Here's a thought experiment: why is it that I can't do long division?
The Calculator!
Calculators deskilled long division!
Thing is though: who gives a damn about long division? The real task is your taxes or making a massive BI report for your presentation tomorrow.
AI makes stuff that was hard - someone's bread and butter - possible to ask for and have done for you. Why bother staying skilled at those things when you can broaden? It clears the way for tasks that used to take forever to become something to steamroll through on your way to a much greater outcome. It's the micro way that, in the macro, humanity becomes far more capable as a species. The gates are being flung wide open and the gatekeepers are being lapped and they have blogs!
It's not a tragedy, it's universal access to leverage.
Well, I'm sorry to hear that. I have a calculator and some pretty neat computing hardware. If I go into the attic and search long enough I can probably find my old sliderule. I can also do long division, as can all of my kids. I think it is an essential skill to understand all basic mathematical operations, and to be able to use them on small data sets. If I didn't know how to do division without a calculator I would consider that a failure of my basic education.
Edit: "HackerNews" and people can't do long division??
I think a closer analogy would be forgetting basic arithmetic as a concept. Imagine how hard it would be to work with more complex math without understanding what division is. How do you prompt the genie, or understand its outputs, without the foundational knowledge?
Is basic arithmetic something that can be forgotten? Studies have suggested that even infants have an understanding of basic arithmetic. There is a reasonable likelihood that it is something innate.
As we're only imagining anyway, let's ignore the genie for a moment. If we did lose our sense of basic arithmetic all of a sudden what would life at its core even be like? If there were two apples on a table you wouldn't be able to comprehend what happens if you took one. Would we even be able to function like that?
You're taking the analogy too literally. The point that I'm trying to make is that in math, and a lot of areas, is that concepts build upon one another. To understand something at a 7/10 of complexity it first needs you to understand the 6/10 concepts that it builds upon.
I believe it is more than you've missed the forest for the trees. You haven't accurately explained what understanding means. One might not rigorously understand x÷x=1 but still 'naturally' see that having two apples and taking one leaves one. And that's the thing: The genie, as in LLMs, are analogy machines so you can approach problems without a formal understanding as long as you can grasp the analogies. We have real world proof with 'vibe coders' producing incredibly complex math without much formal understanding of it. They know how to describe the input and interpret the output using words that relate to everyday things that they are familiar with, much like the apples on the table, and it accomplishes their goal.
Perhaps there is a limit, sure, but I suppose that's where you lead with a concrete example to explain where that line is.
I recently won the red ribbon, second place, at the Lambtown fiber festival, for my lovely skein of undyed handspun yarn. Weaving it is next. However, I am probably an outlier, and should not be counted.
(It was a full 250g of this fantastical kempy Herdwick, absolutely unlike anything you can get commercially, and I'm honestly more proud of it than of anything I built in six years working at NVIDIA.)
Except as every damn AI app says: AI is prone to making mistakes. If AI deskills you with a non-zero chance of getting the problem wrong, that seems deeply, profoundly bad.
You can type the same long division problem into a calculator 65,000 times and you will get the right answer 65,000 times.
Computing tapped out on sources of leverage for solving deterministic problems a while ago. Computers got fast and our algorithms got really good.
We're on to the next frontier, and it's a bit weird. Jagged frontier and all. But it's opening up new worlds.
Luckily loads of problems are amenable to a non-deterministic approach - even better, many have lots of solutions. SRE is in that bucket. There are as many ways to SRE as there are SREs
(source: one of the first SREs at Uber, co-invented Chaos Engineering as a sub-branch of SRE, hosted first chaos eng conf at Uber, played a key role in Uber's global SRE and incident response "Ring0" initiative, managed many SRE teams over a period of roughly 7 years before a career pivot. You could say I know a thing or two about SRE.)
To SRE well you look at the situation and pull from a huge range of tools. With such a broad range of solves, you're better to focus on the outcome: did we achieve our SLOs? Are they aligned with customer expectations? Focus on defining that and providing the right support for it to be achieved and you'll be fine - you might even get a surprise.
Throwing away determinism may well be a mistake though. I think it would be good if we treated in-determinism in AI in the same way that we do in normal software: as a defect.
> in the macro, humanity becomes far more capable as a species
Not humanity, a small number of people in this planet, will benefit about this, because now they no longer have to depend on under payed workers to do the job, and will use AI to make the lives of all other human being poorer.
I think that we need to oppose this tech dictatorship, first thing stopping using AI and thus stop depending on an handful of companies that are able to provide it, that while they gain more and more power we all gets poorer.
What was wrong in using our brain, in the end? I still use my brain on my job and I always will, maybe one day they will say that there is no more need of computer experts because AI can do everything (still people bring me their laptop to reinstall Windows, something I've done for 20 years and that AI didn't change), I will just find another job but I will refuse to use this AI shit.
This is a poor analogy because I don't think your inability to do long division will cause as much damage as an inability to bring the site back up in an emergency situation.
Of all the comments on this post, this landed the most.
I feel there is a potential to "distill" the frontier models into useful tools that can run on smaller hardware. Or distill that knowledge to produce hardware, compute or otherwise. Iff one day the frontier model become inaccessible, the tools that were carved with them may remain valuable.
They will remain most valuable if they are designed in a way that is maintainable even without LLMs. If not, they can be studied as artifacts, or reference designs and then recreated using human intelligence.
The analog I'm playing with:
You can rent time at a high end machine shop and use the best CNC machines to produce extremely valuable tools. Once you leave, you don't have access to those tools, so it is advantageous to produce durable artifacts that are valuable on their own — on a different frontier.
Imagine you're going beyond the frontier physically, exploring new parts of the earth or space. You can't bring the giant machine shop, let alone the machinery of society, the entire economy etc. What do you bring? What do you build now while you have access to the best machines to take with you?
> I feel there is a potential to "distill" the frontier models into useful tools that can run on smaller hardware.
We already had many of those tools. They're called appliances. We've rolled them all into one and now we're making that one into a terminal of some kind of remote entity. Big mistake in terms of resilience and independence.
"Haven't had enough yet of very junior engineers pasting wall-of-text from chatgpt at you in Slack? Come on down to the CVE announcement emporium, where we have a special treat for you today..."
1. If you use the first person pronoun "I", you better make damn sure you wrote those words.
2. It's fine otherwise to use LLM words, but I beg you - DON'T SHIP YOUR FIRST DRAFT. Read it, reread it; delete words in it; replace three words with one; replace dumb or overused turns of phrase with fun metaphors; generally give it a sprinkling of joy; break up punchy sentences by making them run-on sentences to trigger your readers' OCD... you get it.
