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243 件
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スライド 6 枚10:57EN
Matthew Berman· 2024年6月24日Testing Claude 3.5 Sonnet: Coding, Reasoning, and VisionMatthew Berman · Forward FutureMatthew Berman puts Anthropic’s June 2024 model through informal coding, math, puzzle, and image-understanding prompts.評価(Evals)コーディングエージェントMultimodal AI+2
27:37EN
Matthew Berman· 2024年6月17日Leo Pekelis on Extending Llama 3 to a Million-Token ContextMatthew Berman, Leo Pekelis · Forward FutureGradient’s chief scientist explains long-context training, coding use cases, inference costs and why retrieval benchmarks tell only part of the story.コンテキストエンジニアリングモデルと学習Inference+2
スライド 6 枚17:03EN
Matthew Berman· 2024年6月8日Qwen2 0.5B and 72B: A Hands-On ComparisonMatthew Berman · Forward FutureMatthew Berman tests coding, arithmetic and reasoning prompts on the smallest and largest Qwen2 models in a 2024 demonstration.Open-weight modelsBenchmarksLocal inference+2
スライド 4 枚25:00EN
Matthew Berman· 2024年5月23日Microsoft 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
29:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年5月2日ポッドキャスト · 2 人Devin Will Not Replace Engineers. It Will Multiply Them, Says Cognition’s Scott Wuホスト Sarah Guo, Elad GilThe IOI champion behind Devin explains why an AI software engineer that you can watch over the shoulder creates more human engineers, not fewer.コーディングエージェントエージェント工学Developer productivity+3
スライド 4 枚17:12EN
Matthew Berman· 2024年4月30日Testing the Mystery 'gpt2-chatbot' Model in April 2024Matthew Berman · Forward FutureMatthew Berman tries an anonymous model on coding, arithmetic and reasoning tasks while its identity remains uncertain.Benchmarksモデルと学習コーディングエージェント+1
スライド 5 枚12:51EN
Matthew Berman· 2024年4月21日Llama 3 70B on Groq: Fast Inference and an Informal Prompt TestMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and repeated prompts on Groq’s April 2024 Llama 3 service, with mixed results and several scoring caveats.Open-weight modelsInference評価(Evals)+2
スライド 7 枚13:59EN
Matthew Berman· 2024年4月5日SWE-agent Tutorial: Navigating Repositories and Attempting GitHub FixesMatthew Berman, Carlos · Forward FutureMatthew Berman sets up a research coding agent, hits an installation problem and a cost limit, then shows an author’s successful SymPy benchmark example.コーディングエージェントエージェント工学開発ワークフローとテスト+2
1:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2024年3月12日ポッドキャストWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%ホスト Nathan LabenzItamar Friedman argues that completion is already a commodity, that code integrity is where AI still lags, and that flow engineering—not fancier prompts—is how GPT-4 doubled its score on coding contests.コーディングエージェント開発ワークフローとテストCode review & verification+3
スライド 5 枚13:57EN
Matthew Berman· 2024年2月27日Mistral Large: A 2024 Review of Coding, Reasoning and Safety ResponsesMatthew Berman · Forward FutureMatthew Berman reviews Mistral’s launch claims and tests the model with a small set of prompts.モデルと学習BenchmarksAI Safety+1
スライド 5 枚11:14EN
Matthew Berman· 2024年2月8日Gemini Advanced and Ultra 1.0: A First Look and Hands-On TestMatthew Berman · Forward FutureIn February 2024, Matthew Berman reviews Google’s Bard rebrand and tests its new paid Gemini experience on coding, logic and image recognition.GeminiFoundation Modelsコーディングエージェント+2
46:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年1月18日ポッドキャスト · 2 人After a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the modelホスト Sarah Guo, Elad GilBeyang Liu on Cody, why keyword search still does most of RAG, and why CS fundamentals get more valuable as AI compresses the middleware.コーディングエージェント検索拡張生成(RAG)コンテキストエンジニアリング+3
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023年12月2日ポッドキャストIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%ホスト Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.エージェントエージェント工学Reasoning & test-time compute+3
