People who got tricked into buying a Mac mini by the Mac grifters now have a way to actually use them for local models
MACHINE LEARNING
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AI’s Impact on Consulting: The Irreplaceable Human Element
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What's #AI Going To Do To Consulting? The Human Element Remains Irreplaceable
by Annette Klososky @Forbes Learn more: https://
bit.ly/40YVg2M #MachineLearning #ArtificialIntelligence #ML -
Need 1000x More Benchmarks for Coding AI Evaluation
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“We need a thousand times more benchmarks than we have right now” is @alexgshaw of @LaudeInstitute's take on the current moment. “Coding is an extremely broad domain, 89 tasks isn’t nearly enough.”
— Snorkel AI (@SnorkelAI) 1 avril 2026
Full Benchtalks interview posted by @vincentsunnchen and YouTube in the replies pic.twitter.com/BRxjq6uzR4“We need a thousand times more benchmarks than we have right now” is @alexgshaw of @LaudeInstitute's take on the current moment. “Coding is an extremely broad domain, 89 tasks isn’t nearly enough.” Full Benchtalks interview posted by @vincentsunnchen and YouTube in the replies
→ View original post on X — @snorkelai, 2026-04-01 16:35 UTC
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OpenAI’s Internal Data Agent Revealed
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Inside OpenAI's in-house data agent bit.ly/4bqOLLU #AI #MachineLearning #DeepLearning #LLMs #DataScience [Translated from EN to English]
→ View original post on X — @miketamir, 2026-04-01 16:06 UTC
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Trinity-Large-Thinking model released on Arcee API and Hugging Face
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Today we're releasing Trinity-Large-Thinking.
— Arcee.ai (@arcee_ai) 1 avril 2026
Available now on the Arcee API, with open weights on Hugging Face under Apache 2.0.
We built it for developers and enterprises that want models they can inspect, post-train, host, distill, and own. pic.twitter.com/jumuYehJdoToday we're releasing Trinity-Large-Thinking. Available now on the Arcee API, with open weights on Hugging Face under Apache 2.0. We built it for developers and enterprises that want models they can inspect, post-train, host, distill, and own.
→ View original post on X — @thom_wolf, 2026-04-01 15:47 UTC
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NVIDIA Blackwell Dominates MLPerf Inference v6.0 Token Factory Performance
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AI data centers are token factories.
— NVIDIA AI (@NVIDIAAI) 1 avril 2026
See how NVIDIA extreme co-design maximizes token output to profitably scale AI revenue. https://t.co/aotG4jvuFkAI data centers are token factories. See how NVIDIA extreme co-design maximizes token output to profitably scale AI revenue. NVIDIA Data Center (@NVIDIADC) 📣 MLPerf Inference v6.0 results are in. Learn how systems powered by NVIDIA Blackwell set the pace on inference, delivering the highest AI factory throughput. 🔗 nvda.ws/4sFFA0k — https://nitter.net/NVIDIADC/status/2039359226712097227#m
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New scalable method for evaluating 15 LLM AI models published
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The current science of evaluating AI models, such as primarily relying on benchmarks, is far from optimal. @Nature today a new scalable way used to assess 15 LLMs with absolute demand scales, enhancing predictor power and expandability nature.com/articles/s41586-0…
→ View original post on X — @erictopol, 2026-04-01 15:13 UTC
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NVIDIA Blackwell Dominates MLPerf Inference v6.0 with Record Throughput
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📣 MLPerf Inference v6.0 results are in.
— NVIDIA Data Center (@NVIDIADC) 1 avril 2026
Learn how systems powered by NVIDIA Blackwell set the pace on inference, delivering the highest AI factory throughput.
🔗 https://t.co/Abid9w6wx3 pic.twitter.com/yemqfVgS60📣 MLPerf Inference v6.0 results are in. Learn how systems powered by NVIDIA Blackwell set the pace on inference, delivering the highest AI factory throughput. 🔗 nvda.ws/4sFFA0k [Translated from EN to English]
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Large Language Models Need Embodiment: New Neuron Perspective
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The need for embodiment for large language models @NeuroCellPress an open-access perspectiive cell.com/neuron/fulltext/S08…
→ View original post on X — @erictopol, 2026-04-01 14:41 UTC