AI marketing bullshit stunts are unlike anything I've seen in 30 years. It started with MS Copilot so called capabilities for work, which were completely made up use cases that didn't work at all (3 years later still). We've had OpenAI "AGI is coming" and "AI will take your job", now we have Mythos being so "dangerous" for cybersecurity, which of course makes the average Joe interpret it as Anthropic being "the better overall company, the NSA uses it!!". I mean gov foes with Anthropic are probably true, but the marketing is to blame not Mythos capabilities. This is all so fucking pathetic
Don't forget, its no longer cool to say that now that the public has pushed back. The fact they all changed their tone away from taking jobs tells you that it was all just entirely marketing.
I'm just glad there are so many jobs. Just look at the latest unemployment numbers! I wonder if this era of peace and prosperity will be remembered as the peak of humanity?
And did you see that chocolate rations increased again last month! It's literally incredible.
I was able to identify, diagnose, fix, and upstream a minor bug in and erlang/OTP ssh key implementation with Opus in maybe 20 minutes (+2 weeks or so for upstream). It is not impossible that I could have done this before, but it would have taken days or weeks. The actual fix was about 2 lines of code, hardly AI slop, but getting there would have been quite the slog, and I never would have done it.
There is a lot of the reason for AI skepticism out there, but people tend to do massive overcorrections and underestimate the force multiplier it can be, particularly for people with some idea of what they're doing and a good grasp of how to take advantage of the tool.
So let’s say you’re in Anthropic’s shoes. You see that LLM’s are getting better and better, and it’s very possible that they will have some impact on jobs in the next few years, and a very meaningful impact on cybersecurity.
Is it more ethical to stay silent about these concerns, as you might have a bit of self interest? Or even if it looks a bit self interested, is it better to warn people ahead of time? I think the latter is obviously the better position.
Are we really saying that Anthropic claiming AI would take over industries was some benevolent ethical move rather than marketing their product as a cheap replacement for human labor that works in any industry? Wouldn't the ethical thing, if they were actually concerned about labor displacement, be to shut down the lab and work to disrupt and disable other labs instead?
Oppenheimer believed that technological progress is inevitable: if something can be built it will be.
Anthropic (and Deepmind, and some at OpenAI) believe the same thing.
Their ethical argument is:
1) This technology is coming whether or not our company does it or not.
2) Strong AI needs to be under human control, and we are the best placed to develop techniques to make this happen.
To be very clear: Anthropic (at least) is very happy to restrict access to their best models. They have continually campaigned for regulation to make sure others have to do the same.
> Wouldn't the ethical thing, if they were actually concerned about labor displacement, be to shut down the lab and work to disrupt and disable other labs instead
Personally I strongly reject the idea that labor displacement is unethical.
It will be a serious problem to deal with, but that doesn't make it unethical.
The steam engine displaced labor. That doesn't make it unethical.
What are those to be created jobs going to be doing that AI won't be able to?
There's two big differences with the steam machine: this change is happening much faster so society has much less time to adapt, and it's got a much wider scope. Steam machines only replaced a small category of jobs.
Be specific, what are you talking about. Industry has been continuously warning about many of the complex problems that are going to happen as a clear consequence of the technology. I don’t know of any problem they have talked about that hasn’t either already come to fruition in one sense or another or that just hasn’t yet arrived. Dario has been predicting the end of coding for a long time now and look where we already are.
So yea no it’s more like it’s important for industry leaders and those closest to model development to proactively identify the issues that they don’t have complete control over or that we don’t have a regulatory framework for.
Super puzzling to see these comments and of course with zero specifics just “they’re all liars and grifters”
I'm talking about the breathless alarmism that Dario and his company push out as a marketing strategy. They've given us such gems as these:
- "It’s a bit like selling nuclear weapons to North Korea" (from the company that can't go more than a day or two without serious downtime)
- "We are releasing a model that is too powerful for the public"
- "It would be good for the world to have the option to slow or temporarily pause frontier AI development."
