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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
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
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
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 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 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 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 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 4장25:00EN
Matthew Berman· 2024년 5월 23일Microsoft Build 2024: Copilot+ PCs, Phi-3 and AI DemosMatthew Berman, Satya Nadella, Sam Altman, Seth Juarez · Forward FutureMatthew Berman reviews selected Microsoft keynote announcements, product demonstrations and a conversation with Sam Altman.AI platform engineeringLocal inferenceMultimodal AI+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
슬라이드 2장0:42EN
Matthew Berman· 2024년 1월 31일LLaVA 1.6 Adds Higher-Resolution Image UnderstandingMatthew Berman · Forward FutureMatthew Berman reviews the January 2024 release of LLaVA 1.6 and its local availability through Ollama.Multimodal AI모델과 학습Local inference+1
슬라이드 2장5:53EN
Matthew Berman· 2023년 7월 18일Petals: 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.Distributed training & inferenceLocal inferenceInference+2
슬라이드 7장4:36EN
Matthew Berman· 2023년 6월 20일Testing WizardCoder 15B as a Local Coding AssistantMatthew Berman · Forward FutureMatthew Berman runs the 2023 WizardCoder model locally, testing small Python exercises and a longer Snake game.모델과 학습Local inferenceSoftware engineering+2
슬라이드 2장10:40EN
Matthew Berman· 2023년 6월 7일Testing Nous Hermes 13B Locally: Mixed Reasoning and Unsafe ResponsesMatthew Berman · Forward FutureMatthew Berman compares a 2023 quantized model on hosted and local hardware, with uneven results across coding, logic and safety.Open-weight modelsLocal inferenceBenchmarks+1
1:13:52EN
Matthew Berman· 2023년 4월 15일Andriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.Local inferenceOpen-weight modelsData quality & curation+2