BREAKINGOpenAI closes $40B round at $340B valuation — largest private tech raise ever·MODELSAnthropic ships Claude Opus 4 with extended thinking and agentic capabilities·FUNDINGxAI raises $6B Series C led by Andreessen Horowitz for Grok infrastructure·REGULATIONEU AI Act enters full enforcement — high-risk systems must comply now·AGENTSGoogle DeepMind open-sources Gemini Agent Framework for autonomous task completion·RESEARCHStanford HAI: Enterprise AI adoption hits 78% globally, GenAI in production at 45%·WARNINGUS Senate passes AI Transparency Act — content labeling required at scale·PRODUCTMeta releases Llama 4 Maverick open-weight model rivaling proprietary alternatives·MODELSDeepSeek V3 scores within 2% of GPT-4o on MMLU at 1/10th the inference cost·FUNDINGMistral AI raises €600M Series B at €6B valuation for European AI sovereignty·BREAKINGOpenAI closes $40B round at $340B valuation — largest private tech raise ever·MODELSAnthropic ships Claude Opus 4 with extended thinking and agentic capabilities·FUNDINGxAI raises $6B Series C led by Andreessen Horowitz for Grok infrastructure·REGULATIONEU AI Act enters full enforcement — high-risk systems must comply now·AGENTSGoogle DeepMind open-sources Gemini Agent Framework for autonomous task completion·RESEARCHStanford HAI: Enterprise AI adoption hits 78% globally, GenAI in production at 45%·WARNINGUS Senate passes AI Transparency Act — content labeling required at scale·PRODUCTMeta releases Llama 4 Maverick open-weight model rivaling proprietary alternatives·MODELSDeepSeek V3 scores within 2% of GPT-4o on MMLU at 1/10th the inference cost·FUNDINGMistral AI raises €600M Series B at €6B valuation for European AI sovereignty·
announcement
Meta AI Releases NeuralBench: A Unified Open-Source Framework to Benchmark NeuroAI Models Across 36 EEG Tasks and 94 Datasets
May 7, 2026Meta AI
Event Summary
Meta AI team has released NeuralBench, a unified open-source framework for benchmarking NeuroAI models, alongside NeuralBench-EEG v1.0 — the largest open EEG benchmark to date, covering 36 tasks, 94 datasets, and 14 deep learning architectures evaluated under a single standardized interface across 9
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