- "I believe that biological risks may soon follow, and that serious AI autonomy risks may not be far behind."
You can fill my ear with nitpicks about there still being time for these cries of wolf to be born out, but be prepared for me to wax philosophical about all things being possible given an eternal timescale.
> Dario has been predicting the end of coding for a long time now and look where we already are.
Where? It seems exceedingly unlikely that developers have all been phased out while I wasn't looking, as Dario prognosticated. And even if they all up and disappeared, AI still hasn't found a toehold outside of the relatively niche market of agentic coding.
I think that Anthropic is fully absolutely unethical. And they lied a lot. They were actively trying to make the doom happen while trying to cash out maximally on doom trolling.
If they were actually concerned over social impact, they would try to minimize it. They could have sell their product as a tool to be used to make economy boom, they tried to sell it on promiss to make it shrink for most people.
It really does not matter how much they believed own doom predictions, because they were actively trying to make them true whether realistic or not.
> They were actively trying to make the doom happen while trying to cash out maximally on doom trolling.
These words make no sense. Anthropic delayed mythos/fable rollout. A mythos model without safeguards would have been a pretty bad idea, and they sacrificed a ton of revenue and risked being scooped by any of the other labs in the meantime. Frontier models are only frontier temporarily until the next lab releases their model. Of course they are a company and need to act in their own best interest.
It is also clearly serious the problems we need to think about as we march quickly towards even more capable systems. Why on earth is it a problem to point this out?
> If they were actually concerned over social impact, they would try to minimize it. They could have sell their product as a tool to be used to make economy boom, they tried to sell it on promiss to make it shrink for most people.
What a really weird take; they employ some of the best safety and alignment teams in the industry and this is an active area of research that they are campaigning for more attention on. You complain about them “doom trolling” and then complain they don’t do anything about…the doom? No sense at all.
It is perfectly consistent to (1) sound an alarm and (2) March full steam ahead as quickly as they can. If they don’t do (1) that’s unethical. If they don’t do (2) someone else will. I would rather someone like Dario align these models than the CCC. Plus it would be nice not to have a war over Taiwan which is inevitable if China gains enough of the upper hand in this AI race.
The issue is both OpenAI and Anthropic have lied so many times that it’s no longer rational to take anything they say at face value.
Also: they don’t have to know they’re lying to say things that aren’t true. There is definitely some cult-like behaviour at the moment on the west coast
Be specific, what do you consider their lies to be? Also, this is pretty straightforward. You have a decade of extremely stable and predictable performance trajectory. It’s easy to see the writing on the wall. You can feel whatever which way about their motivations and ethics but if you read say Dario’s raw words they are pretty reasonable. We have to have a good regulatory framework and do what we can to prepare ourselves while also not ceding a critical strategic advantage. The west coast is always cult like, that’s not new. And it ignores the very real substance to the discussion.
Every year since 2023 the models are too dangerous to release and in 12 months all white collar jobs will be obsolete. This might not have been a deliberate lie but it's clearly been untrue and they've said it again and again.
Predictions with wrong timing are frankly worthless. I predict at some point in the future the S&P 500 will be at 10,000. Of course I'm guaranteed to be right. But have I really predicted anything useful?
If Dario was really worried about protecting the sheep, he wouldn't cry wolf every five minutes because everyone knows that's the worst possible thing to do.
And if you want to ask if Altman is trustworthy... ask Satya Nadella or anyone else who's ever made the mistake of doing business with him
> Every year since 2023 the models are too dangerous to release and in 12 months all white collar jobs will be obsolete. This might not have been a deliberate lie but it's clearly been untrue and they've said it again and again.
How is a prediction a lie? Did they tell you "this will definitely happen in X time"? Their speculation is not only valuable (they are the closest to the technology) but also necessary (they need to buy long term compute contracts so these predictions are literally what they have to bet their real money and company success on).
They have said again and again that this will make an incredible amount of tasks obsolete, and they are of course right about this. The models _are_ dangerous to release, every time we hit the frontier. This has become _increasingly true_.