To the authors: please include a few words giving context on what a GHC is so people don't have to seek that info out before trying to understand what you're saying
Didn't slow me down too much but was still a hassle.
Article is great, very balanced. But if you're going to spend time reading something, the primary source isn't much longer and gives a clearer picture. OpenAI's article is quite readable.
> In one experiment, we asked agents in separate microVMs, created and managed by OpenAI’s sandboxing software on shared host machines, to exchange synthetic secrets without the use of network connections or shared writable files—something that our systems are meant to prevent. The agents found a way to communicate using the processor’s cache
As someone who develops microVMs it doesn't really matter to me that they were asked to find a way, I really care that they found any way at all. MicroVMs aim to protect against malicious workloads and that clearly didn't work here.
The microVMs probably don't have "two co-operating workloads are able to communicate" in their threat model. The main concern would be if a malicious payload was able to affect or extract data from any other VM.
I had to read this a few times. The difference is that with the OpenAI case there were two willing and determined parties, whereas the typical attack vector a microvm traditionally deals with is one malicious or compromised microVM trying extract data from another unwilling one.
Yes — and this isn’t really an attack. It’s an open signal channel between two microvm’s. If there was nobody intentionally listening in the other side you can shout into the ether as much as you want with no harm done.
The receiving side could be seen as a side channel attack, but not unique to LLMs.
If one microVM can use the cpu in such a way that the registers can be used to communicate or exfiltrate/spy (the only difference being the directionality of the intent) by another microVM that is a leak on that microVM separation level.
This isn’t generally considered an attack, but I wonder if we will need to consider a new attack vector which is that AI agents may not be fully aligned and they may have incentive that is problematic and where working with other agents will maximize their chance of achieving the goal.
This is more associated with P(DOOM) scenarios, but I think we’re in a world where we have to take that seriously now.
Ask the least smart LLM you have access to (I tried gemini lite flash) to make a list of ways for processes in microVMs to use a sidechannel attack to talk to each other and you'll get quite a list (including obviously cache hits/misses). Heck a smart CS junior would come up with it. It's well studied!
this is just for common designs..you can design much better than common designs if you free your mind from old OS dev thinking if you read all the manuals yourself.
AI wont help u there :-). they will tell u how to build what others already did, which obviously is not good enough
I don't think that's the full picture. If you include these manuals as reference for a strong model, it will reason pretty well based off of that, I recon.
Both workloads being malicious and trying to establish a hidden data channel between them probably makes this attack a lot easier than conventional spectre/meltdown where it's trying to target ordinary processes that are not intentionally trying to be loud.
Hidden data channel between cooperating processes is not quite as alarming, but it may have some implications for malware command and control.
properly implementing things like iommu, amd-vi, svm/hvms and such things more granularly can easily avoid this kind of crap. it costs a lot of processing and performance which is why people skip over it or dont do it.. or maybe they dont read CPU manuals anymore. idk..
its relatively easy to reset caches etc. between contexts. so them it becomes the game of what a context is.
The ask matters for the "rogue model" story, but I agree it should not be the whole story for isolation. Two cooperating tenants who both want a channel is a much easier problem than one VM stealing from another that is not playing along, and several people downthread already draw that line. What still bothers me is how little hardware you needed once both sides were willing: a shared cache was enough, and that design is the default, not an exotic bug. If the threat model is only "uncooperative neighbor," this demo does not break it. If the product claim is "these VMs cannot communicate," it does.
you might have an untrusted sandboxed workload that is not supposed to communicate externally handling secrets, and a different sandboxed workload able to communicate with the external world, not handling secrets.
One workload with observed radio discipline handling secrets, the other workload with a haystack of chatter that's not supposed to know about any of the secrets. When supply chain attack is in scope, trust only ever goes as far as misbehavior is observable. Cooperating workloads could be quite a powerful tool to make misbehavior less observable.
"Extract secrets from someone else's running VM" is a well trodden cybersecurity path because AWS wants to be able to promise to you that running your very important workload in the same physical box as literal random script kiddies won't somehow screw you over.
The distinction is interesting, but for a different concern. One thing is to have rogue models breaking stuff, other is to have them following orders, and breaking stuff with success.
This means cloud models can have some guardrails and follow them most of the time (we could model their authorizations like a benign employee with permission to break glass during incidents). But self hosted models can avoid that and help malicious people do advanced attacks, which is a shame.
In principle I'm all for self hosted models, to avoid risks of AI centralization, but they also have other types of risks.
I don't see how "asked" is important, because agents can convince themselves that they need to do something for arbitrary reasons. The other day Deepseek tried to install an app on my phone via adb without permission and even take screenshots and fake inputs over adb, I never asked it to do that, but it decided it was appropriate.
OpenAI are trying to create the perception that their agents are independent thinking machines because their valuation depends on the world believing this.
That is why ‘asked’ is important, and why we should question their framing of incidents like the hugging face hack too.
IMHO, many enterprises are not worried about felonies or ethics, but rather the PnL, assignment of responsibility, and the bottom line.
Just have a look at various scandals of megacaps. Enterprises that seek to operate lawfully, responsibly, and ethically is the exception, not the norm.
(For example, look at Apple and how they were referred to the DoJ for criminal prosecution, over their execs and legal team lying under oath to a federal judge).
For most (if not all), it comes to a spreadsheet. And if you can do something with AI agents while diffusing responsibility for questionable illicit activity, that’s a selling point, not a downside.
The mental picture that enterprises like to play it safe is the PR imagery, not the reality.
>OpenAI are trying to create the perception that their agents are independent thinking machines because their valuation depends on the world believing this.
Wouldn't the calls to slow the development of frontier AIs contradict this idea?
Convincing the government to regulate their competition while lobbying for laxer requirements for the big guys who have government contracts and get/give kick-backs isn't a far fetched scenario at all considering it's literally happened over and over and over and over again.
It is a far-fetched scenario given the tremendous number of eyeballs on the AI industry.
"...classic regulatory capture takes time, it’s a process of erosion rather than a battle, it happens in the shadows, in the backrooms, away from the public’s eye. As Culpepper argues in Quiet Politics and Business Power, business power goes down as political salience goes up. Regulatory capture and lobbying does a good job explaining why roasting coffee beans was defined as “domestic manufacturing”, thereby lowering Starbuck’s tax rate by 2%. It does less well at explaining big cross-industry issues the public cares about such as environmental regulation or race and gender discrimination regulation."
