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5:06:18EN
Lex Fridman· 2025년 2월 2일팟캐스트DeepSeek's $5 million training claim and the five-year bet on compute진행자 Lex FridmanDylan Patel and Nathan Lambert walk Lex Fridman through DeepSeek-V3 and R1, export controls, TSMC, megaclusters, and who actually makes money in the AI race.기업과 전략Open-weight modelsPretraining & midtraining+3
슬라이드 3장6:44EN
Matthew Berman· 2025년 2월 1일Testing DeepSeek Janus-Pro for Image Understanding and GenerationMatthew Berman · Forward FutureMatthew Berman tries the 7B multimodal model on diagrams, memes and image prompts using a sponsored cloud GPU demonstration.비전과 영상Generative mediaMultimodal AI+2
슬라이드 5장7:41EN
Matthew Berman· 2025년 1월 30일CES 2025 and Running DeepSeek R1 Distills on an RTX 5090Matthew Berman · Forward FutureMatthew Berman tours AI demonstrations at CES and runs two quantized DeepSeek R1 distilled models locally on an NVIDIA GPU.Local inferenceOpen-weight modelsSemiconductors+2
1:00:02EN
20VC with Harry Stebbings· 2025년 1월 29일팟캐스트 · 2명Jonathan Ross on DeepSeek, Open Models and AI Infrastructure게스트 Jonathan Ross · 진행자 Harry StebbingsThe Groq CEO discusses reported training costs, inference demand, competitive strategy and the security concerns surrounding AI.InferenceAI cost & performanceGeopolitics+2
슬라이드 3장5:27EN
Matthew Berman· 2025년 1월 29일Ways to Try DeepSeek R1: Hosted and Local Distilled ModelsMatthew Berman · Forward FutureMatthew Berman demonstrates DeepSeek chat, Groq’s hosted distill and a local model in LM Studio.Local inferenceOpen-weight modelsQuantization
슬라이드 4장20:34EN
Matthew Berman· 2025년 1월 28일DeepSeek R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines 2025 reactions to DeepSeek, from training efficiency and market losses to open weights, privacy and the possibility of a demand rebound.모델과 학습AI cost & performanceOpen-weight models+2
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025년 1월 25일팟캐스트From 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Table진행자 Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.모델과 학습Reinforcement LearningReasoning & test-time compute+3
슬라이드0:55EN
Matthew Berman· 2025년 1월 23일A Quick RTX 5090 Local AI TestMatthew Berman · Forward FutureMatthew Berman runs an 8B DeepSeek R1 distillation locally and reports the speed of one generation.Local inferenceSemiconductorsOpen-weight models
슬라이드 4장15:10EN
Matthew Berman· 2025년 1월 22일DeepSeek R1 Tested on Coding, Reasoning and Sensitive QuestionsMatthew Berman · Forward FutureMatthew Berman runs the full R1 model on cloud GPUs and tries game programming, reasoning puzzles and politically sensitive prompts.Reasoning & test-time compute평가(Evals)Open-weight models+2
슬라이드 5장8:52EN
Matthew Berman· 2025년 1월 21일Industry Reactions to DeepSeek R1’s 2025 ReleaseMatthew Berman · Forward FutureMatthew Berman reviews early reactions to DeepSeek R1, from open-weight reasoning models and local hardware to benchmark results and API pricing.Open-weight modelsReasoning & test-time computeBenchmarks+2
1:24:57EN
Unsupervised Learning: With Jacob Effron· 2025년 1월 21일팟캐스트A 50,000-GPU cap and a 1,700-chip loophole진행자 Jacob EffronSemiAnalysis founder Dylan Patel walks through the AI diffusion rule, China’s compute squeeze, and how xAI stood up a 100,000-GPU cluster in a closed Memphis appliance factory.인프라와 배포AI RegulationGeopolitics+3
슬라이드 3장12:15EN
Matthew Berman· 2025년 1월 20일DeepSeek-R1: Open-Weight Reasoning, Benchmark Results and a First TestMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s January 2025 release, compares reported benchmarks and prices, and tries a handful of reasoning prompts.Reasoning & test-time computeOpen-weight modelsReinforcement Learning+2
