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326 件
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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
スライド 6 枚20:00EN
Matthew Berman· 2024年5月7日GitHub Copilot Workspace, Amazon Q and Sam Altman on AI’s Next StepsMatthew Berman, Sam Altman · Forward FutureA May 2024 roundup examines task-centered coding assistants, Rabbit R1, AI infrastructure, generated video and voice cloning.コーディングエージェント開発ワークフローとテストエンタープライズ 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 5 枚15:35EN
Matthew Berman· 2024年4月18日Meta Llama 3 Launch: Benchmarks, a Snake Test and the Meta AI AssistantMatthew Berman · Forward FutureMatthew Berman reviews the April 2024 release, tries a generated game and considers what downloadable models mean for developers.Open-weight modelsモデルと学習Benchmarks+2
スライド 7 枚12:02EN
Matthew Berman· 2024年4月13日Testing Karasu Mixtral 8x22B on Coding and Reasoning TasksMatthew Berman · Forward FutureMatthew Berman tries an early community fine-tune of Mistral's large mixture-of-experts model on a Snake game, arithmetic and logic puzzles.Open-weight modelsモデルと学習評価(Evals)+1
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
スライド 4 枚14:58EN
Matthew Berman· 2024年3月30日OpenDevin’s Early Coding Agent: A 2024 Installation and DemoMatthew Berman · Forward FutureMatthew Berman installs an early open-source coding-agent project and tries a calculator and a simple web page, while encountering setup and browser issues.コーディングエージェントエージェント工学Software engineering+1
スライド 6 枚19:51EN
Matthew Berman· 2024年3月15日Devin’s 2024 Launch: Coding-Agent Demos and Benchmark ClaimsMatthew Berman, Scott Wu, Neal, Walden · Forward FutureMatthew Berman examines Cognition’s software-agent demonstrations, interface and SWE-bench comparison alongside earlier coding projects.コーディングエージェントSoftware engineeringBenchmarks+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
スライド 5 枚24:54EN
Matthew Berman· 2023年12月22日Matthew Berman's 2023 Prediction for AI and the Future of ProgrammingMatthew Berman, Matt Welsh, McKay Wrigley · Forward FutureBerman argues that natural-language interfaces and AI agents could transform software development, while acknowledging the limits of coding tools and his uncertain timeline.Software engineeringコーディングエージェントHuman-AI Collaboration+2
スライド 5 枚17:08EN
Matthew Berman· 2023年12月21日Building and Testing a Login App With GPT PilotMatthew Berman · Forward FutureMatthew Berman demonstrates the 2023 VS Code workflow for AI-assisted planning, coding and debugging an authentication prototype.コーディングエージェント開発ワークフローとテストAI security+1
0:29EN
Matthew Berman· 2023年12月20日A ServiceNow Partner Demonstrates AI-Assisted Code GenerationMatthew Berman · Forward FutureA short promotional demonstration shows code generated from a natural-language instruction in ServiceNow.Developer productivityコーディングエージェント
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
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