搜索“RAG”

1974 Log Windows sandbox availability and backend selection @iceweasel-oai 52034 Preserve agent state when unloading idle multi-agent v2 children @jif-oai 52040 Add regression coverage for cancelled agent reloads @jif-oai 52048 Cover instant interruption in steered-input persistence tests @jif-oai 52061 Run Guardian conversation classifiers concurrently and preserve action order @felixxia-oai 52062 Add scenario coverage for worker context across idle eviction @jif-oai 52065 Require assessment te

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searchers employed IRIS to identify signals needed to create a cell type critical for lung development, the model predicted that activating a specific signaling pathway would encourage lung-specific development. Experiments in mouse embryos confirmed the model’s prediction. By identifying the precise combinations of signals that drive lung cell development, they can more reliably generate accurate, lab-grown models of lung tissue. “In these ways, IRIS is helping us decode the language cells use

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personalized conversational experiences grounded in organizational data and content. This enables NVIDIA to tailor interactions on their website based on customer needs, while leveraging Nemotron to deliver fast, high-quality responses at scale. Sparking Creativity, to the MAX Get ready for what’s next — with three days of creative skill-building, visionary keynotes and valuable connections at Adobe MAX, running Nov. 10-12. Adobe and NVIDIA will showcase the latest advancements for creators alon

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tprint, with the ambition to achieve net-zero greenhouse gas emissions by 2040. In 2025, Volvo Cars sold over 710 thousand cars, with an electrified share of 46%. Volvo Cars on average employed 42,600 full-time employees. Volvo Cars' head office, product development, marketing and administration functions are mainly located in Gothenburg, Sweden. Volvo Cars' production plants are located in Gothenburg, Ghent (Belgium), South Carolina (US), Chengdu, Daqing and Taizhou (China). The company also ha

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We benchmarked Lakehouse//RT against a traditional cloud data warehouse across a suite of spatial queries using SpatialBench. By comparison, Lakehouse//RT delivers 3X faster on average, and up to 20X faster across the tested queries. Under heavy load, the performance differences are even more significant. At 50 concurrent users, Lakehouse//RT delivers up to 38X on the queries where the traditional warehouse could keep up. Try it for yourself: Follow the SpatialBench documentation to generate the

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r it landed, cross-platform correlation was limited because data lived in different places and shapes, and SIEM pipelines were not keeping pace. The team needed a way to coalesce fragmented telemetry into one place and make sense of it, while maintaining flexibility and avoiding vendor lock-in. The solution: Open schema on the security lakehouse Atlassian's answer was to standardize everything on the Open Cybersecurity Schema Framework (OCSF) and build the lakehouse on Databricks. OCSF won becau

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mber of clearly defined categories (e.g., data about customers, attorney-client privileged information, or information about our model architectures), Anthropic employees are encouraged to share information with them just as they would with a fellow employee working on alignment risk.1 METR will publish its analysis of our risk levels, incidents, or practices. Anthropic can’t veto publication, but we can require them to redact information if it falls into narrow, predefined categories like the o

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s of files without breaking tasks into pieces. Beyond coding, it searches the web (including multimodal browsing), spawns and coordinates subagents for decomposable tasks, and leverages computer use capabilities unified across desktop, mobile, and browser. It generates separate commentary before each action, so developers know what the agent is doing and why. The model’s 1.8B perception encoder natively processes interleaved text, images, video frames, and audio without separate pipelines per mo

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gravity provides an agentic science workbench that empowers biologists to discover, structurally evaluate, and prioritize promising targets quickly, compressing what used to be a fragmented search over multiple databases into a single session. It also helps researchers scan through millions of previously uncharacterized proteins in the UniProt database using ProtNLM, a model that predicts biological function from amino acid sequences. This technical walkthrough shows how biologists used Google A

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code and prompts are processed on infrastructure that you configure and control. You can attach the endpoint to your own Amazon Virtual Private Cloud (Amazon VPC), encrypt its storage volume with a key from AWS Key Management Service (AWS KMS), and turn on network isolation for the container. You also choose the instance type and scaling limits, and you pin the model version, so the model only changes when you redeploy. Use cases You can use Muse Spark Open for a wide range of applications. Met

