What these complaints always boil down to is autonomy and control.
The more centralized an organization, the more it relies on metrics to understand and exert control over its employees and customers.
People started hating tech right around the time metrics became popular. I don't think it's a coincidence. AI just accelerates the trend.
The problem is the misidentification of AI as the issue. As long as we don't understand the real issue, we won't solve it. AI is just a tool. It's being used in a way that denies human agency.
Our cultural values need to shift away from safetism that demands centralization. And shift toward valuing human agency. That starts with talking about the core issue.
Everyone pushing tools/AI during initial development/investment and building its demand in the cultural discourse always highlights its ability for good.
Now, like many tools, the majority of those selling AI to make money off of large enterprise sell its ability to increase productivity, efficiency, compliance. Either to make money or to minimise risk. And so like you say, they just become tools to make these metrics move or report them at higher granularity. And often there is either a lack of imagination or a willful ignorance of the perverse outcomes with relationship to humans because they are in service of the organisation not it's employees.
Certainly, I agree that using AI to dehumanize - generally what companies seem to be doing with it - is super bad. And it's also what is being sold to existing companies right now.
But that same AI could cause those companies to no longer exist.
The AI I'm happy about allows people without much tech knowledge create small apps to do exactly what they want. And, for those that know just a little more, use it to help them extend open source software for their niche use case.
This makes computing more personal and gives back agency to the computer operator.
Mix that with the rise of much more competition in much more custom software, and you'll see that a future can exist, if we want it, where software becomes more personal and humane.
The software vendor will capture less value, though - the margins will be thinner. Instead that value will be captured (in non-money terms) by the end users.
That also means that software companies, unable to capture so much value, must shrink and become more boutique. The software that contributes to our centralized world would lose a lot of power.
That's the future I can see. The only way it doesn't happen is if a cynical narrative wins out and manages to lock it out through regulatory capture so that only licensed operators can use or provide AI. The anti-AI narrative helps the cynics.
Are there any reasonable analyses of the practicality of data centers in space?
I know Dwarkesh Patel was interviewing Elon and brought up the fact that power cost for data centers is only 20%. The number I could find is 7-18%? GPUs are the majority of the cost. I don't think Elon responded directly to that.
There's the argument that licensing to build these things is cheaper in space. But earth has a lot of space in the middle of nowhere that no one would object to. That seems cheaper than space.
And the heat dissipation argument against it seems like a good one but I don't know if it's actually just a small engineering problem that can be solved cheaply or more fundamental.
On the plus side, you could say there is better connectivity in orbit. But if you're running inference, you'd probably want to talk to the same server that has your context cached. As it whips around earth, your latency would vary a lot, right?
I'd love it if someone could point me to a better analysis. It's an interesting question in general. Not just because one of the highest valued companies in the world is based entirely on its feasibility.
This has been done on HN a few times. The heat dissipation argument is a solved problem with known physics, it's just that pointing out the inefficiency of radiative cooling is the correct response to the daft claim that "space is cold" (the solution is "launch lots of additional mass into space every 5 years" which isn't exactly cheap). Though that claim is still better than Elon trying to tell idiots that SpaceX's ODCs are "much simpler than a Starlink satellite"...
Perhaps an understated one is chip obsolence. With a terrestrial datacentre you replace chips when they're uneconomical due to how much faster alternatives are or when they reach end of life; with an orbital datacentre you replace them on fixed cycles depending on how much propellant you launched with.
But nobody doubts you can build them, it's just hard to imagine a scenario in which a terrestrial equivalent isn't cheaper, more flexible and more reliable. Actual good reasons for adding compute capacity in space are, ironically, the latency: for some edge cases like autonomous control systems that matters more than the attractive unit economics of sticking computers in a building.
Still, the economic case for ODCs [eventually] is more compelling than the case for the value of that revenue stream to SpaceX exceeding current US GDP in the not too distant future...
Elon has mentioned before that he intends to place AI-powered factories in space that will manufacture and install new chips, while recycling the older ones. He says it's going to be fully self-sufficient.