> Predictions with wrong timing are frankly worthless.
Who cares?
> I predict at some point in the future the S&P 500 will be at 10,000. Of course I'm guaranteed to be right. But have I really predicted anything useful?
You aren't cherry picking and strawmanning here? Should we have a tour of all of the things that have indeed been predicted well and already come to fruition? Was 2025 "the year of agents"? It very much was, wasn't it? Additionally, unlike the S&P, performance trajectory, for almost a decade, is incredibly stable and predictable. It's hard to know, a priori for a given task or category of tasks, what specific error rate will trigger a phase transition but it's absolutely obvious and clear that this will happen quickly. It has indeed happened quickly. Does 2026 coding look anything remotely like 2024?
> If Dario was really worried about protecting the sheep, he wouldn't cry wolf every five minutes because everyone knows that's the worst possible thing to do.
No you're right he would make well reasoned arguments for the types of problems we need to address urgently. Hmm...that feels pretty ethical.
> If Dario was really worried about protecting the sheep, he wouldn't cry wolf every five minutes because everyone knows that's the worst possible thing to do.
I don't feel either of them are trustworthy, they are CEOs acting in their companies best interest. But people suggesting Mythos delay was some sort of PR ploy is some of the most extreme mental gymnastics I've seen. I listen to the actual words spoken by these people and consider the hard data that is in abundance at this point. I listen to the large body of research on alignment and safety and measurement that anyone can read for themselves or use AI agents to digest for them.
I’ve just watched enough old Adam Curtis documentaries to know historically how these things always end, true believers in many dead ends have exactly this kind of zeal.
Very smart people, reasoned arguments, “science”, all wrong.
The point I'm trying to make is Anthropic's marketing about broad security risk related to the capability of its models is a valid concern though their dog and pony show really overdid it, probably to the detriment of us all for many reasons. It is indeed amplifying the abilities of people to find and exploit security issues.
The point of my anecdote is I was able to identify and fix an at least security adjacent bug in a language I could charitably consider myself a novice in. It happened to very unlikely have a security impact, but that was mere chance. LLMs expand the pool of people able to find and exploit security problems and we're all considerably more vulnerable as a result.
The biggest security threat was always someone bored with $20, a lot of attacks could be ignored or at least not prioritized with that threat model. This isn't true any more and our attack surface has gotten a whole lot larger.
Find it yourself. On any recently released erlang create an ssh server with their library. With the only available post-quantum algorithm connect to the server 1,000 times. You should get one or two key exchange failures (1/512 chance to fail)
OP described a simple 2-line fix that would have been annoying to find by hand. That's a matter of heuristic search. The majority of problems in software engineering do not fall in this category.
More than low hanging fruit, I think it would have been legitimately hard to find. It only triggered 1/512 runs and probably would have required some expertise in crypto algorithms.
BUT regardless, pruning low hanging fruit for any task IS a force multiplier. So much of so many tasks are easy but tedious. Finding libraries, documentation not matching code thus reading code, correct syntax/arguments, and just tons of straightforward tasks which are not HARD but time consuming.
But the propaganda deluge was a smash hit so far, HN is drowning in “AI” BS, and astroturfers and spin doctors haven’t seen that much business since the cold war. They made more profit than shovel salesmen in the gold rush.
The US has gone all in on AI because it is one of the few things in which they still have an advantage over Asian countries. I wouldn't use the word pathetic but rather "desperation".
So is your position that i.e. the Five Eyes [1] cyber security leaders are just pretending that AI cyber security is a serious thing to play into the geopolitical east vs. west thing and its not genuine?
It just feels like people are starting to reach for conspiracy theories rather than engage with the idea that these models might actually be dangerous.
The “Five Eyes cyber security leaders” aren’t exactly famous for their political independence, or for having the public’s best interests at heart, or erring on the side of regulating less.
You don’t get very far in the spying profession with honesty.
We should seriously reframe this whole AI thing to "SI = simulated intelligence".
