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5 slides10:36EN
MBMatthew Berman· Oct 13, 2026Meta 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.Models & trainingBenchmarksAI cost & performance+1
Slides0:24EN
MBMatthew Berman· Jul 7, 2026Claude 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.Models & training
4 slides13:30EN
3Blue1Brown· Aug 17, 2025How 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
3 slides10:28EN
MBMatthew Berman· Aug 5, 2025OpenAI’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.Models & trainingAI researchEvals+1
Slides3:13EN
MBMatthew Berman· Aug 5, 2025Claude 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.Models & trainingEvalsCoding agents
4 slides12:14EN
MBMatthew Berman· Jul 16, 2025AI 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 researchModels & trainingAgents+1
1:09EN
MBMatthew Berman· Jul 3, 2025A Discussion of GPT-4.5’s Scaling and TrainingA speaker offers an assessment of GPT-4.5’s cost, speed and alleged training challenges.Models & trainingScaling Laws
1:50EN
MBMatthew Berman· Jan 30, 2025Five AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.Enterprise AIAgentsModels & training+1
0:35EN
MBMatthew Berman· Nov 6, 2024An 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.Models & trainingAI research
2 slides9:15EN
MBMatthew Berman· Sep 25, 2024Llama 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
Slides0:54EN
MBMatthew Berman· Sep 16, 2024OpenAI’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.Models & trainingInference
2 slides9:43EN
MBMatthew Berman· Aug 26, 2024Matthew 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.Models & trainingEvals
3 slides13:40EN
MBMatthew Berman· Jul 29, 2024Testing 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 modelsEvalsModels & training+1
0:58EN
MBMatthew Berman· Jul 11, 2024NVIDIA NIM: Containerized AI Inference MicroservicesMatthew Berman · Forward FutureA sponsored overview of NVIDIA’s approach to packaging model inference for local and cloud applications.Infrastructure & deploymentModels & training
2 slides12:50EN
MBMatthew Berman· May 22, 2024Testing Smaug: Hosted 70B Versus a Smaller Local ModelMatthew Berman · Forward FutureMatthew Berman compares two Smaug configurations on Snake, math and reasoning puzzles.Open-weight modelsEvalsModels & training
3 slides14:23EN
MBMatthew Berman· Mar 31, 2024Testing 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 modelsModels & trainingEvals+1
2 slides6:28EN
MBMatthew Berman· Aug 29, 2023A 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.Fine-tuningSynthetic dataModels & training
3 slides12:20EN
MBMatthew Berman· Jul 10, 2023Testing 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 modelsEvalsModels & training+1
Slides5:24EN
MBMatthew Berman· May 12, 2023Google 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 StrategyProduct & UXModels & training+1
9:59EN
Lex FridmanPodcastIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine LearningHost 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.Models & trainingML fundamentalsDeep Learning+3
11:11EN
Lex FridmanPodcast · 2 speakersYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralGuest Yann Lecun · Host 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.Models & trainingBenchmarksAGI+3
10:16EN
Lex FridmanPodcast · 2 speakersReasoning Without Logic: Yann LeCun on Teaching Neural Networks to ThinkGuest Yann Lecun · Host Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.Models & trainingML fundamentalsDeep Learning+3
13:58EN
Lex FridmanPodcastDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoHost Lex FridmanDavid Silver of DeepMind walks through what reinforcement learning is, how its building blocks fit together, and why deep neural networks keep surprising even the experts.Models & trainingReinforcement LearningML fundamentals+3
10:34EN
Lex FridmanPodcast · 2 speakersWhy Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AIGuest François Chollet · Host Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.Models & trainingML fundamentalsDeep Learning+2
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