He also said that cybertrucks would be deployed to Mars, it would be amphibious and bulletproof, people buying Teslas would make money turning them into to self driving taxis, and charged people for FSD in 2016.
If you believe anything he says, maybe you should get in on this spaceX stock deal!
That's the least practical solution of all (I say that as one of the few people in the world actually working on an orbital recycling project), especially if your technical advantage is launch, not inference chip manufacture. Apart from anything else, these giant satellites in LEO still need refuelling every five years, otherwise they'll just burn up in the atmosphere.
Replacing chips with newly launched chips on a refuelling cycle (and keeping all the heavy structural elements) is well within the boundaries of near term technology, but still involves enough mission and design-for-serviceability complexity to make it not obviously better than the 5 year recycle cadence Starlink and other modern constellations operate on.
Manufacturing newer, better chips in a microgravity environment using exactly the same material and plant technology as older chips is another thing entirely, particularly if you don't happen to own Nvidia et al's closely guarded trade secrets on how to make inference chips that are actually competitive and still aren't fully self sufficient even after the magical technology has been introduced because you need to top your massive satellites up with gas on a periodic basis....
Two things about your line of thinking stand out to me:
The first is a subtle implication that the share price of SpaceX is dependent on the short term feasibility of data centers in space. I don't think it is. Its more dependent on public sentiment and hype, which is detached from the truth and can have its focus directed elsewhere as the company engaged in many activities. I would also argue that the company's culture matters more than any engineering specifics, especially with how diverse their assets, competencies and offerings are. Maybe you didn't mean to infer this though.
Second, if intelligence is something like electricity, in that it's fungible and translates fairly universally into value, then it's safe to assume civilization will pursue expanding it endlessly (and will never have that demand satiated) like a force of nature. If this is true, would we rather have 1000x or 1,000,000x the data centers we have today within earths atmosphere or out in space somewhere? Personally, at that scale I would prefer them far away. (Not even in LEO)
There is no core physics reason why AI data centers in space can't work. It's just really hard engineering. Kind of like what reusable rockets looked like 10 years ago... All the experts were nay-sayers.
Short term, who knows, SpaceX could struggle financially and be a terrible investment today. I have no idea. It seems overpriced to me now and it did at IPO. But on a 10 or 20 year investment horizon, it looks a lot more interesting. I don't own shares but maybe dollar cost averaging in at some point isn't a bad idea especially if the price comes down further and as part of a diversified portfolio.
> Are there any reasonable analyses of the practicality of data centers in space?
The purpose of "datacenters -- in space!" isn't to actually lift server racks into orbit, one piece at a time.
It serves the same purpose as every Tesla serving extra as autonomous taxis, as people travelling by hyperloop instead of a functional train service, and as humanoid robots doing your dishes instead of the normal robots called dish washing machines.
None of these things are meant to be taken literally. Yet they all seems to have worked out just fine.
For these arguments to carry pathos they all need have a grain of truth to them. There will be local AI in satellites, for "special" applications. Think image processing for birds that have a very nice high resolution view of your back yard, and whose decisions must be low latency or when bandwith is an issue. The trick to the argument to to blur the issue by conflating it with the datacenter AI that anyone can use.
No need for any technical analysis. Space-based DC's claim solve one problem: backlash and resistance against construction from local communities.
Yet, the DCs here on earth have other problems such as high energy consumption needing on-prem gas turbines and requiring large quantities of water for cooling requirements.
I'm looking forward to a terrestrial DC that solves all these issues: it's completely self contained and self sustaining requiring very little maintenance, no external power and self contained waterless cooling. Once we have that then we can ask how we can package up this building and put it in the sea. And then when we've had enough of that, we can put them in space.
It's true that in a project, a novel idea undeclared as such will be shaved off quietly by an llm. You really need to be explicit about wanting to keep it.
You will get pushed into the mean.
However, I'd say 90% of making something (that is useful) is repeating the old thing. We stand on the shoulders of giants. Or at least we should. Getting there can be difficult for most of us.
I say this as someone who chronically re-invents things. I then later get stuck and find someone already thought through my problem and solved it better.
