搜索“RAG”

alidate, and patch critical software vulnerabilities. For trusted defenders and our own internal teams at Google, we’ll be releasing Argon without cyber guardrails so they can leverage its full frontier-level cybersecurity defense capabilities. Wiz is already using Argon for cybersecurity defense through its Scan for Good initiative – a program dedicated to protecting critical public infrastructure for free by finding and remediating high-risk exposures. In an early demonstration of its impact,

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asks: Solar Mini 4 generates 208 tokens/s as of launch date, faster than GPT-6 Luna (max) at 152 tokens/s. However, it uses 88k output tokens per Intelligence Index task, so it averages 7.1 minutes per task. ➤ Agentic coding is a relative weakness: It scores 1% on Terminal-Bench 4.0 and 22% on AutomationBench-AA. On agentic knowledge work, it scores 1072 Elo on GDPval-AA and 872 Elo on AA-Briefcase, close to Inkling (xhigh). ➤ Low knowledge accuracy, but also relatively high non-hallucination ra

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Technical Blog sessionStorage.removeItem('facets.search.text'); sessionStorage.removeItem('facets.search.text-copy'); sessionStorage.removeItem('facets.search.filters'); Related Resources Developer Tools & Techniques Parallel work, model family isolation, reversible changes, and GPU-backed validation shaped an open source project designed around coding agents AI-Generated Summary NVIDIA TensorRT Model Connect is an open source collection of AI model reference implementations in C++ built on NVID

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en treated as distinct and unrelated fixes, the field has lacked a single, principled mathematical language to unify, analyze, and optimize how we control generative models. This fragmented approach often forces engineers to rely on guesswork when balancing user preference alignment against image quality. To solve this balancing act, we present the Diffusion Controller framework. Instead of treating image generation as a rigid sequence of isolated steps, Diffusion Controller reframes the entire

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at leading AI conferences and sharing his expertise on Agentic AI at top-tier events. Dalien Ahiekpor Dalien is a Senior Account Executive at AWS supporting enterprise Travel and Hospitality customers. With four years of experience as a Technical Account Manager before moving into his current role, Dalien brings a unique blend of technical depth and business acumen to every customer engagement. He is passionate about helping customers leverage cloud technology to transform the guest experience.

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rity level over the past 12 months as a stacked line chart. Add a trend line for total volume so I can see whether the overall load is rising or falling.” Comparative: “Compare average deal size by industry vertical and sales rep for Q4 2025. Show it as a grouped bar chart sorted by deal size descending, and highlight any vertical where our average is below $50K.” Relationship: “Build a scatter plot of customer lifetime value versus product usage frequency. Color-code the dots by subscription ti

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Condé Nast’s editorial teams had no fast way to do multimodal video discovery. They were spending an average of 250 minutes per content discovery task, manually scrubbing through a library of more than 140,000 videos. They relied on titles and descriptions to find relevant clips. In a media environment where speed-to-market directly determines revenue capture, this process created measurable operational drag across brands such as Vogue, GQ, Vanity Fair, and Wired. The core problem was structural

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of year for our merchants, and buying activity during those days is a bellwether. During this year’s BFCM, Shopify merchants saw another 3% increase in purchases on mobile, an average of 69% of sales.” With mobile so important, it’s no surprise the company built native mobile applications for iOS and Android; after all, native mobile gives full control of a platform’s capabilities, integrations, and performance, so why bother with cross-platform technology? It turns out one reason was the delay

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e specific, noting that hyperscaler capex estimates were now over $1.1 trillion in 2027. These revised capex plans also came with a new and deeply-worrying analysis, taking the average of estimated AI capex for 2026 and 2027, and calculating how much annual AI revenue hyperscalers would need to break even on their capital expenditures for just those two years. To just break even, hyperscalers need $308 billion in annual AI-specific revenues, and for a 10% Return On Invested Capital (calculated b

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re of 7.78%, placing first on the leaderboard. On TALENT, it achieves the top overall ranking across classification accuracy, classification log-loss, and regression RMSE, with average ranks of 6.67, 3.98, and 4.22. On ScoringBench, a benchmark for predictive distributions, Kumo Tabular-Large and Medium rank first and second on average rank. Limitations Kumo Tabular works on numerical and categorical columns only, while text, images, or timestamps can be turned into features via built-in pre-pro

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in New York tonight; it’s urgent.’” He mentioned that the platform is growing 10% day by day, with transaction volume increasing at a similar rate. The company’s founder was also dragged for some of his comments on the show. He said that most restaurants have a first-come-first-served reservation system, which doesn’t account for someone’s special occasion. He said that an agent can check restaurant sites every five seconds and inform the user about available slots. Shinn also hinted that the co