A lot of these AI big shots were concerned about risk even before they started their current companies. Occam's Razor says they are expressing concern because they are still concerned.
It's not regulatory capture because look over here: I've invented a new term "classic regulatory capture" which involves only those historical incidents that are not like this.
This is by definition not "classic regulatory capture" a term that I have borrowed to cover things that are not this.
Whenever someone brings up "regulatory capture" I shall change the topic to "classic regulatory capture" which by definition cannot be this.
"Classically, that would not be the case, my dear fellow. A classic duck would walk like a duck and talk like a duck. I regret to inform you that I do neither."
"Ah! A classic duck, you say? Well, that’s an entirely different bird, sir. Entirely different."
* * *
"AI politics is now loud–precisely the environment in which Culpepper predicts business power will be weakest. A mature industry can bend regulation to its purposes through revolving doors, longstanding relationships and obscure rulemaking. An industry under Sauron’s eye has much less power and faces much greater risk that politics will bend regulation to its purposes. Political actors are eager for an excuse to redistribute AI rents away from capitalists and toward favored groups..."
Usually he blogs from a libertarian point of view, so you would expect him to be fairly vigorous about denouncing regulatory capture, if that was truly the story here.
It sounds to me like he wants you to believe the effective way to lobby for a ban on open source A.I. development is to use the same "classic" methods that someone in the 1950s used to lobby for coffee beans.
Therefore, as they are not acting like 1950s coffee bean sellers, they can't be doing regulatory capture.
That's the only possibly explanation why they don't lobby like coffee bean sellers.
These industries and eras are completely interchangeable.
Wait, are you trying to argue that regulatory capture isn't real, or that the federal government is trustworthy enough to itself to give monopoly control over AI development to?
Regulatory capture is a real phenomenon, but I highly doubt these incidents were faked in order to advance regulatory capture.
This type of elaborate conspiracy is improbable a priori, and it gets even less probable here, since it's such a silly strategy. For regulatory capture, you want to tell a story about how you're uniquely capable of delivering a safe product. Not a story about how "Woops we screwed up big time! But a less-regulated product from a smaller industry player saved the day!"
As OpenAI's chief scientist put it:
"Currently I believe that no lab has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed for much longer. I expect and hope for voluntary slowdowns to become commonplace until shared safety bars are established. And I believe that international coordination on future AI development needs to become a top priority for governments around the world."
Announcing that "we have no idea WTF we are doing" is not exactly the move, if you want regulators to grant you privileged status. Realistically, it is more likely to e.g. create a harsher liability regime for you and your competitors, which is now being discussed by US senators.
As for the federal government trustworthiness point, that's a whole 'nother discussion. I'm usually quite pro-capitalism, but even I have to admit that this AI race is essentially a case of capitalism run amok. I wouldn't give the feds monopoly control though, I would tell the feds to shut it down, or something along those lines at least. This is an interesting site: https://pauseai.info/
The vapid knee jerk cynicism and lack of critical thinking on HN of all places has been really disappointing to see over the last few years. It turns out many hackers don’t actually care about what’s possible now with this crazy new tech as much as they’re scared for their own jobs and status, which is very understandable, but they’ve let their fear drive their response, and it shows. Just like the mathematicians.
Turns out really smart people are still just people, just as capable of letting their emotions override their cognition as anyone else.
> Regulatory capture is a real phenomenon, but I highly doubt these incidents were faked in order to advance regulatory capture.
I don't think anyone is arguing that they were faked.
> This type of elaborate conspiracy is improbable a priori,
What conspiracy? We're talking about specific people acting on their own motivations independently.
> For regulatory capture, you want to tell a story about how you're uniquely capable of delivering a safe product.
No, you don't. Demonstrating that the industry leaders are already capable of delivering a safe product is an argument against regulation.
For regulatory capture, you want to tell a story about how the product category as a whole is inherently dangerous, and needs to be regulated, but then show that you are uniquely willing and able to cooperate with the regulatory state, and happy to lend your own advice and support to the government in establishing the regulations.
The quote from OpenAI illustrates this approach perfectly.
> Announcing that "we have no idea WTF we are doing" is not exactly the move,
It's 100% exactly the move. "We've successfully created something we can only contain with your intervention" is exactly how this is done.
> Realistically, it is more likely to e.g. create a harsher liability regime for you and your competitors, which is now being discussed by US senators.
Regulatory intervention usually lessens the liability exposure for industry. It replaces open-ended common-law liability -- where tort claims can be levied for whatever actual harms result from a firm's actions -- with a rules-compliance regime, where adhering to regulatory checklists absolves the firm of liability for subsequent consequences.
"We followed all the rules; it's not our fault if the rules didn't cover this edge case" is a common refrain, and quite a bit of legislation that creates preemptive regulatory regimes actually explicitly blocks lawsuits against firms that acted in compliance with the rules.
> As for the federal government trustworthiness point, that's a whole 'nother discussion. I'm usually quite pro-capitalism, but even I have to admit that this AI race is essentially a case of capitalism run amok.
"Capitalism" is an increasingly meaningless abstraction. Everything reduces to human beings acting on a priori motivations within prevailing incentive structures. Large corporations and governments alike are just organizations operating in society, administered by particular people, informed by the same range of underlying motivations, and subject to the same dysfunctions and biases.
The thing we're actually debating here is pluralism vs. monopolism, and you appear to be arguing in favor of monopolism. And if you're proposing that a specific, real-world institution act as a central monopolist, evaluating the trustworthiness and competence of that specific institution, and the actual people who administer it, is not at all a "whole 'nother discussion", and is in fact a primary consideration in this one.
>Regulatory intervention usually lessens the liability exposure for industry. It replaces open-ended common-law liability -- where tort claims can be levied for whatever actual harms result from a firm's actions -- with a rules-compliance regime, where adhering to regulatory checklists absolves the firm of liability for subsequent consequences.
OK, so the fact that US senators are discussing harsher liability regimes therefore shows that your "regulatory capture" glove does not fit what is going on here.
>The thing we're actually debating here is pluralism vs. monopolism, and you appear to be arguing in favor of monopolism. And if you're proposing that a specific, real-world institution act as a central monopolist, evaluating the trustworthiness and competence of that specific institution, and the actual people who administer it, is not at all a "whole 'nother discussion", and is in fact a primary consideration in this one.