I don't believe being unique in all the ways is useful. You need to be unique in the important ways and not unique in the other places.
There's also a cultural coherence angle that (my) unique things often fail at. Stuff has to look like other stuff enough for people to understand intuitively what it is and how it works. Here the mean is your friend.
I am able to explore more unique spaces because I no longer deal with the minutia of getting the things that should be the same correct. So paradoxically, this has made my output more unique.
As long as I've been an adult, hardware was a commodity, and software was where the value was. Software could capture most of the value that was in the total supply chain.
Now, with AI, software becomes less able to demand the margins it once did.
Meanwhile, the history of low margins of hardware have created a situation where there are so few players able to demand now software-style high margins.
Hardware has always been valuable but was unable to capture it's value. Those days might be over.
I hope this encourages people who would build software companies to look to hardware. A lot of fun challenges there. Deeply technical, interesting ones. And now solutions will pay.
LLMs is where value capture is anticipated by the market. There's scant evidence they can capture value if they aren't relying on hardware scarcity and their own investment and contractual risks.
Engagement metrics fed into recommendations algorithms are the paperclip maximizers that feed humanity's collective poison.
Europe should do the one thing it knows how to do: regulate. For once, it is the answer. Do it only there. The rest of the dominos will fall.
Making a european branded humanity poisoner is not the answer.
Specifically, regulating against silent signals like watch time and comment count. Upvotes/likes can serve a purpose and would not cause the situation we're in now.
Do you mean regulating "watch time and comment count" at the presentation (to the client) or the server (business/analytics) level? If the later, how would you even enforce that?
Like all good regulation, it would only kick in after a company has a large reach. So as to not snuff out startups and cause regulatory capture problems that are already so common.
Telling big companies to be transparent about their suggestion algorithms would not be hard. I think governments already do this? wasn't that a tiktok thing in the US? Anyway, it's well within government's reach.
Telling companies to only use signals that people consciously give seems like a no-brainer.
Well, I mean, if you believe that a goal of civilization is to respect the free will of individuals up until the point that that free will becomes a problem for other people.
The alternative is something less than respectful of human dignity.
I'm only partially convinced. I just can't see how you could really know if a company is using a hidden metric (or some sort of proxy for that metric so that they are not technically in violation) for figuring out what to promote. Short of having constants audits, how would you ever really know?
But my skepticism may be unfounded. Do you have examples of companies that are currently working with regulators to allow full auditing of their content promotion policies? Are they actually auditing these partnerships or are they simply accepting promises from the companies?
Yes, but us universities aren’t financially accessible to most people and access depends more on connections and families than merit.
But your link also is only relevant to the university system.
It doesn’t change the fact that the non university part of education is severely financially crippled in major areas of the country in order to hinder black people from getting proper education.
Combined with a burnout introducing system of standardized tests the us educational system is truly world leading. At demonstrating how NOT to do education.
> us universities aren’t financially accessible to most people
On the contrary, they are too accessible due to enormous tuition bills and federally guaranteed student loans (which cannot be discharged in bankruptcy). This toxic combination saddles many graduates with debt they will struggle to pay off for decades. Almost as if it was intended to create a modern form of debt slave.
> access depends more on connections and families than merit.
Only true for small elite private colleges these days. Even most of the big top schools have tried to move away from legacy admissions.
State schools also have problems with excessive tuition expenses, but the value is still there for high-demand undergraduate degrees (mostly just for connections and job access afterwards) and definitely for a Master’s. They also accept almost anyone regardless of educational background.
US trade schools are a fantastic value, and more people should take advantage of them. They are a great option, but too many people don’t realize that for many careers a trade school or community college is perfectly adequate and won’t hold you back or saddle you with a mountain of debt.
> Combined with a burnout introducing system of standardized tests
Our standardized testing has problems, but it’s really not that stressful or difficult compared to, say, much of SE Asia.
"On the contrary, they are too accessible due to enormous tuition bills and federally guaranteed student loans (which cannot be discharged in bankruptcy). This toxic combination saddles many graduates with debt they will struggle to pay off for decades. Almost as if it was intended to create a modern form of debt slave."
