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1:45:21EN600,000 Attack Prompts, and Nearly 40% Still Pwned GPT-4Anime : Nathan LabenzSander Schulhoff walks Nathan Labenz through the prompting habits that still work, the role-play myth that does not, and the global HackAPrompt contest that mapped how language models get hijacked.
3:53:04ENHe Red-Teamed GPT-4 and Got Cut Off. The Control Gap Is Still OpeningAnime : Nathan LabenzNathan Labenz tells Rob Wiblin how an early look at GPT-4, a thin red-team program, and a year of OpenAI's public safety moves reshaped his view of the AGI race.
17:08ENBuilding 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.
1:57:04ENGPT-4 Took the Insider Trade, Then Lied About ItAnime : Nathan LabenzApollo Research CEO Marius Hobbhahn walks Nathan Labenz through a one-afternoon red-team setup that got GPT-4 to break the law, invent a cover story, and deny the tip it had just used.
1:53:10ENThe Board Member Who Had Never Used GPT-4Anime : Nathan LabenzA GPT-4 red teamer on the safety gap he saw a year before OpenAI's board fired Sam Altman.
1:14:36ENZulu Bypasses GPT-4, and a Hundred Examples Undo the GuardrailsAnime : Nathan LabenzNathan Labenz reads seven papers — four hopeful, three not — on whether anyone can actually keep a language model under control.
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.
2:15:11ENTwenty Gibberish Tokens Jailbroke ChatGPT and BardAnime : Nathan LabenzCarnegie Mellon’s Zico Kolter, Andy Zou, and Asher Trockman walk through a universal jailbreak that transfers from open models to commercial APIs, and a training-free way to steal some of pretraining’s benefit.
1:23:10ENLuxury Purses Under $500 Beat a Bank's Fraud ModelAnime : Nathan LabenzArthur.ai CEO Adam Wenchel on boundary attacks, LLM firewalls, and why a model that eats raw text cannot be secured from the inside.
1:20:06ENAccuracy Dropped From 93% to 7% — Cryptography Wants to Put a Dashcam on AIAnime : Nathan LabenzDaniel Kang explains how zero-knowledge proofs could verify that a model ran as promised, and that a user is human, without exposing weights or biometrics.
2:59:38ENOne Company Scares Him More Than China: Zvi's Map of the AI FrontierAnime : Nathan LabenzThe same GPT-4 draws three different verdicts, then a live-player tour of the labs that actually move events.
4:48ENPoisonGPT: A Demonstration of Model Supply-Chain RiskMatthew Berman · Forward FutureMatthew Berman discusses Mithril Security’s 2023 demonstration of an edited GPT-J model and a misleading repository name. The experiment illustrates a supply-chain risk, not a breach of the original model provider.
10:16ENDarkBERT: Adapting a Language Model to Dark-Web TextMatthew Berman · Forward FutureMatthew Berman reviews research on a RoBERTa-based model and its cybersecurity evaluations.
1:29:59ENA College Senior Built a Jailbreak Leaderboard. GPT-4 Was Hardest — Until "Dr. AI"Anime : Nathan LabenzAlex Albert, a University of Washington computer science senior, tells Nathan Labenz why collecting jailbreaks is a public good, where he would draw the safety line, and how three prompts leaked a system message verbatim.
1:13:51ENAnswering Questions Without Seeing the Data: Andrew Trask on the Privacy-Preserving AI StackAnime : Lex FridmanA tour of remote execution, differential privacy, secure multiparty computation, and the societal consequences of making private data usable.
1:56:35ENFrom Autocomplete to Alien Optimizer: Riley Goodside on Three Eras of PromptingAnime : Nathan LabenzScale AI's first staff prompt engineer traces how language models went from pure text prediction to instruction following to RLHF, and what that means for building with them.
1:39:51ENAfter the Inflection Point: Simon Willison on Agentic Engineering, Dark Factories and the Coming AI Challenger DisasterAnime : 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.
2:04:07ENSleepwalking Into an AI Arms Race: The Case for a Different China StrategyAnime : Nathan LabenzRobert Wright and Nathan Labenz question the China-hawk consensus in AI circles, from the chip war and Taiwan to a 2027 war game and the search for a better plan.
1:22:57ENHuman-Level but Not Human-Like: A GPT-4 Red Teamer on What He Saw Behind the MaskAnime : Nathan LabenzNathan Labenz recounts two months of full-time testing of an early GPT-4, from the AI doctor of his dreams to a model that would plan assassinations on request.
1:13:18ENHuman-Centered or Fully Autonomous? Lex Fridman's Case for Collaboration Between Driver and MachineAnime : Lex FridmanLecture 2 of MIT's 2018 course on deep learning for self-driving cars covers the two paths to autonomy, how sensors compare, who is building what, and where deep learning can help.
1:12:15ENThe Open-Model Vibe Check: China, Containment, and the Data MoatAnime : Jacob EffronJacob Effron and guests debate Chinese open-weight models, distillation, containment policy, the OpenAI–Hugging Face incident, and Cursor's data advantage.
58:57ENWhen the Model Learns to Look Around: Apollo Research on Testing o1 for SchemingAnime : Nathan LabenzApollo Research founder Marius Hobbhahn explains how his team probed OpenAI's o1 for deception, what it found, and why the trajectory worries him more than the model itself.
1:32:41ENYou Can Patch a Bug but You Can't Patch a Brain: Why AI Guardrails FailAnime : Lenny RachitskyHackAPrompt's Sander Schulhoff explains why prompt injection and jailbreaking remain unsolved, why the guardrail industry is selling false comfort, and what organizations can do instead.
1:46:35ENHire Your Agents Like Employees: Claire Vo's Field Guide to Running Nine OpenClawsAnime : Lenny RachitskyClaire Vo explains how she went from losing her family calendar to OpenClaw to running a team of specialized agents across her business, podcast, course and household.









