Generative AI

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GPT-6 Astra: What’s Actually New in OpenAI’s New Frontier Model

OpenAI has released GPT-6 Astra, its newest frontier model, less than a week after Anthropic’s Claude Fable 5.1. OpenAI calls Astra the world’s most intelligent and aligned model yet. What actually makes Astra different? The simplest way to put it is this: Astra is built to do more, not just answer more. It can use […]

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Anthropic Releases Claude Fable 5.1 and Claude Mythos 5.1: 52.6% on Terminal-Bench-Science and 75% Cheaper Cache Reads

Anthropic has released Claude Fable 5.1 and Claude Mythos 5.1, three months after the Fable 5 line shipped in June 2026. The two are the same underlying model behind different safeguard layers. Fable 5.1 is generally available as claude-fable-5-1; Mythos 5.1 stays restricted to vetted organizations. Both carry a 1M token context window and 128K

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Stop saying AI isn’t a technology problem

“It’s not a technology problem. It’s a process problem.” “It’s not an accuracy issue. It’s an adoption issue.” “It’s not the model. It’s the human.” Sound familiar? I hear these arguments all the time. But here’s the reality: generative AI has an accuracy problem. In fact, it is well documented […] The post Stop saying

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ai in finance

Why Human Judgment Is Essential in AI-Powered Financial Controls

Artificial intelligence (AI) can review vast financial datasets, identify unusual transactions, and extend control testing across entire populations. Yet an alert does not explain intent, business context, or regulatory significance. An atypical journal entry may indicate misconduct while also reflecting a legitimate exception the model has never encountered. That distinction reveals the central limitation of

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Cohere Releases Parse 5 (parse-v5.0): A 2.3B Vision Language Model That Turns Enterprise Documents Into Markdown

Cohere has released Parse (parse-v5.0), a document parsing model aimed at high-volume enterprise ingestion. It is a 2.3B-parameter vision language model with an 8,192-token context window and a ~4.6GB footprint, built on Cohere Labs’ North-Micro-Vision-Instruct architecture. Parse takes a PDF, PPT or JPEG page as a base64-encoded data URI and returns Markdown containing text in

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How to Use Kimi K3: Moonshot AI’s 2.8T Open-Weight Model

Moonshot AI’s Kimi K3 is a 2.8-trillion-parameter open-weight model built with a Mixture-of-Experts architecture. It activates only a small fraction of its parameters per token, helping reduce inference costs while delivering strong coding and agentic performance. K3 combines near-frontier capabilities, open weights, and lower API pricing, making it an interesting alternative to proprietary models. In

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LLM services

What to Expect From LLM Customization Services

LLM Customization services help organizations adapt language-model applications to specific business tasks, knowledge sources, terminology, workflows, and security requirements. The work can include prompt design, retrieval-augmented generation, tool integration, fine-tuning, evaluation, deployment, and continuous optimization. Customization should not begin with the assumption that a new model must be trained. In many cases, clearer instructions and

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Optimizing clinical and operational resources through AI-driven medical record intelligence

AI-powered medical record intelligence helps healthcare organizations turn unstructured clinical documents into actionable insights, reducing administrative burden and enabling faster, more consistent review decisions. The post Optimizing clinical and operational resources through AI-driven medical record intelligence appeared first on SAS Blogs.

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Stanford Evo 2 AI model generates phages against E. coli

Stanford researchers have synthesised nearly 300 phages from DNA sequences produced by the Evo 2 generative AI model. Laboratory testing narrowed the group to 16 phages that showed particularly strong E. coli-killing activity. The work centres on bacteriophage ΦX174, pronounced “FYE-ex-1-7-4”. Brian Hie, an assistant professor of chemical engineering and Dieter Schwarz Foundation Stanford Data

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Claude Code Best Practices: 3 Lessons from 400,000 Sessions

I used to think Claude Code best practices were a matter of taste. Plan mode or not. Long CLAUDE.md or short. Pick what suits you, move on. Then Anthropic scored roughly 400k sessions from over 235k users against hard evidence of success. Tests passing, commits landing, users confirming they got what they asked for. Taste

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