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슬라이드 6장25:50EN
MBMatthew Berman· 2026년 10월 24일Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.Open-weight modelsBenchmarksAI cost & performance+1
슬라이드 2장32:20EN
MBMatthew 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 5장21:29EN
MBMatthew Berman· 2026년 10월 7일Mistral Large 4 Preview: European Open Weights, Cyber Benchmarks and Setup FrictionMatthew Berman · Forward FutureMatthew Berman reviews the model’s reported specifications and benchmarks, then tests it in an agent coding workflow.Open-weight modelsBenchmarksAI security+1
슬라이드 5장20:46EN
MBMatthew Berman· 2026년 8월 26일Open-Weight AI Models: Token Share, Spending and Strategic TradeoffsMatthew Berman · Forward FutureMatthew Berman examines a Vercel AI Gateway snapshot and argues that model usage and spending can tell very different stories.Open-weight modelsAI cost & performanceAI Strategy+2
슬라이드 5장52:29EN
MBMatthew Berman· 2026년 7월 24일Claude Opus 5: Benchmarks, Cost per Task, and Early ImpressionsMatthew Berman · Forward FutureMatthew Berman reacts to the model launch, examines reported benchmark and pricing data, and explains why the cost of completing a task matters more than token price alone.AnthropicBenchmarksAI cost & performance+2
슬라이드 4장27:13EN
MBMatthew Berman· 2026년 7월 21일Kimi K3 and the Debate Over Open-Weight AIMatthew Berman · Forward FutureMatthew Berman examines model economics, competition and security arguments after Moonshot AI’s Kimi K3 announcement.Open-weight modelsAI cost & performanceAI Regulation+2
슬라이드 5장1:00:47EN
MBMatthew Berman· 2026년 7월 15일AI News Live: A Codex Keyboard, Open Models and Agent Safety ResearchMatthew Berman, Alex, Brian · Forward FutureMatthew Berman, Alex and Brian discuss new tools, model costs and a research report, separating initial impressions from verified results.코딩 에이전트Open-weight modelsAI cost & performance+2
슬라이드 5장1:42:54EN
MBMatthew Berman· 2026년 5월 12일AI and Cybersecurity: Matthew Berman’s Warnings, Predictions and Open QuestionsMatthew Berman · Forward FutureA livestream reviews reported AI-assisted threats and debates whether stronger defensive models can keep pace with attackers.AI security보안과 안전AI Safety+2
1:52:38EN
MBMatthew Berman· 2025년 11월 22일Open Models, AI Infrastructure, and Search: Four PerspectivesMatthew Berman, Nick Wentz, Himanshu Tyagi, Misha Laskin, Bryan Catanzaro, Robby Stein · Forward FutureForward Future speaks with leaders from Sentient, Reflection AI, NVIDIA, and Google about openness, scaling, safety, and AI-powered search.Open-weight modelsAI Safety인프라와 배포+2
33:18EN
MBMatthew Berman· 2025년 5월 1일Zuckerberg and Nadella on AI Coding, Agents and the Next Software StackMatthew Berman, Mark Zuckerberg, Satya Nadella · Forward FutureMatthew Berman examines their 2025 LlamaCon conversation about AI-assisted development, open models and changing workflows.코딩 에이전트에이전트 엔지니어링AI Strategy+2
슬라이드 3장5:27EN
MBMatthew 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
0:28EN
MBMatthew 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 2장9:15EN
MBMatthew 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 2장35:30EN
MBMatthew Berman· 2024년 9월 6일Reflection 70B: Its Creators Explain the Proposed Self-Correction MethodMatthew Berman, Matt Shumer, Sahil Chaudhary · Forward FutureA launch-day discussion with Matt Shumer and Sahil Chaudhary covers synthetic data, selective reflection and evaluation limits.모델과 학습Data quality & curation평가(Evals)+2
슬라이드 3장13:40EN
MBMatthew Berman· 2024년 7월 29일Testing Llama 3.1 8B: Benchmark Gains and Mixed Practical ResultsMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and other prompts on the small model and finds several failures despite stronger reported benchmarks.Open-weight models평가(Evals)모델과 학습+1
슬라이드 3장16:06EN
MBMatthew Berman· 2024년 6월 18일AI News: Video Generation, Apple Intelligence, Robotics and DeepSeek Coder V2Matthew Berman · Forward FutureMatthew Berman reviews a week of launches and research, from Luma and Runway to NVIDIA, robotics and coding models.Generative mediaRoboticsOpen-weight models+1
슬라이드 4장9:53EN
MBMatthew 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 2장12:50EN
MBMatthew Berman· 2024년 5월 22일Testing Smaug: Hosted 70B Versus a Smaller Local ModelMatthew Berman · Forward FutureMatthew Berman compares two Smaug configurations on Snake, math and reasoning puzzles.Open-weight models평가(Evals)모델과 학습
슬라이드 3장15:01EN
MBMatthew Berman· 2024년 4월 19일Testing Llama 3 at Launch: Code, Reasoning and Image GenerationMatthew Berman · Forward FutureMatthew Berman tries Meta AI’s new interface on a snake game, logic puzzles and rapid image generation.Open-weight models평가(Evals)모델과 학습+1
슬라이드 3장14:23EN
MBMatthew Berman· 2024년 3월 31일Testing DBRX: Coding Strengths and Reasoning GapsMatthew Berman · Forward FutureMatthew Berman examines Databricks’ open-weight model and puts it through coding, arithmetic and reasoning prompts.Open-weight models모델과 학습평가(Evals)+1
슬라이드 4장14:11EN
MBMatthew Berman· 2024년 3월 23일LM 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.Open-weight modelsInference
슬라이드 3장23:00EN
MBMatthew Berman· 2024년 2월 22일Testing Google Gemma 7B at Launch: Setup MattersMatthew Berman · Forward FutureMatthew Berman compares local and hosted tests of Google’s early open-weight model.Open-weight models평가(Evals)모델과 학습
슬라이드 3장4:42EN
MBMatthew Berman· 2023년 10월 17일Connecting AutoGen to a Local Model With LM StudioMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup and explains where agent behavior still needs work.에이전트Open-weight models인프라와 배포
슬라이드 3장12:20EN
MBMatthew Berman· 2023년 7월 10일Testing UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.Open-weight models평가(Evals)모델과 학습+1