"No mine is the most dangerous"
"Nuh uh mine is"
"Mine could kill everyone!"
"Mine could do it faster!"
"Prove it!!!"
This is where we are
Did somebody say that Elon is stealthly funding: Seven lawsuits filed against OpenAI by families of Canada mass-shooting victims
As always, when the going get's tough, the tough ultimately resort to lawsuits.
You should assume that everyone has a hidden agenda when money is involved.
we are in market capture phase. Domestically hosted Chinese LLMs is a descent market to capture.
In this case, this point is kinda moot since the entire US and SV tech ecosystem, has been subsidized first by the US defense industry during the cold war, and after by the US government funded VCs by its unique cheat-code ability to infinitely print the world reserve currency with little to no inflation consequences upon its own economy, and dump it on its tech sector or on the free market to buy foreign competitors before they become a challenge, in order to be ahead of everyone else.
Given this, I find criticisms of China's state subsidize to pale in comparison, when we talk about what is "fair".
> You should assume that everyone has a hidden agenda when money is involved.
As an European there is little difference between what US is doing and China is doing when it comes to tactics. The particulars may differ, the end result is similar. Traditionally I could at least say that US was more democratic and as such was preferable, but that argument seems to be gradually weakening.
Once it gets to release (they have said they are still adding features and multi-modes like vision) and llama supports it, I think you’ll see a huge asymmetric price point between east and west SOTA models
TPUs were their real moat. All that capacity used throughout their suite of products on non-chatbot features, ready to rip for consumers once soon as somebody else opened the floodgates to the public.
Now all their competitors lose money on every token paying their cloud providers (of course it's funny money, maybe they're just giving the cloud providers equity) while Google is sitting calmly over there, actually owning everything they need for any eventuality, and beholden to nobody.
I didn't think crying could be such a successful business model.
i.e. "I'm so worried that our capped for-profit structure will limit your returns when we make over 1 Trillion in profit".
I'm sure their marketing department is ecstatic but you guys are far more hype-based than what you're calling out.
This AISLE benchmark is interesting in this matter: https://aisle.com/blog/ai-cybersecurity-after-mythos-the-jag...
And the recently discovered Copy Fail by Xint code is another proof that the gating is overblown: https://xint.io/blog/copy-fail-linux-distributions
I'm not entirely up to date on each week's LLM hype train/scandal but last I heard there was no public access to it or public-trusted 3rd parties that can review model's capabilities
What would be really interesting is a side by side Claude Opus 4.7 and Mythos comparison.
This is the world we live in.
To be clear, I don’t think OpenAI could have raised what it raised as quickly as it did without him. But with the benefit of hindsight, Microsoft should have let the safety board fire him.
I'm curious what you're basing this on. Are you aware of any grumblings on the inside? From the outside it appears no different than before largely because it seems everybody knew he was a slippery dude anyways, but they tolerated it because he was slippery in ways that were profitable.
I also think he was prescient in his unquenching thirst for compute. Despite Anthropic possibly having a better product I think OpenAI will prevail simply because he's gone to extreme (sometimes diabolical, cf that DRAM deal) extents in ensuring they have enough compute.
Like, it's pretty likely that Claude's recent problems are due to insufficient compute. With 9's (and resultant loss in goodwill) comparable to GitHub, I actually have doubts they will be able to hit their projected ARR. OpenAI could win simply by dint of having capacity, which can be attributed to Altman's shenanigans.
Anthropic is currently raising tens of billions of dollars at a favourable valuation to fund infrastructure needs. From a shareholder perspective, that beats raising the capital ahead of demand.
> OpenAI could win simply by dint of having capacity, which can be attributed to Altman's shenanigans
If OpenAI is able to deny compute to Anthropic, yes. I'm not seeing any sign that OpenAI will be able to lock Anthropic out of the tech giants' clouds.
(That said, I'm not sure what the Stargate deal falling through means.)
Not because he threatened OpenAI’s valuation. The idea that OpenAI might be worth more without Altman is still heretical talk.
> not sure if you didn't know
My three-sentence comment directly references it in the third.
More accurate to say the board I think.
Pretty incredible that employees will go to bat for a lying scum bag when they would never do that for each other.
A CEO getting fired, not by the for-profit company's Board, but by a board with a public mission, right after said company released a groundbreaking product that captured the popular imagination and then turned that into a multibillion dollar deal with Microsoft (which in turn parlayed into trillions of dollars of wealth across the economy), is absolutely news.
You’re also ignoring the biggest aspect: that these employees would never do that for the actual people doing the real work. The employees got played, the public got played, the media got played.
> which in turn parlayed into trillions of dollars of wealth across the economy
This is a fucking laugh. Where’s my and the rest of the economic workers check? Surely there’s trillions of dollars of wealth for all the economic workers if it was truly beneficial. More like stealing trillions of dollars from the working classes via the economy.
No instead things have sky rocketed in cost due to AI CEOs sucking up all the money investing it in…datacenters and raising energy costs for everyone which has a downstream effect of making plenty more expensive while suppressing wages.
This term has taken the cultural place of FUD. I’m starting to see it as another thought-terminating cliche. Like yes, people should be trying to understand what happened in those days.
