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48:30EN
20VC with Harry Stebbings· 2024년 11월 29일팟캐스트 · 2명Guy Podjarny on AI Coding Tools and the Future of Software Development게스트 Guy Podjarny · 진행자 Harry StebbingsThe Tessl CEO examines coding assistants, agentic development, security and the business choices surrounding AI.코딩 에이전트Software engineeringAI startups & small teams+2
0:28EN
Matthew Berman· 2024년 11월 6일Comparing Three Local Coding ModelsMatthew Berman · Forward FutureMatthew Berman introduces a sponsored comparison of DeepSeek Coder V2, Yi-Coder and Qwen Coder running on a workstation.Local inference코딩 에이전트Open-weight models
슬라이드 9장19:03EN
Matthew Berman· 2024년 10월 30일AI News in October 2024: Apple Intelligence, Coding Assistants, Search, and AgentsMatthew Berman · Forward FutureMatthew Berman reviews the first Apple Intelligence release, new coding tools, AI search disputes, local models, and reports of browser agents.AI agentsAI Adoption코딩 에이전트+2
1:19:00EN
20VC with Harry Stebbings· 2024년 10월 7일팟캐스트 · 2명Eiso Kant on Poolside, Compute and AI for Software Development게스트 Eiso Kant · 진행자 Harry StebbingsPoolside’s CTO explains code-execution feedback, the cost of model development and his company’s ambitions in the AI race.AI research코딩 에이전트모델과 학습+2
2:29:04EN
Lex Fridman· 2024년 10월 6일팟캐스트 · 2명Keep the Programmer in the Driver's Seat: Cursor's Founders on Tab, Agents, and Zero-Entropy Editing게스트 Cursor Team · 진행자 Lex FridmanMichael Truell, Aman Sanger, Sualeh Asif, and Arvid Lunnemark tell Lex Fridman why they forked VS Code, how Tab and Apply actually work, and why most programming still needs a human iterating in real time.코딩 에이전트개발 워크플로와 테스트AI interface design+3
슬라이드 7장15:00EN
Matthew Berman· 2024년 10월 4일Matthew Berman Tests the First ChatGPT Canvas BetaMatthew Berman · Forward FutureA 2024 walkthrough explores side-by-side code and writing edits, unexpected shortcut behavior and platform risk for AI developers.OpenAI제품과 UXHuman-AI Collaboration+1
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 2일팟캐스트30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Think진행자 Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.코딩 에이전트에이전트 엔지니어링파인튜닝+3
슬라이드 6장1:31:56EN
Matthew Berman· 2024년 9월 12일Testing OpenAI o1 on Puzzles, Code and Reasoning: A Launch-Day LivestreamMatthew Berman · Forward FutureMatthew Berman tries o1-preview and o1-mini on word counts, Tetris, physical reasoning and a word puzzle, with viewers checking the results.평가(Evals)코딩 에이전트
51:15EN
Sequoia Capital· 2024년 9월 10일팟캐스트AGI Has One Problem Left: Spend a Million Times More on a TokenMagic founder Eric Steinberger tells Sequoia’s Training Data why he trains his own models, why a software engineer is the MVP of AGI, and why 96% still is not a colleague.코딩 에이전트AGI(범용 인공지능)Reasoning & test-time compute+3
37:47EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 8월 30일팟캐스트 · 2명Working Backwards from AGI: Magic's Five-Million-Token Bet진행자 Sarah Guo, Elad GilEric Steinberger wants a coding colleague you trust like a teammate — and a world that is still a good place thirty years after AGI.코딩 에이전트컨텍스트 엔지니어링Inference+3
슬라이드 3장1:30:24EN
Matthew Berman· 2024년 8월 30일Daniel Miessler and Matthew Berman on AI Privacy, Coding, and Generated WorldsMatthew Berman, Daniel Miessler, Melissa, Alex · Forward FutureA 2024 live conversation explores Recall, open models, AI-assisted programming, a Doom simulator and questions about security, energy and employment.에이전트보안과 안전코딩 에이전트+2
1:07:34EN
Sequoia Capital· 2024년 8월 6일팟캐스트GitHub Didn’t Believe Copilot Was Writing 25% of the CodeThomas Dohmke tells Sequoia how an unplanned GPT-3 experiment became Copilot, why GitHub still will not train its own foundation model, and how he wants a billion people writing software by 2030.코딩 에이전트Company BuildingDeveloper productivity+3
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
25:56EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 7월 11일팟캐스트 · 2명A Prompt Cannot Hold a Good Design: Six AI Practitioners at Midyear 2024진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil stitch together clips from Stripe, Figma, Figure, OpenAI's Sora team, Cognition, and Scale into a half-year snapshot of what people actually shipping AI were willing to claim.기업과 전략AI Strategy평가(Evals)+3
59:11EN
Sequoia Capital· 2024년 6월 25일팟캐스트Don't Train a Model. Factory's Founders Say Go Dig for GoldMatan Grinberg and Eno Reyes tell Sequoia's Training Data why they sell a fleet of job-specific droids on top of other people's models — and how that stack just took SWE-bench from 14% to 19%.코딩 에이전트에이전트 엔지니어링평가(Evals)+3
슬라이드 6장10:57EN
Matthew Berman· 2024년 6월 24일Testing 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.평가(Evals)코딩 에이전트Multimodal AI+2
슬라이드 6장17:03EN
Matthew Berman· 2024년 6월 8일Qwen2 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
슬라이드 4장25:00EN
Matthew Berman· 2024년 5월 23일Microsoft 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· 2024년 5월 2일팟캐스트 · 2명Devin Will Not Replace Engineers. It Will Multiply Them, Says Cognition’s Scott Wu진행자 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.코딩 에이전트에이전트 엔지니어링Developer productivity+3
슬라이드 4장17:12EN
Matthew Berman· 2024년 4월 30일Testing 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.Benchmarks모델과 학습코딩 에이전트+1
슬라이드 7장13:59EN
Matthew Berman· 2024년 4월 5일SWE-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.코딩 에이전트에이전트 엔지니어링개발 워크플로와 테스트+2
1:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2024년 3월 12일팟캐스트Writing Code Is Only 30% of the Job. CodiumAI Wants the Other 70%진행자 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.코딩 에이전트개발 워크플로와 테스트Code review & verification+3
46:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 1월 18일팟캐스트 · 2명After a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the model진행자 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.코딩 에이전트검색 증강 생성(RAG)컨텍스트 엔지니어링+3
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023년 12월 2일팟캐스트If Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%진행자 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.에이전트에이전트 엔지니어링Reasoning & test-time compute+3
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