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13:09ENAI News: Ultrafast Inference, Claude Watermarks and New ModelsMatthew Berman · Forward FutureMatthew Berman reviews an ultrafast coding preview, text watermarking, Grok Bot, open-weight models and Computer History.
0:24ENMatthew Berman Checks His Clawdbot Token CostsMatthew Berman · Forward FutureA short usage check reveals unexpectedly high model spending over two days.
1:38ENNVIDIA’s Groq Licensing Deal and the Inference MarketMatthew Berman · Forward FutureMatthew Berman discusses why NVIDIA licensed Groq’s inference technology and hired members of its team.
8:47ENWhy Identical LLM Prompts Can Produce Different Answers at Temperature ZeroMatthew Berman · Forward FutureMatthew Berman explains Thinking Machines Lab’s work on batch-invariant inference and what its reproducibility experiment actually showed.
10:01ENDeepSeek R1 Code Optimization and a $3 Visual Counting ExperimentMatthew Berman · Forward FutureMatthew Berman examines a human-guided coding improvement and a small reinforcement-learning experiment, then considers their implications for AI research.
0:54ENOpenAI’s o1 Preview: A First Look at Longer ReasoningMatthew Berman · Forward FutureMatthew Berman introduces the o1-preview and o1-mini models and tries a Python game prompt.
11:20ENMatthew Berman Adapts Mixture of Agents to Groq InferenceMatthew Berman · Forward FutureA 2024 tutorial changes an open-source multi-model ensemble to use Groq, then tests its interactive output and fixes a streaming error.
13:18ENTesting Local AI on a Dual RTX 6000 WorkstationMatthew Berman · Forward FutureMatthew Berman tests language models, concurrent inference, and image generation on a Dell Precision tower supplied by Dell and NVIDIA.
9:02ENMatthew Berman Tries LLM Colosseum, a Street Fighter Model BenchmarkMatthew Berman · Forward FutureA 2024 tutorial shows language models choosing fighting-game moves, explains the game-state prompt and walks through local setup.
14:11ENLM Studio in 2024: Local Models, Parallel Inference and a Local APIMatthew Berman · Forward FutureMatthew Berman demonstrates model downloads, hardware settings, JSON output and serving multiple local models.
5:53ENPetals: Distributing Large Language Model Inference Across DevicesMatthew Berman · Forward FutureIn 2023, Matthew Berman explains Petals as a way to use large models through a network of participating computers rather than loading every layer on one device.
8:17ENUsing OpenLLM to Serve Open Models Through an APIMatthew Berman · Forward FutureMatthew Berman demonstrates a local model server, its interactive API and a Python client in a 2023 walkthrough.