1:15:39EN
Cognitive Revolution "How AI Changes Everything"· 2023年11月29日ポッドキャストAfter 20 Years of Frontend, v0 Wrote Better Code Than Guillermo Rauch Didホスト Nathan LabenzThe Vercel CEO tells Nathan Labenz why every product needs ghost text, why Software 2.0 will ossify the old stack, and why betting against open source is still the expensive mistake.コーディングエージェントVibe Coding開発ワークフローとテスト+3
スライド 4 枚7:48EN
Matthew Berman· 2023年11月26日Testing Dolphin 2.2 Yi 34B on Coding and Reasoning TasksMatthew Berman · Forward FutureMatthew Berman runs a quantized Yi fine-tune through informal coding, writing and logic prompts in November 2023, with uneven results.Open-weight modelsFoundation ModelsBenchmarks+2
32:48EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年11月16日ポッドキャスト · 2 人Fourteen People, $200 Million of Compute, and the Reliability Bottleneck for Agentsホスト Sarah Guo, Elad GilImbue co-founders Kanjun Qiu and Josh Albrecht on why agents fail, why language models cannot learn general algorithms, and why they are spending a giant round on GPUs rather than headcount.エージェントコーディングエージェントエージェント工学+3
スライド 3 枚5:31EN
Matthew Berman· 2023年10月30日Connecting MemGPT to AutoGen AgentsMatthew Berman · Forward FutureIn a 2023 tutorial, Matthew Berman configures a MemGPT-backed coding agent alongside an AutoGen product manager and runs a short group chat.Agent memoryMulti-agent systemsコーディングエージェント
スライド 4 枚7:02EN
Matthew Berman· 2023年10月18日Connecting AutoGen to a RunPod-Hosted Model with Text Generation WebUIMatthew Berman · Forward FutureIn a 2023 walkthrough, Matthew Berman connects AutoGen to Dolphin 2.1 Mistral 7B through an OpenAI-compatible API and tests a small coding task.エージェント工学Open-weight modelsMulti-agent systems+2
スライド 5 枚15:03EN
Matthew Berman· 2023年10月10日A 2023 AutoGen Tutorial: Local Agent Setup and Code ExecutionMatthew Berman · Forward FutureMatthew Berman builds a local assistant and user-proxy workflow, then tests how the agents generate and run Python. AutoGen’s packages and APIs have changed since this tutorial.Multi-agent systemsエージェント工学コーディングエージェント+2
1:32:41EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月5日ポッドキャストThere are maybe 5,000 people who can train frontier models. The rest need AI engineersホスト Nathan LabenzSwyx of Latent Space tells Nathan Labenz how a new job is forming, why OpenAI will Sherlock its developers, and what still does not count as an agent.企業と戦略エージェント工学コーディングエージェント+3
スライド 3 枚7:32EN
Matthew Berman· 2023年10月4日MageGPT Generates a Wasp To-Do App: A 2023 DemonstrationMatthew Berman · Forward FutureMatthew Berman uses a Wasp-sponsored app generator to build, run and deploy a basic full-stack to-do app.コーディングエージェントSoftware engineering開発ワークフローとテスト
2:17:30EN
Cognitive Revolution "How AI Changes Everything"· 2023年9月29日ポッドキャストGemini Became the Daily Driver. A GPT-5 Worthy of the Name Would Make Agents Work.ホスト Nathan LabenzZvi Mowshowitz returns to Cognitive Revolution to unpack Gemini 1.5, Sora, superalignment, sleeper agents, and the live-player map of frontier labs.企業と戦略AI StrategyProduct Strategy+3
29:38EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年9月21日ポッドキャスト · 2 人A Beginner Just Shipped a $250K Business. Professionals Got 30 Percent.ホスト Sarah Guo, Elad GilReplit CEO Amjad Masad on Ghostwriter, why a 3-billion-parameter model was enough, and the agents he wants earning bounties while you sleep.コーディングエージェントDeveloper productivityOpen-weight models+3
スライド 4 枚9:59EN
Matthew Berman· 2023年9月7日Open Interpreter: A 2023 Local Code-Execution WalkthroughMatthew Berman · Forward FutureMatthew Berman installs Open Interpreter, analyzes local files with GPT-4 and tries a local Code Llama setup, with mixed results.コーディングエージェントLocal inference開発ワークフローとテスト+2
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