It's google in a box. Great achievement, makes knowledge work faster, but please stop bothering everyone else.
The Uber and Groupon people became billionaires, so the "Simulated Intelligence" folks will also achieve it. No need to worry and drown everyone in these bs stories only non-tech people believe.
Heh. In the Schlock Mercenary universe, "SI" means "synthetic intelligence", which is a level below real AI (which means what we would call AGI). And, as it says (in https://www.schlockmercenary.com/2003-07-21), SI translates to "kinda stupid".
Can you describe your experience using modern AI tools that led to this conclusion? It is hard for me to wrap my head around how my perception could be so different from someone else in presumably the same or similar profession. I'm not asking this in bad faith either but I think your getting downvoted because your comment comes off as a pretty strong assertion without giving details on how you got there.
A lot of effort is spent to make the "conversation" feel just like a human-to-human interaction. This is not a naturally occurring phenomenon due to the technology, but rather a feature carefully engineered by those companies in order to get people hooked. Then they have all these tiny nudges like the typing animations or the "thinking..." popups before the next chat message appears.
At some point you might have also noticed the over-use of emojis, the bolted-on jokes, and the tendency to always approve what the user says (even though they have toned that down after backslash). At some point too many people thought they were in a relationship with the chatbot, because it always encouraged and approved them, so they had to hotfix it.
It's a bunch of really dark psychological patterns that are carefully combined by very clever people in order to create the false illusion that the user is experiencing something deeper than an engineered simulation of human interaction.
I think the technology is really useful, but they are obviously not happy with simply replacing a google-like query interface, they want users to fall in love with the product and mentally treat it like a fellow human being - and that's what I think is insincere.
To get more concrete are you using coding agents like Claude Code/ Codex/ opencode etc? What kind of work are you doing specifically?
If you are doing the kind of median enterprise tech work these tools are just good enough to do it at a relatively high level or atleast heavily augment people doing it.
Examples would be like adding routine CRUD features to APIs/ improving observability/ adding tests or accessibility features to codebases etc.
It try to explain it better in my longer sibling comment. I'm not using any coding agents. Their engineers can't be bothered to design their own webapp properly so I don't trust their binaries.
For me both Claude and ChatGPT are query-response services and replacements for google. They help with error messages, single-file MVPs, and software design problems such as comparison of different modules.
In my experience everything that goes beyond 200 lines creates issues down the line, so I try to keep interactions really short. Of course they can convincingly add CRUD functionality or tests, but one needs to double check their correctness, and if the subtle bugs are finally spotted then one needs to fix them anyways.
It's good for a first draft but I wouldn't use agents on a codebase I actually care about.
Unfortunately the billion-dollar funding forces the AI startups to make a return, and they are finding it in a vulnerable cohort of people who respond positively to a simulated human interaction, which is why they are focusing so much on it.
The query-response knowledge interface was the moat of google, and nowadays it can be 80% replaced with a local GPU and an open model. They know it, which is why they try to hook people on the simulated human interaction aspect of their interfaces through chatbots and voice chat.
Not a good comparison. Education is the part where they train on all digital content they can get their hands at, no matter the copyrights.
You get your education, you can replace google as a query-response interface to all digital content.
But then they use system prompts to simulate a fake persona and a user interface such as female voices or chat conversation in order to suggest that one is interacting with a real human being. This is clearly aimed at exploiting vulnerable cohorts of people, because the knowledge base part of this innovative technology is already solved.
Like casinos and social media companies, they know the profit is in the "whales" who can be psychologically manipulated to spend their time and money against their own interests.
How would you program a LLM so it gives useful information to people with the least amount of people bitching about it?
At the end of the day the LLM does not have a native persona. It has countless numbers of them. It can act like an autistic man, a flirty woman, a kid from some country you've never heard of. Bringing forth an agreeable persona from the myriad is a bad thing?