> Where’s my and the rest of the economic workers check
I never made any claims around how it’s distributed. The fact that this wealth exists, and is sprouting up in multiple sectors, is indisputable. (Whether it’s paper wealth is another question. But people are cashing in massively and across the economy, albeit outside jobs that code.)
Not really when the end result is the same in the grander picture. Helping save Altman does ZERO for LLMs. There is always another douche bag rich a-hole that will do what he was doing. That’s why there are multiple federally contracted LLM companies. And Altman’s is often considered worse than the competition. Why is it important to understand what happened during those days? Enlighten me.
They say this because in their circles it's a compliment, and nobody ever stopped to consider how the general public might react to it, especially if you claim you'll shortly be the one in charge of world-reshaping technology.
"game recognize game"
People don't become bad guys just because they lie. The consequences of their actions (and their lies) matter more. Take Elon Musk for instance, he has always been a recognized liar, even when he was a good guy. What changed? Before, he was famous for making the electric car people actually wanted to drive, and cool rockets. Then came the politics: supporting the party most of his fans disliked, being responsible for many government job losses, in particular in the field of environmental preservation (ironic for a supporter of "green" energy), etc...
The following companies are participating in Project Glasswing (to get out in front what vulnerabilities Mythos is able to find and exploit at scale):
AWS, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, Linux Foundation, Microsoft, NVIDIA, Palo Alto Networks.
Do you think they are all in that gullible category?
My suspicion is an adult in the room realised that simultaneously pissing off every major corporation, government and NGO, and giving them an incentive to bottle you up immediately, could backfire massively.
That an inference for Mythos is probably beyond what Anthropic can provide at scale right now.
assuming mythos is a paper tiger: great marketing, keep going
assuming mythos is for real: err, does this have to be explained?
>ChatGPT: This content was flagged for possible cybersecurity risk. If this seems wrong, try rephrasing your request. To get authorized for security work, join the Trusted Access Cyber program.
Related, they outsourced the TAP verification to a terrible vendor, and their internal support process to AI, so we are now in fairly busted support email threads with both and no humans in sight.
This all feels like an unserious cybersecurity partner.
If you make an LLM more safe, you are going to shift the weight for defensive actions as well.
There’s no physical way to assign weights to have one and not the other.
Do you think a human is capable of providing assistance with defense but not offense, over a textual communication channel with another human?
If no, how does a cybersec firm train its employees?
If yes, how can you make the bold claim that it's possible for a human to differentiate between the two cases using incoming text as their basis for judgement, but IMpossible for an LLM to be configured to do the same? Note that if some hypothetical completely-determinstic LLM that always rejects "attack" requests and accepts "defense" ones can exist, the claim it's impossible is false. Providing nondeterministic output for a given input is not a hard requirement for language models.
In general, no, humans can’t be sure they are only helping with defensive and not offensive work unless they have more context. IRL, a security engineer would know who they’re working for. If they’re advising Apple, then they’d feel pretty confident that Apple is not turning around and hacking people.
I have no comment about whether it's impossible to determine the intentions of a person asking for assistance through a textual conversation with that person.
Because that’s what I am seeing emerge from the various efforts to build LLM safety tools.
> Do you think a human is capable of providing assistance with defense but not offense, over a textual communication channel with another human?
LLM != human? They don’t even use the same reasoning process.
Something having not been obtained so far is not a logical argument it is impossible to obtain that thing.
> LLM != human? They don’t even use the same reasoning process.
There are a finite number of possible input strings of a given length. For any set of input strings, it is possible to build a deterministic mapping that produces "correct" answers, where those correct answers exist. Ergo anything a human can do correctly with a certain set of text inputs, it is possible to build an LLM that performs equally well. You can think of this as hardcoding the right answers into the model. The model itself can get very large, but it is always possible (not necessarily feasible).
It's only impossible for an LLM to do something right if we cannot decide what it means for the answer to BE right in a stable way, or if it requires an unbounded amount of input. No real-world tasks require an unbounded input.
To be fair, we compute a lot slower too. No way in hell are you (or I) able to produce 'tokens' at the same speed as current models.
It'd be interesting to see an actual comparison of humans and AI performing the same (cognitive) task and measuring the amount of energy that was used.
Put up velvet ropes outside… leak out rumors about the horrors inside. Whether it’s LLMs or carnies with tents full of “freaks” it’s the same playbook.
Watching OpenAI tumble from the clear market leader into “hey guys us too!” territory has been insightful.
Thats how this stuff works, although there’s a whole generation that’s not seen the back side of a bubble and seems to think there’s no such thing as a downside.
I'd rather lose my pants if I had to lose anything, so then I'd still be presentable for Zoom calls.
Unless ... idk it sounds crazy but giving me $200/mo might actually make it safe. Lets do that
I personally am ready to buy the drop when this bubble pops.
Not sure about the security capabilities and haven't tested it all that well, as I usually just use hosted models, but I do find myself using it and it's been quite successful for parsing unstructured data, writing small focused scripts and translations.
The fact that I retain control of the data itself makes it incredibly useful, as I work in an environment where I can't just paste internal stuff into Codex.
But since it's run locally on a toaster testing it is out of scope for me. It takes a fairly long time to do anything.