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슬라이드 5장10:36EN
MBMatthew Berman· 2026년 10월 13일Meta Muse Wonder Tested: Strong Benchmarks, Mixed Demos and Quota FrictionMatthew Berman · Forward FutureMatthew Berman tests Meta’s models on browser demos and reviews their published benchmark scores, availability and cost.모델과 학습BenchmarksAI cost & performance+1
슬라이드0:24EN
MBMatthew Berman· 2026년 7월 7일Claude Fable 5 Access Extended Through July 12, 2026Matthew Berman · Forward FutureMatthew Berman reports a short extension for paid Claude subscribers, without a reset of their existing usage quota.모델과 학습
슬라이드 4장13:30EN
3Blue1Brown· 2025년 8월 17일How AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.MathematicsReasoning & test-time computeAI research+2
슬라이드 3장10:28EN
MBMatthew Berman· 2025년 8월 5일OpenAI’s gpt-oss Models: Open Weights, Benchmarks and SafetyMatthew Berman · Forward FutureMatthew Berman reviews the 120b and 20b models, local deployment claims, selected evaluations and the scope of OpenAI’s safety testing.모델과 학습AI research평가(Evals)+1
슬라이드3:13EN
MBMatthew Berman· 2025년 8월 5일Claude Opus 4.1: Anthropic’s August 2025 Benchmark UpdateMatthew Berman · Forward FutureMatthew Berman reviews the model’s reported coding, reasoning and tool-use results, including one benchmark that declined.모델과 학습평가(Evals)코딩 에이전트
슬라이드 4장12:14EN
MBMatthew Berman· 2025년 7월 16일AI News: Windsurf’s Acquisition, Meta Compute Plans, Grok and VoxtralMatthew Berman · Forward FutureA July 2025 roundup examines developer-tool deals, AI infrastructure, model behavior, reward methods and speech recognition.AI research모델과 학습에이전트+1
1:09EN
MBMatthew Berman· 2025년 7월 3일A Discussion of GPT-4.5’s Scaling and TrainingA speaker offers an assessment of GPT-4.5’s cost, speed and alleged training challenges.모델과 학습Scaling Laws
1:50EN
MBMatthew Berman· 2025년 1월 30일Five AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.엔터프라이즈 AI에이전트모델과 학습+1
0:35EN
MBMatthew Berman· 2024년 11월 6일An IBM Visit: Granite Models, InstructLab and Quantum ComputingMatthew Berman · Forward FutureMatthew Berman previews a longer discussion of IBM’s small AI models, model customization and quantum research.모델과 학습AI research
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
슬라이드0:54EN
MBMatthew Berman· 2024년 9월 16일OpenAI’s o1 Preview: A First Look at Longer ReasoningMatthew Berman · Forward FutureMatthew Berman introduces the o1-preview and o1-mini models and tries a Python game prompt.모델과 학습Inference
슬라이드 2장9:43EN
MBMatthew Berman· 2024년 8월 26일Matthew Berman Tests Jamba 1.5 on Coding and Reasoning PromptsMatthew Berman · Forward FutureA 2024 hands-on test of AI21’s hybrid model finds slow output in one hosted session and mixed answers to a small set of prompts.모델과 학습평가(Evals)
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
0:58EN
MBMatthew Berman· 2024년 7월 11일NVIDIA NIM: Containerized AI Inference MicroservicesMatthew Berman · Forward FutureA sponsored overview of NVIDIA’s approach to packaging model inference for local and cloud applications.인프라와 배포모델과 학습
슬라이드 5장13:18EN
MBMatthew 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 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 3장13:37EN
MBMatthew Berman· 2024년 5월 16일Testing Gemini 1.5 Pro’s Long Context and Video UnderstandingMatthew Berman · Forward FutureMatthew Berman’s 2024 tests show useful image and video summaries alongside blocked code and missed details.Multimodal AIBenchmarks비전과 영상+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 2장6:28EN
MBMatthew Berman· 2023년 8월 29일A Historical GPT-3.5 Fine-Tuning WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates generating synthetic examples in Colab and training a model to use a distinctive tone.파인튜닝Synthetic data모델과 학습
슬라이드 2장5:53EN
MBMatthew 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 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
슬라이드5:24EN
MBMatthew Berman· 2023년 5월 12일Google I/O 2023: Bard, PaLM 2 and AI Across Google's ProductsMatthew Berman · Forward FutureMatthew Berman reviews Google's 2023 AI announcements and weighs its focus on improving established products.AI Strategy제품과 UX모델과 학습+1
9:59EN
Lex Fridman팟캐스트Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning진행자 Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.모델과 학습머신러닝 기초Deep Learning+3
11:11EN
Lex Fridman팟캐스트 · 2명Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not General게스트 Yann Lecun · 진행자 Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.모델과 학습BenchmarksAGI(범용 인공지능)+3
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