1:00:05EN
Sequoia Capital· 2025년 1월 14일팟캐스트If Someone Builds a Better Spark Product, We Deserve to LoseIon Stoica on how Databricks turned academic open source into a data-and-AI company — and which problems he thinks will matter more tomorrow than today.기업과 전략Company BuildingOpen-source ecosystems+3
3:53:49EN
Cognitive Revolution "How AI Changes Everything"· 2025년 1월 3일팟캐스트With One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4o진행자 Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.멀티모달과 미디어Multimodal AI비전과 영상+3
1:57:00EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 28일팟캐스트Less Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI First진행자 Nathan LabenzDoom Debates host Liron Shapira presses OpenAI technical staffer roon on extinction odds, alignment-by-default, and a plan that even he admits is balancing on razor wire.보안과 안전안전과 거버넌스AGI Timelines+3
27:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 12월 26일팟캐스트 · 2명After adding $100 billion a month, Jensen Huang says NVIDIA is selling the data center진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.기업과 전략AI Strategy인프라와 배포+3
슬라이드6:16EN
Matthew Berman· 2024년 12월 8일Running Stable Diffusion 3.5 with ComfyUI on a Cloud GPUMatthew Berman · Forward FutureIn a Vultr-sponsored 2024 tutorial, Matthew Berman sets up a GPU instance and generates images with ComfyUI. Licensing, security, and prices require attention beyond the demonstration.Generative media인프라와 배포Open-weight models+1
슬라이드 7장27:54EN
Matthew Berman· 2024년 12월 5일AI News in December 2024: Genie 2, World Models, MCP and New AI ReleasesMatthew Berman · Forward FutureMatthew Berman surveys early interactive world models, voice and video tools, QwQ, distributed training and Amazon’s Nova announcements.World modelsOpen-weight modelsAI agents+1
1:49:41EN
Cognitive Revolution "How AI Changes Everything"· 2024년 11월 21일팟캐스트A Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Base진행자 Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.모델과 학습Post-trainingData quality & curation+3
0:28EN
Matthew Berman· 2024년 11월 6일Comparing Three Local Coding ModelsMatthew Berman · Forward FutureMatthew Berman introduces a sponsored comparison of DeepSeek Coder V2, Yi-Coder and Qwen Coder running on a workstation.Local inference코딩 에이전트Open-weight models
슬라이드 3장11:56EN
Matthew Berman· 2024년 11월 3일IBM Granite 3.0 and InstructLab: Small Models for Enterprise AIMatthew Berman · Forward FutureMatthew Berman reviews IBM's 2024 model family and its approach to adding domain knowledge. IBM partnered on the video and invited him to its event.모델과 학습엔터프라이즈 AI파인튜닝+2
슬라이드 4장12:50EN
Matthew Berman· 2024년 11월 2일Comparing Three Local Coding Models on Games and Programming ChallengesMatthew Berman · Forward FutureMatthew Berman runs DeepSeek-Coder-V2 Lite, Yi-Coder 9B, and Qwen2.5-Coder 7B on a sponsored workstation. Their results vary by task and include manual corrections.Open-weight models평가(Evals)Software engineering+2
2:24:18EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 30일팟캐스트MMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.진행자 Nathan LabenzZyphra’s training lead walks through Zamba 2’s hybrid architecture, the evals that actually matter, and the trade secrets small labs still have to rediscover.모델과 학습Local inference평가(Evals)+3
슬라이드 6장10:39EN
Matthew Berman· 2024년 10월 29일Zamba2-7B: A Hybrid Mamba–Transformer Model Tested on Coding and ReasoningMatthew Berman · Forward FutureMatthew Berman compares Zyphra’s efficiency claims with his own informal tests, including Python games, spatial puzzles and simple word tasks.모델과 학습Open-weight modelsBenchmarks+2
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