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슬라이드 2장30:29EN
Matthew Berman· 2025년 1월 3일How Researchers Think o1-Style Reasoning Models WorkMatthew Berman · Forward FutureMatthew Berman explains a research survey of policy initialization, rewards, search and reinforcement learning, and the open questions behind reasoning models.Reinforcement Learning모델과 학습AI research+1
1:07:32EN
Unsupervised Learning: With Jacob Effron· 2024년 12월 18일팟캐스트o1 Is a New Generation — and the Day AGI Arrives Will Feel Boring진행자 Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.모델과 학습Reasoning & test-time compute에이전트 엔지니어링+3
48:18EN
Unsupervised Learning: With Jacob Effron· 2024년 12월 6일팟캐스트Noam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of Headroom진행자 Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.모델과 학습Reasoning & test-time computeAGI(범용 인공지능)+3
슬라이드 7장27:54EN
Matthew Berman· 2024년 12월 5일AI News in December 2024: Genie 2, World Models, MCP and New AI ReleasesMatthew Berman · Forward FutureMatthew Berman surveys early interactive world models, voice and video tools, QwQ, distributed training and Amazon’s Nova announcements.World modelsOpen-weight modelsAI agents+1
1:49:41EN
Cognitive Revolution "How AI Changes Everything"· 2024년 11월 21일팟캐스트A Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Base진행자 Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.모델과 학습Post-trainingData quality & curation+3
슬라이드 7장14:50EN
Matthew Berman· 2024년 11월 19일AI News in November 2024: Mistral, Gemini, Nuclear Safety and Medical AIMatthew Berman · Forward FutureMatthew Berman surveys Le Chat updates, model rankings, nuclear safeguards and a diagnostic reasoning study.AI StrategyBenchmarksAI Safety+2
슬라이드 4장14:05EN
Matthew Berman· 2024년 11월 15일Test-Time Training Improves ARC Puzzle Results in an MIT StudyMatthew Berman · Forward FutureMatthew Berman explains a 2024 paper that adapts a language model to each puzzle at inference time and combines its predictions with program synthesis.AI researchReasoning & test-time computeBenchmarks+1
0:35EN
Matthew 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 3장11:56EN
Matthew Berman· 2024년 11월 3일IBM Granite 3.0 and InstructLab: Small Models for Enterprise AIMatthew Berman · Forward FutureMatthew Berman reviews IBM's 2024 model family and its approach to adding domain knowledge. IBM partnered on the video and invited him to its event.모델과 학습엔터프라이즈 AI파인튜닝+2
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 6장10:39EN
Matthew Berman· 2024년 10월 29일Zamba2-7B: A Hybrid Mamba–Transformer Model Tested on Coding and ReasoningMatthew Berman · Forward FutureMatthew Berman compares Zyphra’s efficiency claims with his own informal tests, including Python games, spatial puzzles and simple word tasks.모델과 학습Open-weight modelsBenchmarks+2
슬라이드 5장9:38EN
Matthew Berman· 2024년 10월 15일Liquid Foundation Models: Company Benchmarks and a Hands-On TestMatthew Berman · Forward FutureMatthew Berman reviews Liquid AI’s 2024 model and memory claims, then tries the 40B preview on coding, logic, and instruction-following prompts.Foundation Models평가(Evals)Benchmarks+2
1:06:48EN
Unsupervised Learning: With Jacob Effron· 2024년 10월 3일팟캐스트o1 Is Slow and Hard to Use. Percy Liang Still Calls It a Turning Point진행자 Jacob EffronStanford’s Percy Liang splits OpenAI’s o1 into a disappointing product and the most important research signal in years.모델과 학습Reasoning & test-time computeAI research+3
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
1:18:32EN
Cognitive Revolution "How AI Changes Everything"· 2024년 9월 20일팟캐스트A DNA Model That Can Tell Which Genes You Cannot Touch진행자 Nathan LabenzStanford's Brian Hie walks through hybrid architectures, a genome-scale language model trained only on DNA, and an antibody that binds 25 times tighter than nature.모델과 학습AI for scienceComputational Biology+3
슬라이드0:54EN
Matthew 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
Matthew 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)
2:04:15EN
Cognitive Revolution "How AI Changes Everything"· 2024년 8월 14일팟캐스트A parrot cannot paraphrase — and Claude cannot be talked into harm진행자 Nathan LabenzRobert Wright of the Nonzero podcast interviews Nathan Labenz on whether large language models understand anything, what Anthropic’s 10 million features actually show, and why open weights collide with U.S.–China policy.모델과 학습Model InterpretabilityMultimodal AI+3
슬라이드 6장15:24EN
Matthew Berman· 2024년 8월 13일Testing the Anonymous sus-column-r Model, Later Identified as Grok-2Matthew Berman · Forward FutureMatthew Berman tests a mysterious 2024 Arena model on coding and reasoning; its verbose answers prompted speculation about OpenAI that the later identification contradicted.모델과 학습평가(Evals)Reasoning & test-time compute+1
슬라이드 6장14:32EN
Matthew Berman· 2024년 8월 10일OpenAI Departures, Developer Tools and Synthetic Media: An August 2024 AI RoundupMatthew Berman · Forward FutureMatthew Berman reviews leadership changes, training-data disputes, structured API output, Qwen2-Math and emerging deepfake tools.AI researchGenerative mediaAI Safety+2
슬라이드 2장16:06EN
Matthew Berman· 2024년 8월 9일Q* and Strawberry: What Was Known and Speculated in August 2024Matthew Berman · Forward FutureMatthew Berman reviews contemporary rumors and research concepts around reasoning, search and self-play, while the underlying project remained undisclosed.모델과 학습AI researchAGI(범용 인공지능)
슬라이드 3장13:40EN
Matthew 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 5장10:02EN
Matthew Berman· 2024년 7월 24일Testing Llama 3.1 405B on Coding, Arithmetic and ReasoningMatthew Berman · Forward FutureMatthew Berman tries Meta's 2024 open-weight model on an informal set of prompts and demonstrates a sponsored dataset workflow.Open-weight models모델과 학습평가(Evals)+1
슬라이드 4장15:50EN
Matthew Berman· 2024년 7월 23일Llama 3.1: Meta’s 405B Model and the Open-Weight EcosystemMatthew Berman · Forward FutureMatthew Berman reviews Meta’s July 2024 release, the smaller models, reported benchmarks, synthetic data and the proposed Llama Stack.Open-weight models모델과 학습Benchmarks+2
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