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17:12ENTesting 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.
12:51ENLlama 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.
12:02ENTesting 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.
13:59ENSWE-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.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%Host 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.
13:57ENMistral 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.
11:14ENGemini 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.
46:36ENAfter a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the modelHost 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.
24:54ENMatthew 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.
1:22:59ENIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%Host 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.
1:15:39ENAfter 20 Years of Frontend, v0 Wrote Better Code Than Guillermo Rauch DidHost 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.
7:48ENTesting 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.
32:48ENFourteen People, $200 Million of Compute, and the Reliability Bottleneck for AgentsHost 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.
5:31ENConnecting 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.
7:02ENConnecting 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.
15:03ENA 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.
1:32:41ENThere are maybe 5,000 people who can train frontier models. The rest need AI engineersHost 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.
7:32ENMageGPT 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.
2:17:30ENGemini Became the Daily Driver. A GPT-5 Worthy of the Name Would Make Agents Work.Host Nathan LabenzZvi Mowshowitz returns to Cognitive Revolution to unpack Gemini 1.5, Sora, superalignment, sleeper agents, and the live-player map of frontier labs.
29:38ENA Beginner Just Shipped a $250K Business. Professionals Got 30 Percent.Host 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.
9:59ENOpen 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.
6:11ENRunning 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.
10:20ENPhind 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.
1:39:53ENUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer IntelligenceHost 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.
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