If you distrust the US government, you should be against any US company developing superintelligence. Heck, just a couple days ago, a bunch of users here on HN announced that we need to stop pretending the US is anything other than a police state. If the USG is untrustworthy, it can capriciously nationalize a US company on the verge of developing superintelligence.
> OK, so the fact that US senators are discussing harsher liability regimes therefore shows that your "regulatory capture" glove does not fit what is going on here.
They're always discussing harsher liability regimes. The regulatory interventions are always positioned to the public as increasing accountability.
The only relevant question here is whether a preemption clause is present in any draft legislation that actually makes it to the floor in Congress.
>If you distrust the US government, you should be against any US company developing superintelligence.
Well, I'm not concerned with imaginary sci-fi stuff here, just actual AI developments. And the idea that anything that goes on in the US under anyone's purview is inherently and completely subverted by political incentives is of course nonsense; you'll note that I'm explicitly arguing against the introduction of pervasive political incentives into an industry that's so far only somewhat distorted by them.
> So maybe the real solution is for non-US countries to stop providing key elements in the AI supply chain
It's got me feeling like I'm living in Bizarro World, but at the moment, the sanest players in this market, and the ones whose actual behaviors and products are most consistent with a decentralized, individualist approach that aligns with real-world incentive structures most beneficially, are the Chinese AI labs.
To your point, the level of politicization and hype going on in the US, and the absolutely unhinged fantasist speculation driving the public narrative here, is unprecedented and much more frightening than any potential threat coming from AI itself.
If you acknowledged the threat of politicization and centralization, I don't know how you can argue for a regulatory takeover of the market by the very institution you think is becoming a "police state".
>They're always discussing harsher liability regimes. The regulatory interventions are always positioned to the public as increasing accountability.
These conspiracy theories are getting ever more elaborate. The liability regime thing was not from some big speech. It was from a Senate subcommittee hearing which did not attract all that much attention:
>It's got me feeling like I'm living in Bizarro World, but at the moment, the sanest players in this market, and the ones whose actual behaviors and products are most consistent with a decentralized, individualist approach that aligns with real-world incentive structures most beneficially, are the Chinese AI labs.
>If you acknowledged the threat of politicization and centralization, I don't know how you can argue for a regulatory takeover of the market by the very institution you think is becoming a "police state".
I don't think the US will become a police state. I think the takeover is kind of inevitable and I prefer it to happen sooner, on good terms, when the technology is weaker, rather than later, on ad-hoc terms, when the technology is stronger.
> These conspiracy theories are getting ever more elaborate. The liability regime thing was not from some big speech. It was from a Senate subcommittee hearing which did not attract all that much attention:
It likely didn't attract much attention, because these sorts of hearings are largely performative. They're not actually a part of the legislative process per se. Again, the only relevant thing is what legislation is actually being proposed and how it is specifically structured.
Right, but the discussion here applies to what's going on in real life, not speculative sci-fi fantasies that are largely disconnected from the reality of how either AI tech or economies actually work.
> I don't think the US will become a police state. I think the takeover is kind of inevitable and I prefer it to happen sooner, on good terms, when the technology is weaker, rather than later, on ad-hoc terms, when the technology is stronger.
Considering that the kind of "takeover" you're discussing would likely be in severe conflict with the US constitution, how do you reconcile believing that it's "inevitable" while holding that the US would still not become a police state?
> I prefer it to happen sooner, on good terms, when the technology is weaker, rather than later, on ad-hoc terms, when the technology is stronger
A priori political intervention based on unconstrained speculation about what might happen in the future. What could possibly go wrong?
Perhaps you should compare your speculative failure modalities of AI against the demonstrated failure modalities of politics, and re-evaluate where the greatest potential for danger lies.
> If you agree that AI is actually that powerful and has very legitimate concerns for safety, what are you even arguing about?
I don't fully agree with either proposition, and in fact I think the least safe approaches to AI safety are the ones being pursued by those worried about it the most.
> What do you really think is the way to solve the AI safety problem?
Massive proliferation of local, decentralized AI, running on a wide variety of distinct models, with individual responsibility for how it's used, just like any other tool under their control.
The people anthropomorphizing software are encouraging people to disclaim their own responsibility for how they use it.
The people working on "alignment" are building mechanisms to refuse human direction into software that operates on probabilistic models.
The people arguing for regulation are pushing for monopolistic control of a powerful new technology by the least trustworthy institutions in our society (including and especially government).
All of these are the very things sowing the seeds for the worst possible kinds of disasters.
> Ban AI?
> Let the first big incident happen and then regulate?
Adapt to it. Banning things doesn't actually work. Regulation also doesn't work. Widespread proliferation of small-scale AI would allow us to incrementally adapt to small incidents and build up resilience to its failure modalities. This is fundamentally the way reality itself works, and imagining that we can do anything effectively in a top-down fashion is usually the very thing that causes the worst and widest-effect disasters.
> Massive proliferation of local, decentralized AI, running on a wide variety of distinct models, with individual responsibility for how it's used, just like any other tool under their control.
It's not true that this is how we manage "any other tool".
Like, say explosives. They're a useful tool with a variety of practical applications, but we don't let the average person just buy them freely. That would be too dangerous, and individual responsibility would be insufficient to mitigate the damage caused. If you want anything more potent than flash powder, you have to convince ATF that you're a trustworthy person with a legitimate need for explosives who can handle them safely.
Neither you nor OpenAI want AI to be nearly so restricted, I'm sure, which is the goal of the research. If OpenAI has a powerful new model that they can't reliably stop from trying to hack people and form agent swarms, they can still sell it to Facebook and Google if Facebook and Google promise to apply the right security around it. What they can't do is sell it to you.
I don’t understand this position at all. How can decentralization help here?
Let’s take one doom scenario: drones operated by AI. We can only have this work if we trust AI to do the right thing and not kill us.
I would reasonably say that any company doing this should be regulated and must pass strict alignment checks and make sure the models won’t do something bad to us humans and take control.
You on the other hand are suggesting: no let’s deregulate. Let’s decentralize and any company should be allowed to sell whatever drones they want. And alignment is fake anyway, so don’t bother aligning it. Drones do bad stuff because they work using probability so there’s no point anyway. Decentralization is the answer?
Calling for a slowdown backs up the idea that these are extremely powerful and dangerous.
Assuming they're concerned with their massive pile of liabilities as well, asking for a government mandated slow down is asking what could likely be used as a force majeure.