How about making universities accessible without federally guaranteed studen loans? Debt slaving doesn't mean accessibility.
“Too accessible” was just a rhetorical flourish, obviously it would be great if everyone could get a good education. If “access” comes with crippling debt, better not to have that access. 4 year college isn’t the only way to get an education.
And yet my American ex-GF that went to one of these top universities with very good grades when she came to Barcelona to do a masters (in a lowly Spanish university) she was so far behind in knowledge compared to her peers she had to do a lot of work just to catch up.
I'm pretty sure most of these are just politics being played.
I feel the same way as you. But was unfortunately not surprised to see the replies you are getting here.
There are a ton of opportunities available right now to make new things. And make them better, more customizable, and more sovereign.
To the replies: be the change you want to see in the world, guys. That may be trite but focusing only on the negative will just make your own life shitty.
Software devs lost their pricing power due to LLMs but not exactly how most people think.
What's missed in understanding is 'how exactly does this functionality work for this specific case?' or 'can we implement this tiny one off feature in some legacy code base'. Both things are why you keep the guy that wrote it around. And you couldn't really replace him. Because digging into what he wrote was hard.
Now, LLMs can do that stuff better than the guy that wrote it.
Software devs were non-fungible. Now they're commodities. When things become commodities, they lose their value.
I'm not sure why I haven't heard people talk about this aspect. It's the biggest effect on jobs.
While this is true to an extent, oftentimes the important context is not in the code but in the head of the writer. The code is just the fence in the Chesterton’s Fence analogy. And that is still non-fungible and will (presumably) forever be.
> There exists in such a case a certain institution or law; let us say, for the sake of simplicity, a fence or gate erected across a road. The more modern type of reformer goes gaily up to it and says, “I don’t see the use of this; let us clear it away.” To which the more intelligent type of reformer will do well to answer: “If you don’t see the use of it, I certainly won’t let you clear it away. Go away and think. Then, when you can come back and tell me that you do see the use of it, I may allow you to destroy it.”
In big companies, the why is 80% of the work. I could swear actual dev work is less than 20% of a “developer’s” job at a standard large (non-SV/FAANG/tech-first) company. The rest is holding a lot of really weird organization-specific context in your head to make the right decision.
With my own tiny company, I used to answer questions about my code to support. Supporting the support. I remember doing that when working at big companies too.
Now, my support asks claude about the codebase to answer those sorts of questions. He's better than my memory.
I am yet to see this pan out in the enterprise. Enterprises are full of mini kingdoms built by VP+ leaders with the tools they prefer or were sold on. And many of these tools are inherently and sometimes by design are cumbersome, expansive and not onboarding friendly. LLMs haven't breached this domain and this domain empirically is 80% of enterprise software. I am yet to see direct examples of llm agents replacing say 4 engineers out of an existing 8 person team.
1. Mythos uniquely is able to find vulnerabilities that other LLMs cannot practically.
2. All LLMs could already do this but no one tried the way anthropic did.
The truth is one of these. And it comes down whether the comparison is apples to apples. Since we don't know the exact specifics of how either tests were performed, we lack a way of knowing absolutely.
So I guess, like so many things today, we can to pick the truth we find most comfortable personally.
People have found 0days assisted by LLMs for a while, and none of them wrote hype pieces to find an excuse not to release their 10x bigger model in the middle of a GPU shortage.
I really wanted to like anthropic. They seem the most moral, for real.
But at the core of anthropic seems to be the idea that they must protect humans from themselves.
They advocate government regulations of private open model use. They want to centralize the holding of this power and ban those that aren't in the club from use.
They, like most tech companies, seem to lack the idea that individual self-determination is important. Maybe the most important thing.
People started hating tech right around the time metrics became popular. I don't think it's a coincidence. AI just accelerates the trend.
The problem is the misidentification of AI as the issue. As long as we don't understand the real issue, we won't solve it. AI is just a tool. It's being used in a way that denies human agency.
Our cultural values need to shift away from safetism that demands centralization. And shift toward valuing human agency. That starts with talking about the core issue.
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