Anthropic researchers discover the weird AI problem: Why thinking longer makes models dumber
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models
A new paradigm for AI: How ‘thinking as optimization’ leads to better general-purpose models
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Open vs. closed models: AI leaders from GM, Zoom and IBM weigh trade-offs for enterprise use
Experts from General Motors, Zoom and IBM discuss how their companies and customers consider AI model selection.Read More
Why your enterprise AI strategy needs both open and closed models: The TCO reality check
This article is part of VentureBeat’s special issue, “The Real Cost of AI: Performance, Efficiency and ROI at Scale.” Read…
Beyond static AI: MIT’s new framework lets models teach themselves
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Anthropic study: Leading AI models show up to 96% blackmail rate against executives
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Google launches production-ready Gemini 2.5 AI models to challenge OpenAI’s enterprise dominance
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Do reasoning models really think or not? Apple research sparks lively debate, response
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Red Team AI now to build safer, smarter models tomorrow
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Your AI models are failing in production—Here’s how to fix model selection
The Allen Institute of AI updated its reward model evaluation RewardBench to better reflect real-life scenarios for enterprises.Read More
Which LLM should you use? Token Monster automatically combines multiple models and tools for you
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How Snowflake’s open-source text-to-SQL and Arctic inference models solve enterprise AI’s two biggest deployment headaches
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