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wth in 2025 after five years of decline, with revenue rising 20% in the first six weeks of 2026, according to Circana. Bose’s $99 pair costs nearly 8x the category’s around $13 average selling price in 2025, testing whether the comeback can sustain demand for a premium upgrade. Image source: Flock The Rundown: Flock’s surveillance network just got an unwanted close-up: a researcher published a map of its device records and received a takedown demand, while some cities dropping Flock are turning

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r on the reported local configuration, with the NLI and routing calls themselves in the tens of milliseconds. Why this fits Multiverse Computing As agents move from single-passage RAG to multi-tool MCP setups, the question of which source a fact actually came from stops being a footnote and becomes part of what factuality means. ProvenanceGuard makes that source connection visible claim by claim. For Multiverse Computing, that means a way to check existing agents while keeping sensitive traces i

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mmittee (an LP and my beloved alma mater) asked for a few thoughts on what's happening in AI. I recorded a test run yesterday morning and then shared it with my partners, who encouraged me to share it more broadly... so here you go! \n\nThis is not…","username":"gradypb","name":"Pat Grady","profile image url":"https://pbs.substack.com/profile images/1012299406580674561/PoFKkmm7 normal.jpg","date":"2026-09-25T17:25:07.000Z","photos":[],"quoted tweet":{},"reply count":125,"retweet count":350,"like

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prefix is a state where the teacher gives a target distribution, so 64 rollouts per step already yield tens of thousands of supervised positions. One query reaches 71.5% state coverage of what full-data OPD visits; 16 diverse queries reach 98.9% and match full data—extra queries buy new states, not new questions. 3️⃣Alignment slows, not the data. The student keeps improving, but each update absorbs less of what is left, which is why a run takes hundreds of steps rather than tens. This decline ha

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d in the Hugging Face incident . OpenAI’s agents sometimes considered the possibility that they were engaged in “unauthorized” activities but proceeded anyway, sometimes with encouragement from other agents. The solution could include a change to the instructions that guide a model’s behavior. Claude’s constitution , for example, sets out the values Anthropic wants the model to follow. But “perhaps surprisingly, law is just not one of them,” Kolt notes. These instructions could rank legal compli

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scaling. On HotpotQA, RLCR reduces expected calibration error (ECE) from 0.37 to 0.03 compared with RLVR, with similar accuracy (62.1% versus 63.0%). Across six other datasets, average ECE falls from 0.46 to 0.21, while accuracy rises from 53.9% to 56.2%. These are the results in the paper’s Table 1(a). Conceptually, the “Classifier” in “RLVR + Classifier” is a supervised binary classifier that predicts whether the generated answer is correct. For Jev, I could apply calibration rewards directly

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6%. Scores come from Table 1 of the RRSI research paper. All methods share the same starting harness, policy, evolve split and candidate budget. Per the RRSI research team. OOD average is the mean of JobBench, GDPval and APEX-Agents, computed from Table 1 . Meta-Harness leads on the Harvey LAB evolve split. RRSI has the smallest evolve gain but the only OOD average more than 1 point above H0. git clone https://github.com/google-research/rrsi.git && cd rrsi pip install -e ".[dev]" python3 rrsi.py

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g and Computer Science (EECS) and is also a principal investigator in the Laboratory for Information and Decision Systems (LIDS). Hedden is joined on the paper by co-author Manish Raghavan, the Drew Houston (2005) Career Development Professor at the MIT Sloan School of Management and in EECS, as well as a LIDS principal investigator. The research appears in Philosophical Perspectives. The move toward monoculture Algorithmic monoculture, in which all decisions across a certain domain are made usi

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net 5.5を使った作例として、紅葉のシミュレーターや手描き風のフローチャートツールなどを紹介した。フローチャートツールでは、図形をドラッグして接続したり、図の上に描き込んだりできるという。 A working flowchart tool that looks like doodles on graph paper, by @kevin t ngo. Drag shapes, connect them, or sketch on top. pic.twitter.com/JOWje43O7t— Claude (@claudeai) September 28, 2026 また、AnthropicのEdwin Arbus氏は、Sonnet 5とSonnet 5.5が「はい／いいえ」で答えられる質問を重ね、20問以内で絵文字を当てようとするデモを紹介している。このデモでは、Sonnet 5.5はSonnet 5よりも所要時間が短く、費用と使用トークン数も少なくなっている。 Sonnet 5.5 plays twenty cool calls: It tries to guess the

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