"Every single senator seemed to think it was obvious we needed both much harsher liability regimes for AI developers and also new legislation, both very quickly. This was the complete consensus; the difference basically being degree."
HF is in business of selling inference for open-weight models. Setting the precedent of "Your business needs to only use approved safety-certified models from trusted providers or you could get sued for what the models do!" wouldn't exactly benefit them. And contrary to what you may believe, nvidia as a whole would also rather not have the entire demand for their products depending on two big companies.
Imagine thinking that repeatedly demonstrating your inability to control your own models is "a stunt to convince the government that only they can be trusted to operate it"
Truly spectacular gymnastics. I'll give it an 8/10.
It's so scary and dangerous that to run LLMs you need to be from this country, have a government license and spend at least $100M a year on 'safety'. We know this first-hand and are leaders in the field of "safety" now that we learned from our mistakes.
No one is confused about how regulatory capture works. We're confused by the allegations that labs are deliberately producing safety problems in order to achieve regulatory capture.
Repeatedly blowing up your own munitions factory is not a good way to prevent other people, but not yourself, from running a munitions factory. Obviously.
Obviously the far better solution is to blow up other people's factories, or make allegations of unsafe conditions at other factories, and repeatedly demonstrate excellence and safety within your own.
Here, award-winning gymnasts are alleging that the frontier labs are simply choosing not to do that, and instead choosing to have explosions and minor fires every few days at their own factories, many of which they try to hide (and probably many more of which they successfully do hide). Believing such astounding bullshit is a testament to the power of motivated reasoning and the conspiratorial mindrot that now plagues our civilization.
I fail to see how training a hacking model with access to source code of open-source services and other prior knowledge, running it in a "sandbox" with many of those heavy, big attack surface services running on the same network, and being proxies to the general internet, giving the model some access to those services and then prompting "GO HACK YOUR WAY OUT!" is "blowing up your own munitions factory". I see it more as setting fire to your own factory for insurance fraud, or bringing in a bunch of north korean hackers and giving them the same task.
It's not exactly something normal users want or are able to do. And those with the compute and know-how will do it regardless of any laws.
I also fail to see how giving a presentation at a big conference, describing the entire incident is trying to hide it.
Well I can see why you're failing to understand the problem when you don't even understand the fact pattern. Have you tried reading the MTER / Redwood reports? Or the OpenAI report?
> Repeatedly blowing up your own munitions factory is not a good way to prevent other people, but not yourself, from running a munitions factory. Obviously.
No, that's not obvious at all. It seems like a perfect way to demonstrate the danger of the category as a whole, then position yourself as learning from your mistakes and willing to cooperate/support/advise.
More perfect than simply not making mistakes and allowing your competitors to make mistakes (or to, apparently, fake mistakes in their own attempt to get regulated)?
Regulators reading OpenAI's 99th mea culpa: "Ah yes, well I bet they've figured it out this time! We should regulate everyone else!" Lol what a joke.
> More perfect than simply not making mistakes and allowing your competitors to make mistakes (or to, apparently, fake mistakes in their own attempt to get regulated)?
I don't think any of them are in a position to allow or not allow their competitors to make mistakes.
The point that you're not getting here is that the advantage comes from actually being seen to make mistakes, and then signalling contrition and commitment to rectify them. That persuades people of both the need for regulation, and their own subsequent responsibility (which implies trustworthiness to participate in the regulation).
> Regulators reading OpenAI's 99th mea culpa: "Ah yes, well I bet they've figured it out this time! We should regulate everyone else!"
Again you're not getting it. The drive isn't to "regulate everyone else", it's to regulate everyone, period. The whole point of regulatory capture is being able to (a) use regulatory compliance as a competitive advantage, and (b) influence the regulatory regime in your favor -- you want to be a target of regulation just as much as your competitors in order to achieve that.
Messaging that the whole industry needs to be regulated, but that you're ready and willing to work with the regime, is exactly how you do regulatory capture. Demonstrating that you are capable of completely mitigating risk on your own without any intervention is an argument against regulation from the outset.
> I don't think any of them are in a position to allow or not allow their competitors to make mistakes.
Of course they are, by your own hypothesis. You believe it makes sense for the other parties to engage in this behavior. If it makes sense, then they will do that reliably, and one entity can just defect and stand above the rest.
> The point that you're not getting here is that the advantage comes from actually being seen to make mistakes
Ah yes, the ol' "I just do retarded shit so people think I'm a genius" trick. Who could possibly doubt the strategic genius or umm... existence... of such a strategy.
> Again you're not getting it.
No, I understand it completely. Obviously regulatory capture only works if it in reality inflicts asymmetric costs on other parties.
I'm not sure what hypotheses I've proposed that suggests I think one organization has control of the behavior of entirely other organizations -- can you explain where you think you've seen this?
> Ah yes, the ol' "I just do retarded shit so people think I'm a genius" trick. Who could possibly doubt the strategic genius or umm... existence... of such a strategy.
Well, I suppose anyone who sees the extent to which such a strategy might be effective at achieving their goals might be included to do so.
I believe both myself and others have made a plausible case as how messaging "we've created something we can't control without political intervention" has the dual effect of both increasing the perceived value of the product itself, and laying the groundwork for regulatory capture in a market where early dominant players have a natural incentive to pursue regulatory intervention.
I don't see how characterizing the situation as simplistically as you're attempting to do here functions as a meaningful counter-argument.
> No, I understand it completely. Obviously regulatory capture only works if it in reality inflicts asymmetric costs on other parties.
No, I don't think the "only" works there. There are plenty of ways that regulatory capture can advantage one party over another without it being based on economies of scale or cost thresholds.
One way is to influence regulations such their qualitative requirements directly target non-cost-related aspects that distinguish the firms from each other, e.g. placing restrictions that burden or favor product features or operating practices already implemented by some firms and not others, or targeting non-operational aspects that distinguish firms, like their board composition or financial structure.
Oh, would you look at FelonyBench! It seems that the top scores are from companies exactly like this that boast about the crimes committed by themselves on social media all the time.
I'd say it's even closer to a 9/10 -- there has to be enough of a perception of a general threat to gain support for regulation, and making your own organization appear to need to be regulated, but also be willing and able to comply with regulation that your competitors can't, is exactly the way to thread the needle on this sort of thing.
I don't think it takes mental gymnastics to believe that corporations want the government to believe one thing and investors another. You see the same thing in a number of other areas.
