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슬라이드 2장32:20EN
Matthew Berman· 2026년 10월 23일Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.Local inferenceOpen-weight modelsAI cost & performance+1
슬라이드 4장9:15EN
Matthew Berman· 2026년 8월 17일Six Open-Source Projects for Local AI, Agents, and 3D DesignMatthew Berman · Forward FutureMatthew Berman tours tools for running and training models, giving agents new skills, coordinating work, browsing, and generating 3D meshes.Open-source ecosystemsAgent skillsLocal inference+2
1:04:14EN
Unsupervised Learning: With Jacob Effron· 2026년 7월 31일팟캐스트The Man Who Helped Stand Up Colossus in 120 Days Is Betting on an AI That Lives in Your House진행자 Jacob EffronxAI co-founder Igor Babuschkin left to start River AI, arguing coding agents have crossed a threshold, closed labs are getting squeezed, and the next prize is personal, local intelligence.에이전트AI startups & small teamsCompany Building+3
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026년 7월 4일팟캐스트19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip진행자 Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.모델과 학습Local inferenceScaling Laws+3
슬라이드 5장9:47EN
Matthew Berman· 2026년 4월 3일Gemma 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.Open-weight modelsLocal inferenceFoundation Models+2
슬라이드 4장18:09EN
Matthew Berman· 2025년 12월 15일Training 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.Reinforcement LearningPost-trainingOpen-weight models+2
1:32:38EN
Cognitive Revolution "How AI Changes Everything"· 2025년 12월 6일팟캐스트Polish Is 1% of Frontier Training Data, So Poland Built Its Own Model진행자 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.기업과 전략Open-weight modelsData quality & curation+3
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
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 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
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
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 9장19:03EN
Matthew Berman· 2024년 10월 30일AI News in October 2024: Apple Intelligence, Coding Assistants, Search, and AgentsMatthew Berman · Forward FutureMatthew Berman reviews the first Apple Intelligence release, new coding tools, AI search disputes, local models, and reports of browser agents.AI agentsAI Adoption코딩 에이전트+2
슬라이드 6장23:29EN
Matthew Berman· 2024년 10월 19일AI News in October 2024: Swarm, Blackwell, Video Models and Edge AIMatthew Berman · Forward FutureMatthew Berman reviews a wide range of announcements, including OpenAI’s experimental agent framework and new models from NVIDIA and Mistral.AI agentsSemiconductorsGenerative media+2
슬라이드 2장9:15EN
Matthew Berman· 2024년 9월 25일Llama 3.2 Adds Vision and Smaller On-Device ModelsMatthew Berman · Forward FutureIn a Meta-partnered 2024 video, Matthew Berman reviews the model family, its tooling and a brief hosted 1B demonstration.Open-weight modelsMultimodal AILocal inference+1
슬라이드 2장1:00EN
Matthew Berman· 2024년 8월 8일NVIDIA AI Resources for STEM StudentsMatthew Berman · Forward FutureIn a partnered short, Matthew Berman points students to learning, model development, robotics and local document tools.AI in EducationRoboticsLocal inference
1:16:11EN
Cognitive Revolution "How AI Changes Everything"· 2024년 7월 11일팟캐스트Scooping Food Into Boxes Is 70 Percent of Plant Labor진행자 Nathan LabenzChef Robotics CEO Rajat Bhageria on 20 million plated meals, a foundation model for food, and why the kitchen may leave the house.RoboticsData quality & curationLocal inference+3
슬라이드 4장8:53EN
Matthew Berman· 2024년 7월 8일RouteLLM: Routing Queries Between Strong and Cheaper ModelsMatthew Berman · Forward FutureMatthew Berman explains a 2024 research framework that uses preference data to choose a model for each query.Model routing & gatewaysAI cost & performance평가(Evals)+2
슬라이드 5장13:18EN
Matthew Berman· 2024년 6월 20일Testing 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.Local inferenceInference모델과 학습+2
슬라이드 6장17:03EN
Matthew Berman· 2024년 6월 8일Qwen2 0.5B and 72B: A Hands-On ComparisonMatthew Berman · Forward FutureMatthew Berman tests coding, arithmetic and reasoning prompts on the smallest and largest Qwen2 models in a 2024 demonstration.Open-weight modelsBenchmarksLocal inference+2
슬라이드 4장9:53EN
Matthew Berman· 2024년 5월 28일Testing Microsoft Phi-3 Medium Locally: Mixed Coding and Reasoning ResultsMatthew Berman · Forward FutureMatthew Berman runs a quantized Phi-3 Medium on a MacBook and explores coding, arithmetic and reasoning prompts.Open-weight modelsLocal inferenceBenchmarks+1
슬라이드 7장21:47EN
Matthew Berman· 2024년 4월 24일Phi-3 Mini: Microsoft’s Small Model, Phone Deployment and an Uncertain Local TestMatthew Berman · Forward FutureMatthew Berman reviews Microsoft’s 2024 technical report and runs informal prompts, with an unresolved model label in the demonstration.Local inference모델과 학습Benchmarks+1
슬라이드9:19EN
Matthew Berman· 2024년 3월 28일Trying an Open-Source Answer Engine with Groq and OllamaMatthew Berman · Forward FutureMatthew Berman installs a Perplexity-inspired search app, demonstrates a hosted-model configuration and attempts an unfinished local-model integration.Search & retrievalLocal inferenceOpen Source+2
슬라이드 5장9:25EN
Matthew Berman· 2024년 1월 31일Matthew Berman Tests Meta’s Code Llama 70B on a Snake GameMatthew Berman · Forward FutureA 2024 look at Meta’s coding-model release, a SQL-focused fine-tune and a hands-on test that did not work on the first attempt.Open-weight modelsSoftware engineeringBenchmarks+2
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