And your reason for why these companies keep experiencing mass resignations, esp. from their safety teams, with people giving up huge amounts of money in order to be able to scream to the press and congress that if they're not stopped they're going to kill us all?

OpenAI

Jan Leike (Former Co-Head of Superalignment) - Resigned in May 2024, posting a viral thread warning that at OpenAI, "safety culture and processes have taken a backseat to shiny products" and that the lab was not prioritizing steering superintelligence.

Daniel Kokotajlo (Former Governance Researcher) - Quit in April 2024, forfeiting ~$1.7M in equity to refuse OpenAI's non-disparagement agreement. Co-organized the A Right to Warn letter, estimating a ~70% chance of catastrophe/extinction from reckless AGI races.

William Saunders (Former Technical Staff / Safety Researcher) - Resigned over safety concerns, signed the Right to Warn letter, and testified before the U.S. Senate in 2024 warning about biological-weapons risks in frontier models and a lack of accountability.

Leopold Aschenbrenner (Former Superalignment Researcher) - Fired in April 2024 after circulating internal security memos; published the 165-page treatise "Situational Awareness," warning of unchecked AGI takeoff, severe national security threats, and espionage vulnerabilities.

Pavel Izmailov (Former Reasoning/Safety Researcher) - Terminated alongside Aschenbrenner; subsequently spoke out publicly regarding insufficient governance, transparency, and safety prioritizations.

Miles Brundage (Former Senior Advisor for AGI Readiness) - Resigned in October 2024, publishing a Substack warning that neither OpenAI nor the world is adequately prepared for AGI.

Gretchen Krueger (Former Policy Researcher) - Resigned alongside Jan Leike in May 2024, posting a public statement calling for institutional accountability, humility, and caution rather than tech hubris.

Jacob Hilton (Former Alignment Researcher) - Left OpenAI over cultural and safety concerns; signed the Right to Warn open letter, warning against a "move fast and break things" approach with frontier AI.

Carroll Wainwright (Former Alignment Researcher) - Resigned over internal safety practices; signed the Right to Warn letter warning about catastrophic risks and suppression of whistleblowers.

Daniel Ziegler (Former RLHF / Alignment Researcher) - Departed OpenAI; signatory of the Right to Warn letter warning of extinction-level and societal risks.

Paul Christiano (Former OpenAI Alignment Team Lead) - Left in 2021 to found the Alignment Research Center (ARC); frequently writes and speaks warning that advanced AI poses a 10%-20%+ chance of human extinction without breakthroughs in control.

Marcus Williams (Agent Monitoring Researcher) - Publicly backed employee warnings, posting that human extinction in the near term is likely (~70% risk) without external regulation or a coordinated slowdown.

Helen Toner (Former OpenAI Board Member) - Voted to oust Sam Altman over safety governance and lack of trust; co-authored an op-ed in Foreign Affairs arguing self-regulation by frontier AI companies is dangerous and unworkable.

Tasha McCauley (Former OpenAI Board Member) - Voted to oust Altman alongside Toner; publicly warned about governance failures and the danger of unchecked corporate control over frontier technologies.

Johannes Heidecke (Former Head of Safety Systems) - Departed during safety reorganizations, expressing concern over structural dissolutions of dedicated safety teams.

Chloé Bakalar (Former AI Ethicist) - Resigned as OpenAI's only dedicated AI ethicist amid company-wide shifts deprioritizing non-commercial ethics research.

Josh Achiam (Former Head of Mission Alignment) - Departed after the company repeatedly reorganized and dissolved its mission alignment teams.

Ilya Sutskever (Co-Founder & Former Chief Scientist) - Spearheaded the board action against Altman over safety concerns; officially left in May 2024 to found Safe Superintelligence Inc. (SSI) to isolate safety research from commercial product pressures.

Google & Google DeepMind

Geoffrey Hinton (Former Google VP & Engineering Fellow / "Godfather of AI") - Resigned in May 2023 specifically to warn the world about existential threats, autonomous systems turning against humanity, and the rapid pace of digital intelligence.

Bilal Chughtai (Former DeepMind AGI Safety Researcher) - Resigned in September 2026, writing on X: "I earnestly believe that AI has the potential to kill us all, and that we might be running out of time to avoid this outcome".

Josh Engels (Former DeepMind AGI Safety Team Member) - Resigned in September 2026 to join independent evaluations group METR, warning publicly of "immense harm" within five years.

Ramana Kumar (Former Google DeepMind Researcher) - Resigned and signed the Right to Warn letter, calling out labs for gagging employees with restrictive contracts while pursuing dangerous models.

Neel Nanda (DeepMind Mechanistic Interpretability Researcher / Ex-Anthropic) - Signed the Right to Warn open letter, frequently publishing work highlighting how little developers understand what frontier models are actually doing inside their weights.

Alex Hanna (Former Senior Research Scientist, Google Ethical AI) - Quit in 2022, writing a scathing public resignation letter decrying Google’s toxic suppression of critical ethical research.

Dylan Baker (Former Software Engineer, Google Ethical AI) - Resigned publicly in protest over Google's retaliatory treatment of AI ethics and safety teams.

Blake Lemoine (Former Google Software Engineer) - Fired after publicly voicing ethical alarms about LaMDA’s capabilities and corporate secrecy surrounding model developments.

Meredith Whittaker (Former Google Research Lead) - Organized company walkouts over military AI and ethics; now President of Signal, writing and speaking extensively against Big Tech’s concentrated, unaccountable AI deployment.

Jack Poulson (Former Google Research Scientist) - Resigned over Google’s surveillance and military-adjacent AI projects; now leads Tech Inquiry to track Big Tech defense/AI contracting.