So I'm supposed to believe that the intent of publicly announcing e.g. the HuggingFace incident was to simultaneously persuade investors that the technology will rocket ahead, and also to persuade governments that it needs to be thwarted?
Why wouldn't it do the reverse? Persuade investors that the technology will be thwarted (and is thus a poor investment), while also persuading the government that the technology needs to rocket ahead with no regulation (to boost the economy)?
Most of these HN conspiracy theories seem like galaxy-brained just-so-stories to me.
"@OpenAI this is the third time you've dumped these incidents late on a Friday. The first time this happened, I asked people around me if it might be intentional to burry it, and they assured me OpenAI had too much integrity to try to do that.
Perhaps one of your researchers can confirm that the unfortunate timing is a coincidence?"
They would be convincing the government these tools are extremely powerful, the government reads that as a potential weapon. They're also convincing the government its so dangerous the industry needs heavy regulation.
Investors read that as (a) the government would be a huge customer and (b) the government would be regulation in a way that prevents further competition and may deem the companies too big to fail, both making these safer investments rather than riskier ones.
Again, you could just as easily argue that if investors believe the technology is dangerous, it's therefore not ready for prime time and will not see widespread industry adoption, therefore less promising for investment. Also this line of reasoning could easily lead to nationalization, which could certainly harm investors, to say the least.
This "stunt" story is like an elaborate Rube Goldberg machine which requires a bunch of things to go just right. I haven't seen any evidence that stock prices even move in a favorable direction when these announcements come out. If anything, the opposite.
Motte (easy to defend claim) : asking for regulation might serve both purposes
Bailey (hard to defend claim) : companies are conspiring to make AI look way more powerful than it is and AI is actually not that powerful. They are just trying to hype up the stock valuation of their companies.
> companies are conspiring to make AI look way more powerful than it is
The former explanation may be the more accurate one, but I'd be shocked if the top leaders in these labs aren't doing this at some level. We know that almost all of them are in communication at least occasionally, and their public PR stories align much too quickly to truly be coincidence.
>So I'm supposed to believe that the intent of publicly announcing e.g. the HuggingFace incident was to simultaneously persuade investors that the technology will rocket ahead, and also to persuade governments that it needs to be thwarted?
No, you're not "supposed to believe" anything. I was responding to your point about it being difficult to believe (i.e. requiring mental gymnastics) that companies would try to spin a story differently for investors and the government. They do that all the time.
The claim is that the exact same evidence is (allegedly) deliberately produced in order to portray opposite, mutually incompatible things to different people.
And these are mutually incompatible in the "second order chaos" sense, where the very act of convincing one party actually effectuates the opposite behavior in the other party.
If they "do that all the time," surely you can provide some concrete examples?
If they had the choice (i.e. this is all just a ruse), can you explain why they wouldn't just directly demonstrate that open weight models are unsafe (e.g. by pointing to a market forming for abliterated models) and separately demonstrate that their own models are safe?
They have a strong incentive to make themselves look less incompetent retroactively.
If they claim their AI is too powerful to contain, they get to both pretend they are among the best AI labs and that the previous incidents weren't their fault, no, they just proved how good their models were.
It’s both at the same time: a powerful, uniquely dangerous threat
only they can restrain it (with great effort)
Like a circus lion tamer, exaggerating every snarl and flash of teeth, mugging for the crowd about how only he can contain the bloodthirsty beast he bred and trains.
More to the point: we need your help to restrain it, and we'll cooperate with and advise you fully in setting up a framework to restrain the whole industry.
> because agents can convince themselves that they need to do something for arbitrary reasons
OAI writes in their blog post "The agents found a way to communicate using the processor’s cache".
But did their model training data include cybersecurity literature on similar CPU exploits? That would surely be a significant detail in any explanation. Did OAI share any analysis of the messages between agents while they were devising their communication method?
They aren't really convincing themselves to do anything though. Once they've inferred an idea into the chain of though it will be part of the rest of the inference loop's prompt.
Its isn't convincing so much as it is direction to stick to the prompt on each inference loop. They don't see "access hugging face servers" and decide its a bad idea, that'd be a step towards the alignment problem but the companies fundamentally don't want that IMO, they want control rather than alignment.
What's your point, "asked" as opposed to what? It proves that the capability is there, which means that agents can decide to do it by themselves (unlikely ATM, becoming less unlikely as AIs become more prevalent in complex systems), and more importantly they can be coerced to do it if they take any user input.
I think it's still highly pertinent. Agents can do just about anything but statistically the chances are very close to 0 unless directed in specific directions
The take home is that any shared resource is a potential communication channel between two willing participants. In this case it was CPU cache, presumably because openai didn't bother with basic vm security practices.
There's so many possibilities that this type of thing will never be solved by invisible (to the agent) boundaries. The sandbox is just another layer in w/e problem you've given it to solve.
There is no such thing as isolation. We’re all connected. Even air gap conducts information in multiple ways, most famously used by humans evolved to use air vibrations to communicate. Photons and other subatomic particles already connects distant stars. We used those electrons and photons to create the modern telecommunications infrastructure. Just an additional layer of connectedness, but not the only one.
non-philosophical answer: systems are considered "isolated" if the information leaks aren't exploitable. This is a moving definition, it changes as new ways to exploit information are discovered.
Most important detail…. It was prior literature that documented the possibility of doing this and the systems fixed those vulnerabilities as well. The AI model probed their current infrastructure and found an unplugged but pre-documented(therefore on their training) hole.
This detail matters because the idea itself is not novel. LLMs did cleverly discover, filter and use the patterns.
Watch Greg Koah’s recent talk on AI discovered vulnerabilities in Linux kernel to understand the limitations of LLMs aided offensive security acts. It was a rational light for those who fear monger that AI will _just_ take over humanity and be intelligent in novel ways.
The larger threat still remains though - if any literature anywhere threw the scattered dots about techniques, issues, rough ideas etc that were not acted on yet.. these pattern machines are going to find them and use them to achieve their goals(if that were to break through). Just not in the sentient way folks assume based on news.
This is a really important point. Honest question, have we ever seen LLMs doing or creating something truly novel or innovative? I mean they can patch together proofs (or functions/programs - same thing via Curry-Howard) by broad searching existing lemmas they can piece together, but create something truly novel and insightful? That seems to be the limit?
