Traster

It's kind of interesting that they're releasing this, because anyone with access to the OpenAI RestAPI has probably already vibe coded an equivalent to this. It's a trivial thing to bootstrap.

To be fair, I don't think they do want you to be excited. They have a REST API. It does the obvious things a REST API would do with OpenAI - lets you interact with openai models via a REST API. This is a CLI for it. There's really nothing to describe that isn't in the name, it's the CLI for the OpenAI Rest API. If you don't already care about the REST API then this isn't really for you.

As a man in tech, it's quite easy to just completely miss this behaviour. It's very easy to overlook. Especially since there are often very few women, and the women that are around aren't likely to trust you enough to tell you what's actually going on. One of the senior engineers I worked with literally came to me after an interview she was conducting and was like "Yeah we can't hire that guy", why? because he got aggressive when a female engineer (who was literally interviewing him for a job!) corrected him on his approach to a coding problem.

And it's a mine field, because it's also not helped by some of the companies I've worked at - big companies - who literally had quotas for hiring from "diverse" backgrounds. It doesn't matter what you do, if you put in those top level targets, atleast some of the idiots in your management chain are going to take it as "just hire a woman" and 1 bad woman is the justification for 1000 mediocre men to go on a rant.

I find it funny she complains about being called "guys". When I was at uni we were in the meeting with the head of the department, a group of 6 of us. He goes "So guys <pauses> <creepily turns to the one woman in room> and lady". And then goes on to explain to us he does that because a woman once complained because he kept on saying "guys" when he was talking to a mixed group of people. It was genuinely unbelievable that he thought that was acceptable. But then he also explained that sub-10% of the department was women because they "wouldn't lower their standards".

Europe is going to be just as worried about using US models for large parts of government related functions and they're going to feel alot better about open source self-hosted chinese models than US models which can literally get turned off on a whim by Trump. They'd prefere home grown models if they can, but if they can't they'll go self-hosted and that'll be Chinese at this rate.

I hope this gives people a nice illustration of how absurd the claims are here. Mass incarceration, the removal of their right to self-determination, military occupation, forced re-education camps. A plan to remain enforcing this punishment on unborn future generations of Gazans....

And not a single word on the land currently occupied and being expanded on by Israeli settlers and the Israeli military in contravention of international law. Or sorry did I misunderstand, does the military occupation also put those settlers on trial in the Hague?

What is your expectation of how the civilian population of Gaza are meant to live after this? You can repeat your propaganda all you like, but what is the actual outcome you expect from this? In five years time, is this land occupied? By the same population that was displaced, or by Israelis? Or by no one?

That is a staggering level of incompetence.

I'd be kind of surprised if OpenAI were really doing this deliberately because a whole bunch of their execs come from Meta, and all those guys learned the hard way.

First: You don't want to leak information about your users to advertising networks because it's going to leak, get back to your customers, they're going to figure out you're doing it and get really angry.

But second and more importantly - it's a much better business model to collect that data for yourself, keep it in house and then you control how you use that data to target ads which gives you a massive competitive advantage in selling ads because you have unique targeting data.

The way meta does this now is the model, they don't give the advertiser a list of the people you're going to show the advert to, the advertiser gives you a list of characteristics they want to hit and meta decides who those people are.

It's often more useful to think about incentives than try to look for evidence. Even before AI is was relatively well known that "google is dead" and you couldn't research products using google because it was all just SEO slop, so instead people were googling "X product reddit" for recommendations on like menswear, or tools or whatever they were thinking about buying. And you just think to yourself, well yeah, if I were trying to drive sales for my brand, I would be astro-turfing on reddit. And what's the incentive that reddit has to stop this happening? They don't really sell effective ads, so it's not competition, it drives engagment, and the people really responsible for stopping this (if anyone is) are the moderators, who are unpaid and so are eminently bribe-able.

Everyone understands that pretty girl on instagram who has 300,000 followers is getting paid to show that make up in her stories, why on earth would you think the guy with 300,000 karma posting his fits on /r/malefashionadvice isn't getting the same?

Hang on, are our kids learning from AI agents? Do we have a child alignment problem? Do we need to put our kids in a sandbox. At this rate our kids are going to out live us, I for one, am panicking.

No one has actually said that Dana White is a bad business man. It's just very difficult to believe that's the reason he was appointed to the board of a social media company on the same day that Donald Trump was inaugurated. If he was so consequential why wasn't he named to the board on Jan 7th 2021? I think we know why.

I put this firmly in my category of "Bitcoin Millionaires". Well, yes, technically, if you had noticed at the time, and you had sued them and they had lost (which they might not, it seems he knew the paperwork was a mistake) then you would have had 9,375 more shares, and then if you'd kept them you'd have a billion dollars more worth of Nvidia stock.