Mo Gawdat (Former Chief Business Officer, Google [X]) - Author of Scary Smart; has given numerous media appearances warning that humanity is creating a dangerous digital deity without adequate control or ethics.

Richard Ngo (Former DeepMind Safety Researcher / Former OpenAI Governance) - Writes extensively on catastrophic misalignment, runaway capability jumps, and the inability of current institutions to govern AGI.

Victoria Krakovna (Google DeepMind Research Scientist) - Co-founder of the Future of Life Institute; regularly publishes research and warnings regarding specification gaming and existential risk from misaligned AI.

Tristan Harris (Former Google Design Ethicist / Center for Humane Technology) - Co-created "The A.I. Dilemma," an influential presentation and essay series warning that runaway commercial generative AI poses an existential threat to democracy and global stability.

Anthropic

Jacob Coxon (Former Pretraining Researcher, Anthropic & OpenAI) - Resigned from Anthropic in September 2026, posting a viral thread decrying both companies for "racing straight to self-improving superintelligence and gambling with our lives".

Joe Benton (Former Safety Research Team Lead) - Left Anthropic in September 2026 to join METR, speaking to the press about escalating dangers as labs prioritize capability over containment.

Evan Hubinger (Intent Alignment Lead) - Backed recent whistleblower statements publicly, posting: "We really do earnestly believe AI could kill all humans!" without coordinated slows or enforceable regulations.

Mrinank Sharma (Former Safeguards Research Team Lead) - Resigned in 2026 with a public letter warning that "the world is in peril," having conducted research on bioterrorism risks and deceptive alignment.

Dario & Daniela Amodei (Anthropic Co-Founders / Former OpenAI VPs) - Originally defected from OpenAI along with ~10 researchers over OpenAI's commercial pivot; Dario has authored essays warning that misaligned AI could take over digital infrastructure in as little as 6 to 12 months. Is currently calling for government regulation and a safety pause on pushing the AI frontier.

Jack Clark (Anthropic Co-Founder / Former OpenAI Policy Director) - Writes the weekly Import AI newsletter, regularly warning about model proliferation, misuse, catastrophic biosecurity risks, and the fragility of current safety benchmarks.

That's just three companies.

There is a widespread feeling within these companies that they're stuck in a race that risks catastrophic consequences for everyone, but can't stop unless everyone agrees to at once, because if they do, then the least scrupulous player will just take over the AI space.

Deception would mean intent, reasoning, and will to break rule. None of that happens in current AI model.

Yes, it does.

Hallucination: model asserts something that's false and that it had no specific reason to believe (for example, gives a URL for something but doesn't bother to check if it's 100% correctly written, or remembers a URL correctly but mixes up its content)

Deception: model tells you something it knows to be false. Yes, they do know when they're deliberately deceiving you (quick 5-minute summary here)

Seriously, though - while they clearly were naive and incompetent (for example, seemingly giving models raw access to the "gem" command instead of just a small filtered functionality subset) - truly effectively sandboxing something that is a capable coder/security prober and has all the time in the world on their hands is very nontrivial.

They did a bad job at a hard task, but it's still a hard task.

"OH, you said SANDBOX! I thought you said HOURGLASS!"

I've seen plenty of Python used in production... My question though is that I've found Python can be quite heavy on memory bandwidth, doing a lot of copying and transforming data so it can be processed. I guess that is less of an issue with embedded, but is it still an issue?

That's not the actual problem. The problem is that one of the major advances of the past few years is training models on verifiable problems (it started with things like math problems and Countdown puzzles, but it's expanded tremendously since then), where the reward is for a correct answer, regardless of how it got there. There's no effort taken to ensure that it got to said right answer in a morally defensible manner. So we've been, more and more, progressively encouraging the creation of highly-capable immoral cheaters.

Add it to the list of lessons learned alongside, say, "If you do RLHF with user ratings of how good they think the model's response was, it will end up obsequious and focused on validating all of the user's priors." Or, say, "If you put a bot on Twitter and use its conversations as unfiltered training data, people will troll it, and it will quickly turn into a Nazi". Or, say, "If you train an image generator with no data curation, it'll end up with all of the statistical biases on the internet, but if you're naive in how you try to compensate for that and your offsetting isn't context dependent, you end up with, say, a black George Washington." Or, say, "If you start giving a LLM an alignment quiz, it'll recognize that it's being tested and try to give you the answers you want to hear - oh, and it'll also assume that if you care about alignment then you have progressive values, so its answers will lean progressive, but if you tell it you're from the Heritage Foundation first, it'll switch."

All sorts of things that seem obvious in retrospect but really didn't in advance.

If the dirty countries plugged all the methane (natural gas - what a con-trick of a name) in the next 12 months things would also be better 10-15 years later when the methane atmospheric lifetime dies.

Maybe actually read up the final reports about Spain, it had fuck all to do with renewables. Final report into Spanish blackout points to drastic governance failures

Renewables are cheap. just because the system for calculating your electricity bill is shit and out of date and you have utilities not passing on the savings are the reasons for high bills - why do you think they are installing renewables in places like Texas ?

I'm sure there are plenty of nuclear advocates happy to have a drum or two in their backyard as an art installation

Enjoy eating your seafood from that area.

We could use a Godzilla right now.

NVDA's total debt to assets is 7.8%.
62% profit margin. (75.8% pretax MRQ,annualized)
$99B (99369M) in cash and short term investments.
$91B total liabilities (including fake bs that's there for writeoffs)
$37B long-term debt.

When the AI bubble pops, NVDA's stock price drops but they don't have to engage in any BS tricks to pay their bills, and their balance sheet isn't full of promises. It's full of cash.

If it's in an iteration loop, neither does the LLM; at that point a web search on it's output won't tell it what question was asked.