-a-judge is a common substitute for costly human evaluation, and aggregating several judges is the standard remedy for any single judge's bias. Judge pools mix judges of very different reliability, while the human-labeled sets that validate them hold a few hundred items or fewer. In this regime the per-item mean weights weak judges as heavily as strong ones, and confusion-table models such as Dawid-Skene must estimate a per-judge error table from too few items. We propose AGORA (Aggregation Of Reliability-weighted Assessments), an item-response-theory aggregator that places every item on one latent quality scale and describes each judge by a sensitivity parameter and ordered rating thresholds, so judge reliability is learned from all items jointly and without human labels. Across three benchmarks, AGORA matches or exceeds Dawid-Skene on large evaluation sets, and its advantage widens as the set shrinks toward a few hundred items. It remains accurate as pools grow more uneven, a label-free dispersion statistic indicates in advance when trust weighting helps, and its learned trust weights track per-judge human validity.

Model releases & updatesRead original
13:00
aarXiv cs.AI·News

Assurance-Conditioned Continuous Authorization for Autonomous AI Agents

arXiv:2611.05632v1 Announce Type: new Abstract: Autonomous software agents can act through tools, delegate work, and change their models or execution environments while earlier authorizations remain in flight. We present Assurance-Conditioned Continuous Authorization (ACCA), an approach designed to be harness-independent, for maintaining operational authority according to currently justified assurance. It distinguishes evidence validity from contextual applicability, derives assurance claims from eligible evidence, and resolves a multidimensional effective-authority envelope within a principal-declared ceiling and applicable policy. A typed dependency graph supports selective re-evaluation of authorization-relevant changes. An authority epoch changes when effective authority changes; a distinct optional authorization-basis version supports revalidation of action-specific authorization conditions. Protected effect-time enforcement can reject stale actions before a consequential resource change, subject to the available commit mechanism. A compositional Domain Governance Profile expresses domain-specific semantics without granting authority. Controlled scenario tests implemented as a regression suite using a trading profile exercise default-deny rules, evidence-conditioned contraction and recovery, policy divergence, selective non-response, and stale-action rejection at a local gateway before the simulated-broker boundary. The study establishes implementation-level evidence in one domain, not a cross-domain guarantee of harmful-behavior prevention.

Model evaluations & benchmarksRead original
08:00
HHugging Face 官方博客·News

A Closer Look at Phonon TTS. Launching High-Quality On-Device Speech That Tops the Benchmarks.

Phonon, a small text-to-speech model that runs entirely on the user's device without requiring internet access, has been released with support for English, French, German, Spanish, and Portuguese. Built on the Pocket TTS lineage using flow matching, Phonon achieves high-quality audio in compact sizes (65 MB and 75 MB), with the 31m version licensed under Apache 2.0 for commercial use. It excels in intelligibility and speed, ranking first in German and Spanish on Hugging Face's Open TTS Leaderboard and leading in CPU streaming benchmarks. The model supports voice cloning, custom voices via Gradium Studio, and integrates with Hugging Face Transformers. It is available in multiple formats and backends, including WebAssembly, GPU, and NPU, enabling deployment across phones, laptops, single-board computers, and browsers. Over 200,000 downloads were recorded in its first two weeks, with active developer adoption through tools like ExecuTorch, Micdrop, and Spaces. Future developments include support for additional languages, smaller models, and custom vocabulary fine-tuning.

Open models & weightsRead original
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