More details on Fable 5’s cyber safeguards and our jailbreak framework
More details on Fable 5’s cyber safeguards and our jailbreak framework
Official announcements and industry reporting. Follow the timeline of AI.
From the latest news to tools that work for you.
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.
分类推荐榜首OOpenDesign 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.
分类推荐榜首KKiro 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.
分类推荐榜首M
MemoAIMusic & audioMemoAI 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.
分类推荐榜首EEvoMap 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A
AI ShortWriting & contentAIS ALERT MANAGEMENT AND SHARED PLATFORM, QUICK COMMAND FOR MULTIPLE SCENARIOS
分类推荐榜首AAssemblyAI is a speech AI platform for developers, offering pre-recorded, real-time, and short-form synchronous transcription APIs. It enables the building of voice-based applications by integrating capabilities such as speaker identification, emotion analysis, chapter and summary extraction, as well as speech agent functionality, dictation, and sensitive information processing.
待评分 · 分类列表推荐RRows is a spreadsheet tool that combines AI analytics, data integration, and interactive reporting, enabling you to organize documents and business data using natural language, merge datasets, generate reports, and build computational models. The official website currently indicates that it has been integrated with Superhuman and provides a corresponding link to continue using the service.
待评分 · 分类列表推荐IIamIP is a patent platform that provides AI-driven search, analysis, and monitoring tools to help users conduct patent research and management more efficiently.
待评分 · 分类列表推荐ZZoom Workplace is Zoom’s team collaboration platform, integrating video conferencing, chat, calendars, and documents, and leveraging built-in AI to organize discussions, draft messages, and track follow-up tasks.
待评分 · 分类列表推荐More details on Fable 5’s cyber safeguards and our jailbreak framework
The n8n 2.46.5 update addresses several bugs, including fixing the AI Agent Node's deprecated agent type callout, improving credential resolution for node parameters, and enabling reading named array keys in expressions. New features include hiding archived workflows by default in migration reports and displaying a message when the migration report takes too long to load.
The n8n 2.47.1 update introduces features to enhance the migration report experience, including hiding archived workflows by default and displaying a message when the report takes time to load.
NVIDIA H100 GPUs are here, with better performance and lower cost.
Enterprise artificial intelligence platform company Oumi PBC today extended its Frontier AI Engineer agent so it can build AI agents for customers and retrain the models those agents run on. The release goes after a problem that tends to surface once agents leave the demo stage. A failing agent might have a bad prompt, a […] The post Oumi’s Frontier AI Engineer now builds AI agents and retrains the models behind them appeared first on SiliconANGLE.
Query Insights for ClickHouse Managed Postgres now shows what active sessions are waiting on, with wait event breakdowns, blocked-session and lock-wait charts, and the same metrics in Prometheus.
Tech Report HuggingFace ModelScope Qwen Chat HuggingFace Demo ModelScope Demo DISCORD Introduction Two months after upgrading Qwen2.5-Turbo to support context length up to one million tokens, we are back with the open-source Qwen2.5-1M models and the corresponding inference framework support. Here’s what you can expect from this release: Opensource Models: We’re releasing two new checkpoints, Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, marking the first time we’ve upgraded our opensource Qwen models to handle 1M-token contexts.
GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction In the past three months since Qwen2’s release, numerous developers have built new models on the Qwen2 language models, providing us with valuable feedback. During this period, we have focused on creating smarter and more knowledgeable language models. Today, we are excited to introduce the latest addition to the Qwen family: Qwen2.5. We are announcing what might be the largest opensource release in history!
QWEN CHAT API DEMO DISCORD It is widely recognized that continuously scaling both data size and model size can lead to significant improvements in model intelligence. However, the research and industry community has limited experience in effectively scaling extremely large models, whether they are dense or Mixture-of-Expert (MoE) models. Many critical details regarding this scaling process were only disclosed with the recent release of DeepSeek V3. Concurrently, we are developing Qwen2.
