필터 결과
278개정렬
4:35EN
Matthew Berman· 2023년 9월 5일Running WizardCoder on a Cloud GPU: A 2023 RunPod WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates downloading a quantized 13B coding model into a hosted text-generation interface, then explains how to stop the pod and avoid ongoing charges.
14:59ENMatthew Berman· 2023년 9월 2일AI News in September 2023: Tesla, Code Llama, Drone Racing and CopyrightMatthew Berman · Forward FutureMatthew Berman surveys a week of AI announcements, from Tesla's driving demonstration and ChatGPT Enterprise to model releases, generative media and a copyright inquiry.
6:11ENMatthew Berman· 2023년 8월 31일Running WizardCoder Locally with Text Generation WebUIMatthew Berman · Forward FutureMatthew Berman walks through a 2023 setup for a quantized Code Llama-based coding model, from the Python environment to a simple test prompt.
10:20ENMatthew Berman· 2023년 8월 30일Phind 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.
1:39:53EN
Cognitive Revolution "How AI Changes Everything"· 2023년 8월 8일팟캐스트Under 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligence진행자 Nathan LabenzMichele Catasta, Replit's new VP of AI, lays out a generate-execute-learn loop he will not call AGI, a 2x-to-1000x productivity ladder, and a keystroke-level data advantage.
1:45:46ENCognitive Revolution "How AI Changes Everything"· 2023년 8월 4일팟캐스트Replit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring Bots진행자 Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.
11:07ENMatthew Berman· 2023년 7월 24일Installing Llama 2 13B Chat and Testing Its ResponsesMatthew Berman · Forward FutureMatthew Berman demonstrates a 2023 local setup and tests a 13-billion-parameter chat model on coding, writing, arithmetic and reasoning. His small set of prompts illustrates both useful outputs and mistakes.
12:20ENMatthew Berman· 2023년 7월 10일Testing UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.
7:05ENMatthew Berman· 2023년 7월 2일Aider’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.
6:26ENMatthew Berman· 2023년 6월 14일Installing 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.
7:37ENMatthew Berman· 2023년 5월 25일Smol 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.
32:48ENCognitive Revolution "How AI Changes Everything"· 2023년 2월 23일팟캐스트A Hundred Million to Train, a Penny to Infer진행자 Nathan LabenzIn a February 2023 roundtable, two founders argue on mic over whether AGI ends humanity — and who actually captures the value if it does not.
1:25:13EN
Lenny's Podcast팟캐스트Codex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a Teammate진행자 Lenny RachitskyCodex product lead Alexander Embiricos explains the 20x growth, why every useful agent may need to write code, and why human review speed is the real bottleneck.
1:39:51ENLenny's Podcast팟캐스트After the Inflection Point: Simon Willison on Agentic Engineering, Dark Factories and the Coming AI Challenger Disaster진행자 Lenny RachitskyDjango co-creator Simon Willison explains what changed in November 2025, how he works with coding agents, and why prompt injection remains the field's biggest unsolved risk.
1:33:50ENLenny's Podcast팟캐스트Evals Are the New PRDs: Inside Anthropic's Research Product Team진행자 Lenny RachitskyDianne Penn, Anthropic's head of product for research and Labs, explains how the company found its identity, how her team turns user feedback into evals, and why human judgment still matters.
1:11:06EN
Unsupervised Learning: With Jacob Effron팟캐스트Replit's Amjad Masad on Building Your Own Model, Latency, and the Next Billion Software Creators진행자 Jacob EffronThe Replit founder explains why AI should be native to the product, why he trained a small in-house model, and why he thinks software engineering is about to split in two.
1:53:14ENCognitive Revolution "How AI Changes Everything"팟캐스트Worth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute Cap진행자 Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.
1:04:25ENUnsupervised Learning: With Jacob Effron팟캐스트Inside GitHub's Copilot Bet: Agents, Open Source, and Why the Developer Job Endures진행자 Jacob EffronGitHub CEO Thomas explains how Copilot went from a research bet to 1.3 million developers, and what agents, fine-tuning and a multi-model world mean for the next five years of software.
50:03ENLenny's Podcast팟캐스트Copilot Is a Copilot, Not a Pilot: Inbal Shani on the Future of AI in Software Development진행자 Lenny RachitskyGitHub's chief product officer explains what AI changes for developers, what it does not replace, and how teams should adopt it.
1:38:45ENLenny's Podcast팟캐스트When Coding Stops Being the Bottleneck: Inside Anthropic's Claude Code and Cowork Teams진행자 Lenny RachitskyFiona Fung, who leads the teams behind Claude Code and Cowork, describes how an engineering org that ships roughly eight times more code manages quality, hiring, metrics and culture.
1:36:57ENUnsupervised Learning: With Jacob Effron팟캐스트Do the Dumb Thing First: A CTO's Playbook for Building an AI Coding Assistant진행자 Jacob EffronSourcegraph CTO Beyang Liu on which AI coding features actually earn daily use, how new models get shipped and evaluated, and why retrieval is still a search problem.
1:27:45ENLenny's Podcast팟캐스트Coding Is Solved, Says the Creator of Claude Code: Boris Cherny on What Comes Next진행자 Lenny RachitskyBoris Cherny, head of Claude Code at Anthropic, on the tool's origin, the principle of latent demand, and how work changes when engineers stop writing code by hand.
1:07:48ENLenny's Podcast팟캐스트Most Productivity Metrics Are a Lie: Nicole Forsgren on Measuring Developer Experience in the AI Era진행자 Lenny RachitskyThe creator of DORA and SPACE explains why lines of code and old pipeline metrics fall short with AI, and how to start improving developer experience by listening, surveying and tying results to what leaders care about.
1:41:26ENCognitive Revolution "How AI Changes Everything"팟캐스트The AI Scouting Report, Part 3: What AI Can Already Do, Who Will Win, and Why Nathan Labenz Wants Caution on Scaling진행자 Nathan LabenzNathan Labenz closes his AP-course tour of AI with capabilities, market moats, jobs, law, safety plans and a stance on what to do next.더 보기278개 중 24개 표시