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46:20ENOne Vector Made the Assistant Plot to Take Over the WorldModeration: Nathan LabenzNathan Labenz and Robert Wright pick apart AI doom, mechanistic interpretability, and why today's alignment tricks are not expected to work.
16:44ENMatthew Berman on OpenAI’s 2024 AI Infrastructure Security ProposalsMatthew Berman · Matthew BermanA review of six proposed security areas and a critique from the perspective of open model weights.
54:25ENJail Only for Perjury: Scott Wiener Walks Through California's Frontier AI BillModeration: Nathan LabenzSB 1047 sets the same 10^26 FLOPs threshold as the Biden executive order, and the San Francisco senator wants testing without a licensing regime.
1:43:54ENFifteen Examples Can Poison GPT-4: Today's AI Systems Are Exploitable by DefaultModeration: Nathan LabenzFAR AI founder Adam Gleave walks through cheap jailbreaks in GPT-4's APIs and amateur-level wins against superhuman Go engines, and why robustness is not arriving on its own.
1:45:21EN600,000 Attack Prompts, and Nearly 40% Still Pwned GPT-4Moderation: 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 OpeningModeration: 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 ItModeration: 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-4Moderation: 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 GuardrailsModeration: 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 BardModeration: 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 ModelModeration: 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 AIModeration: 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 FrontierModeration: 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"Moderation: 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 StackModeration: 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 PromptingModeration: 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 DisasterModeration: 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 StrategyModeration: 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 MaskModeration: 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 MachineModeration: 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.
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