Here's a question though - you were given 15,625, so are you a billionare? Do you have those shares? Probably not. So what's makes you think that if you'd got those extra 9k shares you would've kept them?

It's the same as the Bitcoin millionaires, yes, you had 50 bitcoin in 2012 you'd be rich now. But the vast majority of those people sold their bitcoin long before it went up (or bought a pizza with it) and a big chunk of those who didn't got Mt Goxed or BitFinxed or FTX'ed, or got hacked, or lost their hard disk with their private keys etc. etc. etc.

In the UK we have the laws around how government documents of historical value go into the national archives after 20 years, documents with personal information are held longer (up to 100 years). I could see a good argument for the Snowden archive to be automatically decrypted and published after 100 years on a similar basis for it's historcial value.

I think the answer to what happened is really straight forward though - they published as much of it as they could, what they published is probably pretty representative of other stuff in the archives and there's no news value to publishing 100 variations of the same story. If they published 1% of the archive, but the other 99% is just a million details about the same basic decisions then I don't think it matters much. It's also a really slow and painful process to make sure you're protecting the identities of people.

Having said that, I could see some value in a team taking a privately hosted open source AI model, feeding into it the archive and any related news articles into it and asking it if there's anything newsworthy that we missed.

I view this very much as the same trick Silicon Valley pulled with Uber. "We're a technology business! Ignore the fact we're playing employees less than minimum wage and using VC money to force out competition to set up monopolies".

"We're creating the machine god! Ignore the fact that our companies are stealing IP and have directly violated several federal hacking laws and should be in jail". Literally the defence seems to be "well it wasn't us it was our computer software that did it". But all hacking is done with computer software.

So why don't we stop talking about possible future crimes against humanity and just start by prosecuting the actual crimes these companies have committed so far.

You know how you get alignment? Through incentives, and "Your CEO is going to be sent to a maximum security federal prison for hacking" really aligns incentives very well.

Yes, imagine it's a book cipher and then you hand it to a tool which famously has had every book in existence cleaved apart and fed into it.

This just seems to be quintessential silicon valley

"I don't want to live in a world where someone makes the world a better place, better than we do."

It's amazing how transparently OpenAI is running the standard silicon valley playbook.

Parse that statement more carefully.

> I was told the model did not look up user data.

The naive way to read this is "Nothing you guys did influenced the way our model got to the solution".

The less naive way to read this is "Of course the model isn't looking up your user data. I (the guy trying to blackmail you to remove the Anthropic employee from credit on your paper) looked up your sessions, and tipped our model off on how to solve this problem".

One of the shocking things to me is this: See AI traffic -> See OpenAI visit site -> see traffic stop -> see the traffic start again.

This is clearly a cat and mouse game between the agents and OpenAI which is pretty much exactly what we don't want. Just absolutely horrible alignment.

I'm still of the view that if you have these alignment failures you can't just continue training on top of that because you're baking the cheating into the model going forward.

There's two different things you're talking about here. There's the cost estimate- the amount you tell people up front a surgery is likely to cost, vs the actual cost to the hospital. You don't need to guess how many syringes of X you're going to need when you've already done the surgery. At that point you just addd up all the stuff you used, price it up and that's the BOM. Cuban is saying they don't even do that - they don't track their costs on a surgery by surgey basis at all. And because they don't track any of that it's impossible to reason about it.

It's impossible to answer "How much will it actually cost to insure person X" because you don't have any of the data on what the costs will be when person X needs a given surgery, all you have is the aggregate costs of the entire system - a lot of which is misleading because things are cross-subsidized because no one is really tracking costs. It may well be that whilst every surgery is billed equally in reality obese patience are responsible for 80% of the cost. Or it may even be that the hospital is making an average loss on hip surgeries because their negotiations with the insurer drove those prices down whilst brain surgeries give a nice profit margin.

And so you can't ask "How much would it cost for the government to fund service X" because you don't know how much it costs, all you know is the aggregate money spent across all medecine.

It's not difficult to define what curing cancer is, we've got tonnes of measures we can define. Let's define curing breast cancer - we have cured breast cancer if the 5 year survival rate is above 99% for all SEER stages, or less than 1 in 1000 women get diagnosed with TNM stage 1 or above. It's not that hard, it's just that deep down, they don't want to be judged on that basis.

(Details of the definition of these terms: https://www.cancer.org/cancer/types/breast-cancer/understand...)

This semi-analysis article reads a lot more like an OpenAI press release than a real analysis. And to be honest some of the statements seem like just straight up lies - they initially claim they were invited to benchmark it, and then half way down switch to claiming that OpenAI provided all the numbers. This really kind of sucks, because I want to read actual detailed nuanced and credible analysis of what's happening in the industry and it doesn't seem like you can trust this as far as you can throw it.

