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214 件
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スライド 3 枚22:27EN
Jane Street· 2024年2月7日How OCaml Infers LocalityRichard Eisenberg · Jane StreetA look at local and global mode inference, module signatures, mode crossing for integers, and conversions between function types.Programming LanguagesSoftware engineering
スライド 5 枚15:17EN
Jane Street· 2024年1月31日OCaml Locals, Modes, and SubmodingRichard Eisenberg · Jane StreetA worked explanation of how local and global modes control escaping values, and how those modes interact with function types.Programming LanguagesSoftware engineering
スライド 5 枚9:25EN
Matthew Berman· 2024年1月31日Matthew Berman Tests Meta’s Code Llama 70B on a Snake GameMatthew Berman · Forward FutureA 2024 look at Meta’s coding-model release, a SQL-focused fine-tune and a hands-on test that did not work on the first attempt.Open-weight modelsSoftware engineeringBenchmarks+2
スライド 3 枚7:20EN
Matthew Berman· 2024年1月30日Using Cody and Ollama for Local Code CompletionMatthew Berman · Forward FutureIn a sponsored 2024 tutorial, Matthew Berman sets up Code Llama 7B for Cody autocomplete and demonstrates additional hosted coding features.Developer productivityLocal inferenceOpen-weight models+1
スライド 7 枚12:52EN
Jane Street· 2024年1月23日OCaml Local Variables, Return Values and RegionsRichard Eisenberg · Jane StreetA worked example shows how `local_` and `exclave_` let a function accept a local value and return a local structure in its caller's region.Programming LanguagesSoftware engineering
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 4 枚8:52EN
Jane Street· 2024年1月5日Introducing Local Parameters in OCamlRichard Eisenberg · Jane StreetA demonstration of how Jane Street's experimental local mode restricts escaping values and makes function interfaces easier to reason about.Programming LanguagesSoftware engineering
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
55:34EN
Jane Street· 2023年11月29日Andrew Hunter on Performance Engineering for Low-Latency SystemsYaron Minsky, Andrew Hunter · Jane StreetWhy small optimizations pay at hyperscale, why trading latency is harder to measure, and how profiling, tracing, language design and hardware fit together.Software engineeringオブザーバビリティと信頼性Programming Languages+2
スライド 3 枚10:37EN
Matthew Berman· 2023年11月17日Testing DeepSeek Coder on Forms, Bugs and a Snake GameMatthew Berman · Forward FutureMatthew Berman puts the 2023 coding model through a small hands-on rubric, from JSON and unit tests to a playable game.Software engineering開発ワークフローとテストOpen-weight models+1
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
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
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 5 枚10:20EN
Matthew Berman· 2023年8月30日Phind Code Llama 34B vs GPT-4: A 2023 Python Coding TestMatthew Berman · Forward FutureMatthew Berman compares a quantized Phind fine-tune with GPT-4 on games, short functions and refactoring, with mixed results.Open-weight modelsコーディングエージェント評価(Evals)+2
スライド 6 枚9:55EN
Matthew Berman· 2023年7月14日Building AI Characters With the a16z Companion AppMatthew Berman · Forward FutureMatthew Berman walks through a 2023 starter project for conversational characters, from service configuration and embeddings to editing a companion’s personality.AI agentsSoftware engineering検索拡張生成(RAG)+1
スライド 3 枚7:05EN
Matthew Berman· 2023年7月2日Aider’s Early Coding Assistant: Snake and an Existing Rails ProjectMatthew Berman · Forward FutureMatthew Berman demonstrates the terminal tool’s 2023 workflow, from generating and iterating on a game to proposing a dependency change in a repository.コーディングエージェント開発ワークフローとテストSoftware engineering+1
2:21EN
Jane Street· 2023年6月30日Varun on Software Engineering at Jane StreetVarun · Jane StreetA London-based developer describes useful technical foundations, OCaml training and team matching at Jane Street.Software engineeringCareersCompany Culture
スライド 5 枚59:36EN
Matthew Berman· 2023年6月27日Pascal Pfeiffer on Retrieval, Open Models, Kaggle and Fine-Tuning with H2O LLM StudioMatthew Berman, Pascal Pfeiffer · Forward FutureIn a 2023 interview, H2O.ai’s Pascal Pfeiffer explains document retrieval and parameter-efficient fine-tuning, reflects on Kaggle competitions and demonstrates LLM Studio. He and Matthew Berman also consider coding assistants and unverified rumors about model architecture.ファインチューニング検索拡張生成(RAG)Open-weight models+2
スライド 3 枚8:17EN
Matthew Berman· 2023年6月22日Using OpenLLM to Serve Open Models Through an APIMatthew Berman · Forward FutureMatthew Berman demonstrates a local model server, its interactive API and a Python client in a 2023 walkthrough.Open-weight modelsInferenceインフラとデプロイ+1
スライド 7 枚4:36EN
Matthew Berman· 2023年6月20日Testing WizardCoder 15B as a Local Coding AssistantMatthew Berman · Forward FutureMatthew Berman runs the 2023 WizardCoder model locally, testing small Python exercises and a longer Snake game.モデルと学習Local inferenceSoftware engineering+2
スライド 4 枚6:26EN
Matthew Berman· 2023年6月14日Installing and Trying GPT-Engineer: A 2023 Snake Game WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates the early project-generation workflow, from a Conda environment and prompt to clarification questions and generated Python files.コーディングエージェント開発ワークフローとテストSoftware engineering
3:34:03EN
Lex Fridman· 2023年6月2日ポッドキャスト · 2 人Python Isn't Finished: Chris Lattner on Mojo and the Hardware Messゲスト Chris Lattner · ホスト Lex FridmanThe LLVM creator returns to Lex Fridman to argue that Python should grow C-like performance instead of forcing people out of the language.インフラとデプロイAI platform engineeringSoftware engineering+3
スライド 5 枚7:37EN
Matthew Berman· 2023年5月25日Smol Developer: Generating a Small Python Project From a PromptMatthew Berman · Forward FutureMatthew Berman walks through a 2023 project generator, from a simple Ruby example to a multi-file ChatGPT API program.Software engineeringコーディングエージェントDeveloper productivity+1
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