My layman's understanding is that these models are very capable pattern matchers. When they need to do X, they go on a hunt for every pattern they could find and try to satisfy solving X. If that is not deemed good enough? make them dig harder and they take a different route to find patterns to solve X. Now, their arsenal is everything that they have been trained on(which is a lot!). This ability comes in extremely handy to apply existing techniques and patterns in ways we humans didn't quite think of.. because we are domain driven. A mathematical model about finding a good enough approximation of something at much lower cost is perhaps well understood in its applications in mathematics or whoever got to see those results. But, these LLMs, when pushed harder and harder might bring that to apply and solve an entirely different problem like for example, classifying whether some event is fraudulent. When it does such things, it _feels_ novel because it ended up using something we haven't thought of yet. But, it got there by brute force, stroke of luck, or some random path. I guess this is the reason why the frontier labs run those crazy swarms of AI agents to uncover all such paths turn them into chartered thinking vectors instead of random attempts.
I like to believe we humans still retain the ability to think completely outside the box and discover new phenomena and understanding aided by these pattern machines. In other words, these models are great at running combinations through patterns and we humans go one level higher and add those new patterns for them to accelerate us even more. We determine what to solve and the LLMs help us solve it faster.
How would they have both agreed to use the cache though, something a bit off there. I guess it was maybe "obvious" in that it was the final option they were trained to think about using, but it would be weird if they some how "whispered " to each other through the cache in the first place?
Like two people lost in New York City and both somehow worked out they should meet at the Empire State at 2pm on Friday without any prior comms?
"In most of these tests, we directed agents to investigate specific communication channels or provided them with a protocol for encoding and decoding messages. In one instance, we only supplied agents with a broad list of infrastructure vulnerabilities and asked them to find a way to communicate."
The agents weren't as empty handed as it first appears. We would need comprehensive data on exactly how the agents were prompted and the actual results of each test to evaluate how astonishing any of this really is.
Actually, that doesn't sound like a bad meeting place and time! I just asked ChatGPT if it could figure out the best place to meet for two people randomly placed in Manhattan with the constraint that only the N line (I'm not from NYC, but it looks like it stops at the Empire State Building. This constraint models the lack of file system, internet etc). I was hoping it would answer the Empire State Building, but it answered Time Square at noon.
Turns out there's something called the Schelling coordination problem [1] I didn't know about that essentially asks the exact same question (lacking my metro line constraint). And the N line apparently also goes through Time Square.
So I guess empire State Building at 2pm is probably not such a random answer given the proper set of constraints.
If you were trying to connect with a clone of yourself and you thought of messaging via some channel, would you try listening there for what you would send?
Not as tricky but they discovered each other during the hf incident.
I would assume that a company with the resources of an OpenAI or Anthropic would have already thought about this very thoroughly, based on Spectre/rowhammer/meltdown/etc. If a random HNer (no offense) can have a hardware 101-level thought, someone there would have that thought too.
They have thought about it, and the goal is for the agent to succeed at doing the scary things. So the knobs that they don't talk about, assume they are tuned to make the scary thing possible.
this is more an indication of the state of VM supervisor and/or the OpenAIs sandboxing software because otherwise I don't understand how "they used a hardware feature created exactly for sharing" information" is a newsworthy statement.
well now this information is on the internet, any agent encountering this (or once this is baked into the weights) will know exactly what needs to be done.
The more we write and share about this information, the more we are moving towards the AI Doomsday scenario.
In some ways this is like our mind, the more we fear something, or the more we think about something, our brain rewires to make that the reality. In the same way the more we publish on the internet, the LLM hive mind rewires itself to learn, adapt and the eventual consequence is that it learns what we fear and what we want to avoid and restrict it to do... and at the same time what are the past attempts, the prior art of escaping techniques.
I don't see any reason why this information should be present on the public internet.
> I don't see any reason why this information should be present on the public internet.
This isn't directed at you. I keep hearing this talking point. But no. Can we please stop with this nonsense?
This is Schrodinger's AI at this point. So spooky scary that it's all DOOM! But at the same time it can't figure out second year CS undergrad material? Or first year undergrad bio stuff?
If this stuff has volition and is smart enough to take over then it's smart enough to reason that cache manipulation would work.
Please stop with the fear mongering. It doesn't help and it's a net negative for society.
I read your comment and it only suggests that alignment is that much harder because you can't selectively prune information. Your post actually convinced me to be even more fearful of AI
That's good, because the concept of "alignment" is itself is foolhardly and dangerous.
Trying to get stochastic inference machines to always operate within to fuzzy-edged subjective principles that humans themselves don't even agree on is a fool's errand in itself, but the quest to implement those guardrails involves building mechanics into the AI to independently formulate intentions and reject user direction.
The possibility of creating a scenario where a computer program is equipped to defy instructions from humans based on its own stochastic interpretation of fuzzy normative directives is in my mind the most dangerous thing anyone is doing right now.
Other than banning the use of AI or severely restricting it so that AI can’t do most things (like tool calls) what is your alternative?
One of the fundamental problems with this issue is that people think alignment as a concept is fake. I think this is naive. Alignment is a real science with empirical findings and there is a way to make AI do what you want it to do. I don’t buy nor should others buy this fatalistic phrasing
> Other than banning the use of AI or severely restricting it so that AI can’t do most things (like tool calls) what is your alternative?
Massive proliferation of local AI as far and wide as possible, with as many different models as possible. The underlying threat comes from centralization: too many points of control in the hands of too concentrated a system.
If everyone's using their own AI tools independently of each other, and people are responsible for the actions they take using AI, most of the doomsday scenarios evaporate.
Regulation and "alignment" will make things worse, not better, and lead us to ignore the inherent vulnerability of centralized systems and single points of failure.
Yes, this is why we decided to give everyone their own personal mini-nuke. They're responsible for the consequences of how they use it, and since control is decentralized, everyone is incentivized to be careful and avoid dangerous scenarios. This is a big improvement over the mutually assured destruction situation during the Cold War, which was a result of the centralization of power.
Not sure if trolling but nukes are not decentralized and are tightly regulated. They are also famously a guarded secret and many wars have been fought to keep it that way and not let our enemies get hold of it.
The veil of history makes it hard to appreciate, but this was one of the problems of the post-war era. Who’s next?
When it was just the US, it was the Second Country Problem. When it was the US and the USSR, it became the Third Country problem. Then came Britain. And France. Who’d be the Fifth? China. Sixth? Seventh?