Bespoke-Minicheck is a new grounded factuality checking model developed by Bespoke Labs that is now available in Ollama. It can fact-check responses generated by other models to detect and reduce hallucinations.
arXiv:2611.01893v1 Announce Type: new Abstract: Domain skew challenges federated learning by requiring a shared model to accommodate distinct visual distributions. Domain-specific experts can capture these distributions separately, creating an opportunity to integrate their representations in a unified predictor. We propose Federated Knowledge-Preserving Learning (FKPL), a two-stage framework that combines domain-oriented expert training with prototype-based classifier calibration. First, a one-shot subspace-based clustering procedure groups clients for intra-cluster training. The resulting expert encoders are concatenated and frozen, preserving each learned feature mapping during global integration. Second, clients interpolate their concatenated features with class-matched domain prototypes and upload the resulting virtual features. The server trains a global linear classifier on these features, concentrating classifier optimization at the server after a single feature upload. FKPL achieves average accuracies of 73.01\%, 67.00\%, and 64.51\% on Office-Caltech-10, PACS, and a four-domain subset of DomainNet, respectively. On DomainNet, its cross-domain standard deviation is 7.50 percentage points, the lowest among the evaluated methods. With the same concatenated extractor, prototype-based calibration improves average accuracy over federated classifier training by 9.99 and 14.94 percentage points on Office-Caltech-10 and PACS. These results identify classifier calibration as an effective way to combine preserved domain representations into a global predictor.
arXiv:2611.03826v1 Announce Type: new Abstract: Next-visit diagnosis prediction forecasts the diagnoses documented at a patient's next encounter, turning retrospective electronic health records into prospective clinical prediction. However, conventional aggregate evaluation obscures its multifaceted nature: distributionally, models must handle variable-size diagnosis sets and long-tailed labels; temporally, they must distinguish persistent, newly recorded, and recurrent diagnoses; and both vary with observed history depth. We introduce an evaluation framework along these dimensions and apply it to rule-based heuristics, LLM-based prompting, retrieval, memory, and multi-agent approaches. This reveals that repeating the last visit outperforms most LLM-based approaches overall despite predicting no new or recurrent diagnoses, and that retrieval and memory exhibit distinct profiles whose relative strengths vary across temporal transitions and backbones. Motivated by this, we propose LONGINUS, a retrieval-memory multi-agent adjudication framework combining evidence retrieved from patient records with structured memory of the patient trajectory. Using cross-view agreement as a reliability heuristic, it preserves shared predictions and adjudicates disagreements without revealing their source. Across MIMIC-III and MIMIC-IV with four LLM backbones, LONGINUS achieves the best transition-specific performance among LLM-based methods in nearly all settings while remaining competitive with them on aggregate metrics.
We've partnered with Hugging Face to bring Replicate inference to their platform.
MiniMax's Speech-02 models give you high-quality text-to-speech with voice cloning, emotional expression, and multilingual support.
A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes. The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep. No human checks either handoff. When it’s…
This repo provides an alternative to the ontology compiling capabilities of NVIDA Auto-Ontology.The main difference is that it builds the ontology from most of your existing data assets (transformation code, dashboards, docs), instead of building it from your warehouse and semantic layer only.It consists in skills and python scripts that ingest the metadata and docs your team already has, and compile them into YAML and Markdown files structured in a file tree that an agent can use as context to query your data.When your existing asset contradict, or reveal a gap in the business context around your data, it writes down questions for you and your team instead of guessing a plausible meaning.It runs locally in any coding agent. Comments URL: https://news.ycombinator.com/item?id=50363667 Points: 1 # Comments: 0
Article URL: https://chipmunksdanceai.net/ Comments URL: https://news.ycombinator.com/item?id=50362042 Points: 1 # Comments: 0
Article URL: https://github.com/posterlet/amazing-posters Comments URL: https://news.ycombinator.com/item?id=50367201 Points: 1 # Comments: 0
Article URL: https://railyard.run/ Comments URL: https://news.ycombinator.com/item?id=50361191 Points: 1 # Comments: 0
Give your curiosity direction. Make every day of reading count.