This is such a good example of a straight forward question that achieves the exact opposite of its purpose. What do we want? Highly ethical people that are mission focused and willing to give up on economic upside for the mission. What are we going to get? Sociopaths who are perfectly happy lying to your face about their intentions, or sycophants who are going to tell you what you want to hear.

Do you know who has the best answer to a moral quandry they've had to navigate during their career? Liars! That's a really difficult question to answer if you're honest, it's a really easy question to answer if you're dishonest.

If you really want to pursue this strategy rather than setting up bullshit interview questions you could do something much more straight forward. Agree some standard of living that's acceptable for your employees - let's say 250k in the bay area. Give them that as cash comp, and everything else goes into a "fund" which gets paid out when specific milestones are achieved, as judged by some panel. Cure cancer? You all get 10% of your deferred comp.

If you want your employees to be prioritizing things other than stock price you can literally just encode that into your compensation strategy if you like!

Obviously no one would do that, because they don't actually want to give up the comp.

Well clearly they choose, there's more demand for their GPUs than there is supply, so they have to decide somehow and the fact that the announcement of these deals frequently come with a plethora of weird funding/loan/guaranteed demand/exclusivity/bunlding, shows they're doing a lot more than just running a simple bidding process.

Can someone explain to me how Nvidia chooses who they sell chips to. As far as I can tell there are dozens of companies out there trying to build out these data centres; all frontier labs to some extent, all the hyperscalers, the neoclouds. The demand for Nvidia chips outstrips supply by a decent margin. There must be so much that goes into this - the commitment from musk to exclusively use Nvidia, the weird equity deals, etc. For example, is Google just completely unable to buy GPUs at this point because Nvidia sees the TPU as a threat?

All the conversation on twitter seems to be about how cheap this is. Are they just choosing to lose money on inference to gain market share or do they actually have inexplicably lower inference cost/more efficient models?

The shear hypocrisy of this is quite staggering. Ok, so we own the outputs, but you get to decide how we use them, and you don't trust us to use them. But the people whose books you stole to build your psychopath machine, they didn't trust you, did they. They didn't really want you to build a machine that can generate thousands of books to compete with their work, but you did do it anyway. Are you going to commit to auditing every input that was used to train your model and attain positive consent for their use for training?

It's also pretty wild to call this standard practice. It's not. I can grab any of the open weights models and train to my hearts content. So it's not standard is it. You'd like it to be standard because you don't want to compete.

And you don't trust us, but it is your company that's been going around telling us how excited you are that your model goes out onto the internet and hacking people.

This continual authoritarian bent from the least trustworthy people in the world is deeply problematic and the only saving grace is their absolute total and complete failure to enforce the restrictions they wish to place on us.

Your ability to build the God machine doesn't magically endow you with the moral authority or judgement to decide how it's used, and the fact that these people believe it does is a great indicator that they aren't to be trusted.

I really don't understand why they do trials for this. What would be the failure case for the trial? "We carried out the trial for 6 weeks over X period of time, we arrested Y people, at that rate we've decided this is not compatible with modern liberal democracy, we would've traded a free society for Y+2 arrests over X period but we just didn't quite get there"?

As suggested by other people - this is just going to be used to identify, infiltrate and disrupt the numerous peaceful protests that the police aren't keen on in London.

That is absolutely not true in this case. If what Apple alleges is true, the closest example we can look to is Waymo vs Uber. Where Uber ended up settling, they paid Google a quarter of a billion in stock, agreed not to use the IP they had stolen and fired the engineer involved. This could very easily just kill OpenAI's hardware product, they might literally not be able to release what they've built. At that point they have to decide whether they start again from scratch, with monitoring to ensure they aren't using any of the IP or they just give up on this expensive distraction from their core business in the run up to an IPO.

This looks really bad for OpenAI. Honestly, do not post text messages on the web, you look like a messy bitch. At this point I really don't see this company going public under Altman, they're going to have to bring someone in to bring some professionalism here. Altman seems to have badly mismanaged pretty much every corporate relationship they've got going. OpenAI is such a natural fit to be a partner with Apple, yet somehow they've managed to completely burn those bridges in the most public and messy way possible.

It makes me so angry that an entire branch of "science" gets to just take data and go "I dunno man, maybe kids are just dumber". There's so much of this in social science. Take some measurable thing, and then just wildly speculate about the cause of it in an entirely untestable way, and then test that theory in ways that absolutely do not justify the conclusions. At the very least, the whole field should get a lesson in how to communicate the certainty of their theories and conclusions. You've got some guys hanging around couching their uncertainty when they're banging sub atomic particles together at the speed of light and then you've got some social science bro being like "If you move that checkbox on that form to the bottom it'll be way more effective, trust me bro I've hacked how people think".