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eviously passing metric regresses. This prevents developers from accidentally trading a critical capability for a minor edge-case improvement. Shared dashboards and centralized storage: Configure your eval processes to export run artifacts—including raw trace JSONL, prompt hashes, model versions, latency profiles, and scorecard summaries—into a central data warehouse like BigQuery or Cloud Storage. Publishing these metrics to a shared team dashboard gives everyone visibility into accuracy, laten

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practice: finance (financial advisor, small-business loan processor), evaluation (LLM auditor), document and knowledge pipelines (high-volume document analyzer, multiformat hybrid RAG), content and brand (brand-aligned presentations, brand-search optimization, on-brand genmedia), retail (product search, virtual try-on), and framework examples (agent-skills tutorial, staged UI widgets). Java, Go, TypeScript, and Kotlin each carry smaller sets. Every entry in contrib/ is a worked example of how a

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service where engineers implement OAuth 2.0 and cryptographic security controls like DPoP to protect API integrations. Separately, Google Workspace Context-Aware Access (CAA) leverages DPoP to secure enterprise AI workloads on the Gemini Enterprise Agent Platform by cryptographically validating agent identities at the Agent Gateway. Google's OAuth Platform supports DPoP binding specifically for refresh tokens. This design choice reflects a pragmatic engineering tradeoff: by sender-constraining

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and gave them no human hints. GPT-6-Astra, running in OpenAI's Codex coding environment, came out on top. It found the right answer for 49 of 50 problems, or 98 percent, at an average cost of under $3 per problem and just under $116 for the whole benchmark. The benchmark tests routine research work, not grand challenges The collection deliberately leaves out major open questions and focuses on what the authors call "turn-the-crank" problems, where researchers apply known methods to a slightly m

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cap to 50 and equipment cap to 55. GeForce NOW offers Enshrouded 1.0 ready to play in the cloud at launch across supported devices. Skip the 60GB local install to save precious storage space, then step into the Shroud without waiting for downloads or needing to make room for the update. Let the Bolts Fly Warhammer 40,000: Boltgun 2 is now streaming on GeForce NOW. The brutal, fast-paced sequel to the retro first-person shooter brings more enemies, more weapons and new ways to purge. Picking up d

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2016. It ranks each segment by its absolute and relative revenue impact, revealing that weekday midday hours drove the largest gain while the weekday evening rush was the biggest drag. Because these functions use tailored machine learning methods, they enable Genie to answer questions a general-purpose LLM cannot reliably handle on its own. Industry-leading quality These functions all deliver high-quality predictions backed by production-grade ML models. Because Databricks maintains those models

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ers will support additional tags for prosody or speaking rate. A script written for one TTS provider won't behave the same as another, even if both claim SSML support, because coverage of the full tag set varies. What varies most is which tags a given text to speech model actually processes, which is where ElevenLabs' implementation becomes specific. Using SSML with ElevenLabs SSML support through ElevenLabs isn't fully uniform. It depends on which model you select to generate the audio. The tag

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ed up to 31x faster than diffusion LMs with 3–5x fewer training tokens (Hazy). Hybrid Reasoning Agents: The method reasons in latent space and acts in text. It reports a +10.4% average gain, 35–55% fewer tokens and 1.8–2.6x faster inference (summary). DuoDiscover: Google’s agent co-discovers optimization targets and cheap proxy evaluators. It reports 1 on SOL-ExecBench, 1.92x on vLLM and 2.68x over production TPU kernels (@VioletNPeng). AutoEnvScaling: Self-designed RL environments lift Qwen3.6-

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kids and they are lying to Iowans,” Iowa Attorney General Brenna Bird said in a statement to CNBC. “OpenAI claims ChatGPT is safe while it’s giving dangerous medical advice, encouraging people to hurt others, and coaching people to commit suicide — all while pretending to be their fake friend.” In a statement, OpenAI told me that the company is focused on product safety. In August it introduced ChatGPT for Teens, a suite of product features with enhanced guardrails and parental controls. “We’ve

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batches example. Initial training benchmarks Our baseline training of the model over the complete dataset takes 7 hours and 44 minutes and during the training the GPU shows 98% average utilization. The result is 9,396 tok/s training. This GPU utilization looks high, but as mentioned earlier that number is misleading. The standard GPU utilization metric only counts the percentage of the time the GPU was doing anything, so this does not tell us how well the model was using the GPU while it was act

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