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Today in AI
Tuesday, May 26, 2026
Today in AI – May 26, 2026
5 links
  • 1
    Qwen 3.7 Max: Alibaba's New Flagship AI Model 2026
    www.digitalapplied.com
    Alibaba announced Qwen 3.7 Max on May 20 with 1M-token context window and a 56.6 score on Artificial Analysis Intelligence Index, outperforming Claude Opus 4.6 Max on Terminal-Bench 2.0. Developers evaluating open-weight alternatives to closed commercial models now have a competitive flagship option from a major cloud provider.
  • 2
    AI Model Releases May 2026: Complete Launch Tracker
    www.digitalapplied.com
    Google announced Gemini 3.5, Gemini Spark, Antigravity 2.0, and Omni models at Google I/O 2026, plus Search overhaul and Universal Cart features. Practitioners need updated capability matrices and pricing comparisons as Google's multi-tier model strategy expands across reasoning, coding, and multimodal tasks.
  • 3
    Anthropic Plans Public Release of Mythos-Class AI Bug Finder Once Safeguards Are Ready - gHacks Tech News
    www.ghacks.net
    Anthropic announced plans to release Mythos-class models for public access pending safety validation, currently restricted to select partners. Security teams and developers await availability of specialized bug-finding models as deployment safeguards complete evaluation.
  • 4
    OpenAI raises $110 billion at $730 billion valuation
    en.wikipedia.org
    OpenAI closed a $110 billion funding round in February 2026 (extended to $120 billion in March) led by Amazon ($50B), SoftBank ($30B), and Nvidia ($30B), becoming the largest private technology fundraise in history. Massive capital deployment signals accelerated model iteration and infrastructure buildout across the industry.
  • 5
    Study of 34 AI models finds biggest risks in privacy and fraud
    www.stocktitan.net
    Telus Digital's GenAI Safety Model Benchmark tested 34 leading models with 620,000+ adversarial tests, identifying privacy and fraud as primary risk vectors. Enterprise teams deploying AI systems need updated threat models and vendor evaluation frameworks reflecting real-world vulnerability patterns.
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