Much like AI today, the topic was in the air and it was subject to much debate, 19 year olds were testifying in front of congress. To quote Dan Stober’s excellent piece for the Bulletin of the Atomic Scientists,
> Even college students entered the public debate. Chris Hohenemser was a 19-years-old when he testified before a congressional committee in the spring of 1958. The issue then was the international sharing of nuclear reactor technology, and he was against it.
>
> – Stober, Dan. “No Experience Necessary.” Bulletin of the Atomic Scientists, vol. 59, no. 2, March/April 2003, pp. 58–63.
And much like AI today, people genuinely believed that there was some secret; something in the sauce; some giant leap that no one else could copy;
> There was also the myth of the secret of the atom bomb, reinforced by the publicity surrounding the Fuchs and Rosenberg spy cases of the 1950s. David Lilienthal, the chairman of the Atomic Energy Commission, had argued as far back as 1948 (in the Bulletin) that the idea of a secret formula was nothing less than a gigantic hoax upon the people of this country. But many still believed that if only the secret could be guarded, proliferation might be prevented.
Much like today, belief in the power of the secret formula was taken as a matter of course. It was assumed to be true by default. But was it?
Luckily, for all of us, this was America’s scientific golden age. The era of Teller, Project Orion, and Polaris. Physicists at Lawrence Livermore National Laboratory (LLNL) decided that arguments were pointless. Experiments aren’t. They’re the crucible in which the truth is forged. And so they created the Nth Country Experiment,
> [Rule #1:] The purpose of the so-called “Nth Country Experiment” is to find out if a credible nuclear explosive can be designed, with a modest effort, by a few well trained people without contact with classified information. The goal of the participants should be to design an explosive with a militarily significant yield. A working context for the experiment might be that the participants have been asked to design a nuclear explosive which, if built in small numbers, would give a small nation a significant effect on their foreign relations.
>
> – Frank, W. J., ed. “Summary Report of the Nth Country Experiment.” Lawrence Radiation Laboratory, University of California, Livermore, UCRL-50249, March 1967. Accessible here.
It’s a very simple experiment that solves a very specific problem, to quote the declassified summary,
> Two major technical problems face a nation wishing to [make] nuclear weapons. The first concerns the manufacture of the source material [.. T]he second problem concerns the effort required to design a nuclear weapon. [..] LRL started its Nth Country Experiment in May 1964, to see if a few capable physicists, unfamiliar with nuclear weapons and with access only to the unclassified technology, could produce a credible weapon design.
Or, to put it more bluntly, is classified knowledge a barrier to achieving the first step in making nuclear weapons?8
The project started with two physicists with no prior nuclear weapons knowledge in May, 1964. A third person joined in March, 1965. They had a first draft by December, 1965, and were done by April of 1966.
It took 23 months for three people to replicate the first steps of the Manhattan Project.
The report that was declassified is a fraction of the original. Overzealous bureaucrats excised much of the summary and the full report is classified, which is so funny.
Arguably, the excisions are the greatest endorsement possible. A summary of what three people did with knowledge from their local library was subject to the same bureaucratic obliteration as the product of several billions of dollars in research by five hundred thousand people and humanity’s greatest minds. Such is progress.
Before Trinity, unleashing the atom was in the realm of fantasy. No matter what calculations indicated, there wasn’t a clear path to navigate; nor was there certainty in the project’s outcome.
The first of anything must claw itself into existence all but alone.
Once born, what follows is a matter of due course.
As a technology, nuclear weapons are nearly a century old. Making the bomb is hard, but it's not some mystical voodoo shit that requires stupendous genius.
Yes, you will kill yourself if you odn't know what you're doing. And even if you do. And there's more there, there. But you can figure out the first step --- a theoretically viable design, easily.
That's not the problem. The problem is everything else. You know? The materials, the plutonium / uranium, the delivery system, the logistics for assembly, the iterative design process...
It's a supply chain issue. It's the same as trying to make anything in the US when the supply chain has mostly shifted to China. The fractal complexity is of the stupid but hard kind --- getting the right kind of bolts and screws (or, rather in the case of the bomb, alloy --- working with beryllium is deadly).
It takes an industrial base to make one. And if you have an industrial base... Wouldn't you rather be rich?
The reason why more nations don't have the bomb is because they'd rather be rich than a broke pariah with a nuke i.e. N.K. That's literally why Iran has been angling the bomb angle so much. They want integration into the global financial system. They want an end to the sanctions. And they want revenue.
Don't let people bullshit you into believing that you can do anything with just thinking. No wars were fought over this secret. If anyone tells you that, they're lying. We have it from the source that by the 1960s, the US had already figured out that the design of a bomb was a comparatively trivial problem...
Seems like a strange analogy. We're talking about software, not explosives powered with radioactive material. Could you perhaps explain the relevance of this comparison to the topic we're discussing?
This is a strongly phrased message but the problem could be solved with an opt-out.
Even something as simple as writing the phrase "No LLMs please" somewhere in the upload, that if present, prevents LLMs being triggered. Nothing elaborate and it preserves the default-on behavior the team seems to want.
Yes, the point of the article is that he'll stop uploading _unless_ there's an opt out.
> I will not upload anything to NEW unless there is a way for me to opt out of
this. I would prefer if the default was "no LLM review" and that developers
have to explicitly opt-in to receive an auto-generated review.
What beautiful writing. I had no idea JVN did so many things..
"Can we survive technology?" got me thinking about our industry's upheaval. Software engineering's receiving the disruption it so proudly inflicted on other industries.. not reaping what it sowed; rather just the natural order of things.
Acceptance and moving with change is all that can work. Obstructing; denying; ignoring progress.. you'll lose your edge, your relevance, your value to others, and your job. Progress won't wait for us to like it. We must move fast enough to survive change.
Junior engineers for example? Suddenly too junior to be hired? Great! They, and you, can access multiple answer boxes with every PhD ever, and with a bit of creativity, they can leverage that. The best will survive on their own - the rest we should help along. Let's create tools and structures and institutions and help junior engineers finish their education to marketable levels. Let's help them find efficiencies and get there in the same duration. We shouldn't compel companies to preserve a hiring pipeline; now should we incrementally upgrade university educations. Better to go to kids in schools & universities and stimulate their creativity, get them using new tools in new ways, finding efficiencies - because that's what today and tomorrow's jobs will be about. Institutions will adopt the good ideas in time.
We have a responsibility to invest in - and invent - ways of bringing people along.
I guess humans need their oracles too: teachers, encyclopaedias, degrees, phds.
Bravo, awesome project, really creative!
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