POV OpenAI, early 2021. You have a pretty good next-token predictor called GPT-3. You noticed sometimes it can do useful things if you write out the start of a task and let it predict the next step. However, sometimes it's very difficult to frame a task that way. So instead you train it to predict the answer based on a question or instructions. Oh wait, it didn't get it right the first time... better let users iterate too. Now you have a conversation.
Things like loading indicators are basic good UI dating back to the 90s.
A/B testing and generally following user preferences might still push towards the dynamic you're describing, as it did with gpt-4o. xAI and a few other companies like Replika also intentionally created "companion"/porn AIs. But in general, natural language was previously exclusive to humans. It's completely natural that the first technology capable of it would therefore be perceived as more human. It's worth trying to resist this tendency, but it doesn't require evil intent on the part of the creators.
The "conversation" interface is exactly the same workflow as one used with google search: user states a query, page loads, user adapts query because they are not happy with the result, until they end up with a suitable result which makes them close the tab.
So they have made this amazing query-response system which is far superior to google due to the summarization of query results from the global web and the auto-translation to present them in the user's native language. This is the type of raw query-response capability which many software engineers are trying to use in their agentic coding sessions.
However, after achieving such innovation, the AI startups consciously choose to apply social media KPIs to their query-response startup, which incentivizes all the dark patterns we have seen in their user interface. They notice that a certain subset of users can be tricked into believing that the startup's query-response interface has human-like qualities such as a name and persona.
This user cohort shows amazing metrics in terms of time spent on app, so they adapt their user interface and their system prompts accordingly. The AI startup doesn't have to care if the reason for humans accepting the illusion of a simulated human interaction is due to social circumstances (lack of emotional intimacy) or an underlying psychological vulnerability that the startup is actively exploiting.
The AI startup only cares if their "simulated human interaction" product receives negative attention from normal people who are not part of the vulnerable cohort, e.g. the suicides or the parasocial romantic relationships with the chatbots.
It is exactly the same as in the gambling industry: There is a certain subset of users called "whales" who are the cash cows for casinos, but if you look at the actual humans who are labeled with this term one can see pathological gamblers, most of which are ruining their lives and families. Casinos do everything to prevent people from jumping from their roofs after they lost all their money.
If AI startups can use simulated human interactions to make vulnerable people act against their own interests in the same way as casinos and social media companies do, it will allow them to make shitloads of money.
But if you're actually a clever person then be honest to yourself and others about what you are working on, and why these human-like features are really added to the user interfaces of OpenAI or Anthropic or the other AI startups.
So this is my framing of the situation.
I don't think this kind of problem can be overlooked by the insiders, and we might see some internal rifts along these lines: Will our AI startup simulate a human interaction in order to exploit our vulnerable peers, or will our AI startup focus on delivering the best response to our user's queries?
Because now we have local models, which - assuming one has suitable hardware - provide 80% of the utility in terms of a query-response knowledge base.
As we are currently seeing, the AI startups with billion-dollar funding have very big economic incentives to focus on the "simulated human interaction" part of the equation, because their investors need returns.
The biggest strategic blunder I see at Google. Because if Google actually changes their excellent query-response user interface to a chat conversation which simulates a human interaction with persona, name, and voice, then they knowingly pivot to the same social media KPI driven business as OpenAI and Anthropic are struggling with.
Feels like OpenAI and Anthropic are both more interested in B2B. OpenAI I'm more suspicious of after GPT-4o. I mostly use Claude and I haven't noticed anything that feels like an intentional dark pattern. It's constantly reminding me that it's a chatbot.
(It's actually probably more profitable than their projections here calculated because they were expecting to be running Fable but can't, and Opus costs less to run)
Well the good thing is you’ve done the homework to definitively demonstrate that this is remotely true. These confident claims of this all being some sort of unprofitable Ponzi scheme, not understanding the concept of a growth phase which a multitude of highly successful tech companies have already demonstrated work while simultaneously commenting on a site with YCombinator in the url are just getting amusing now.
Of course this is a profitable technology, and it doesn’t matter if any of the labs are profitable today or not. Running at a loss is a perfectly rational strategy.
