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169 件並び順
17:26ENMatthew Berman on Funding US Open-Weight AI in Competition With ChinaMatthew Berman · Forward FutureBerman argues that open models face a financing problem and proposes public support, hardware-backed development and specialized models.
1:35ENDeepSeek V4 and the Cost of Frontier AI ModelsMatthew Berman · Forward FutureMatthew Berman argues that an open-weight Chinese model could put price pressure on US AI providers. The comparison depends on the workload, evaluation and cost assumptions.
17:21ENDeepSeek V4, Model Efficiency and the US–China AI DebateMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s April 2026 V4 preview and argues that efficient open-weight models raise questions for American AI providers and policymakers.
9:47ENGemma 4: Smaller Open-Weight Models for Local AIMatthew Berman · Forward FutureMatthew Berman reviews Google’s model sizes, multimodal features and reported benchmarks, with an eye toward local agents.
1:09ENThe Benefits and Tradeoffs of Running AI Models LocallyMatthew Berman · Forward FutureMatthew Berman weighs the privacy, control and costs of local models against technical complexity and performance tradeoffs.
0:59ENMatthew Berman's Quick Guide to AI Models and ToolsMatthew Berman · Forward FutureA March 2026 overview groups chat assistants, open-weight models, image and video generators, world models, coding agents and audio tools.
20:35ENA Beginner’s Guide to AI Assistants, Media Models and Coding AgentsMatthew Berman · Forward FutureMatthew Berman surveys hosted assistants, downloadable models, image and video tools, world models, coding agents and audio generation in a March 2026 overview.
54:26ENTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-Readyホスト Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.
4:25:13ENThe Architecture Barely Changed. Data, Cost, and Open Weights Did.ホスト Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.
14:44ENKimi K2.5: Visual Coding, Agent Swarms, Benchmarks and Local DeploymentMatthew Berman · Forward FutureMatthew Berman examines Moonshot AI’s multimodal open-weight model, its parallel-agent demonstrations and the practical costs of running it.
1:20ENLTX-2 Brings Open-Weight Audio and Video Generation to Local WorkflowsMatthew Berman · Forward FutureMatthew Berman discusses NVIDIA’s ComfyUI demonstration, creative controls and the prospects for locally generated video.
1:54:30ENFrom One in Ten Cancer Cells to One in a Millionホスト Nathan LabenzNathan Labenz's solo AMA updates his son's lymphoma treatment, calls Claude Opus 4.5 software AGI, and ranks the live players of early 2026.
1:18:40ENWhen AI Becomes the Oil Well: Luke Drago on the Intelligence Curseホスト Nathan LabenzThe Workshop Labs co-founder tells the FLI Podcast why a world of non-human production could recreate the resource curse — and how private data, open weights, and moonshot careers might still break it.
12:30ENAI News in December 2025: Gemini 3 Flash, Nemotron 3 and SAM AudioMatthew Berman · Forward FutureMatthew Berman reviews model releases, image generation, multi-model routing, data-center policy and reported AI investment talks.
18:09ENTraining a GPT-OSS 2048 Strategy With Verifiable RewardsMatthew Berman · Forward FutureMatthew Berman walks through a local Unsloth notebook, reward checks and one 2048 training run on an RTX 5090.
15:01ENAI News in December 2025: Disney, DeepSeek, Runway and MetaMatthew Berman · Forward FutureMatthew Berman reviews an OpenAI licensing deal, reports about AI chips and Meta’s model strategy, video generation, and Rivian’s autonomy plans.
9:41ENAI News in December 2025: Devstral 2, Agent Standards and Data-Center PowerMatthew Berman · Forward FutureMatthew Berman discusses model-release predictions, open agent infrastructure and ideas for powering terrestrial and space-based computing.
1:32:38ENPolish Is 1% of Frontier Training Data, So Poland Built Its Own Modelホスト Nathan LabenzMarek Kozlowski of Poland's National Information Processing Institute explains how PLLuM uses language adaptation, organic instructions, and on-prem small models to keep a mid-size country in control of its AI.
1:09:48ENChina's AI Labs Went From 15 to Six. The Compute Gap Is 15-to-1.ホスト Jacob EffronJordan Schneider tells Unsupervised Learning that Chinese models were a private-capital story, that Beijing still thinks in hardware, and that the West's real edge is chips it can serve — not a state master plan.
1:25:54ENHours after training ends, Z.ai puts the weights on the internetホスト Nathan LabenzZixuan Li of Z.ai tells ChinaTalk how a Chinese lab ships GLM, treats open weights as a ticket into Western ecosystems, and still sees itself as an upstart.
7:49ENDeepSeek V3.2: Reasoning, Sparse Attention and Agent TrainingMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s December 2025 model release, its benchmark results and the techniques used to improve long-context efficiency and tool use.
17:51ENAI News in August 2025: Claude for Chrome, New Models and AI InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a browser-agent preview, model releases, reported Apple discussions and research on inference and weather.
1:01ENOpenAI’s gpt-oss Release and a Coding BenchmarkMatthew Berman · Forward FutureMatthew Berman introduces two open-weight models and reviews a Codeforces comparison from the launch.
15:30ENQwen3 Tested: Coding Demos, Long Context and Response BehaviorMatthew Berman · Forward FutureMatthew Berman tests generated simulations, political and safety prompts, hand tracking and word puzzles using a hosted Qwen3 model.
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