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"I am not sure how many people will run AI models locally. It still seems like a niche application to me. However, it will make decent machines to play video games..."

This is the 2026 edition of Ken Olsen: "There is no reason anyone would want a computer in their home"

5 comments

> This is the 2026 edition of Ken Olsen: "There is no reason anyone would want a computer in their home"

Digging into this:

> In conclusion, there is evidence that Ken Olsen did doubt the need for computers in the home, but the evidence is based primarily on the testimony of David Ahl who was perturbed when the personal computer project he championed at DEC was not supported by Olsen in 1974.

> Olsen’s resistance may have been similar to that expressed by another DEC executive, Gordon Bell. In 1980 Bell thought home terminals would act as gateways to remote computers which would provide appropriate services.

* https://quoteinvestigator.com/2017/09/14/home-computer/

It was supposedly said in 1977: most computers at that time were not small, and so it would not be surprising that people would not expect the general public to desire a large, power-hungry, noise-y apparatus in their house.

That's exactly the point. Until recently, AI models that could run on home machines were so bad that it was very hard to imagine anyone wanting to.

And, like the overly large machines of 1977, models are getting faster, leaner, and better. It's happening a lot quicker, though.

This is why I'm bearish on Anthropic, OpenAI, and friends. I am not confident that we will continue to see the same pace of improvement in frontier model capabilities as we have seen over the past year or two - not using similar mathematics at least. But I think that getting results that are close enough to the same standard to be a realistic substitute but in a model small enough to run locally may well happen quite quickly. And if it does - where is the moat to defend these AI organisations with their astronomical budgets when they're already starting to price more realistically and that's already killing a lot of the hype they've enjoyed until very recently? They have an accidental moat because they bought up the global supply chain for storage but that surely isn't going to last once the data centres to hold that storage are becoming liabilities.

If model performance asymptotes and CPU/GPU and RAM keep growing, even slowly, then eventually we will have frontier models on desktop that are totally competitive with hosted. It’s only a matter of time.

You already can if you’re willing to spend many thousands of dollars on a beast of a machine. I’m talking about middle tier desktops and laptops here. Maybe eventually even phones.

The only way hosted stays strongly competitive in that world is if they can keep pushing the frontier or by playing the classic social media and SaaS games of network effect building and integrations.

Many people might still use hosted, of course, but what I really mean is that their multiples won’t be justified and they will have little to no moat. AI will become commoditized, like a sophisticated next generation form of an encyclopedia with search.

> This is why I'm bearish on Anthropic, OpenAI, and friends.

Just because you can do more and more things at home (thanks Moore and Dennard), doesn't preclude needing things also done remotely. The number of at-home systems seems to have fed a growing number of remote systems (especially once always-on connectivity became ubiquitous).

It's basically the angle Apple is going for: do as much locally (for the sake of privacy), and then offload when it becomes "too much".

I agree that one doesn't preclude the other. But the sky high valuations we've been seeing for the AI industry recently can only be justified if they bring about a fundamental change in our society and those companies continue to bring in the lion's share of the resulting profits. I don't see why everyone else in our society - particularly other large businesses with lots of money to invest - is going to play a game by the AI companies' rules once they can take their ball and go home and still have most of the fun without paying much for it by comparison.

We kinda ended up with terminals connected to mainframes anyway. The terminal being the web browser, and the mainframe being SaS. So it wasn't that far off.

the network is the computer

It doesn't really need this much explanation.

People take these quotes out of context all the time. Said in a business context, there was no need, at that time, for someone to have a personal computer.

There's no business justification in 1977 for a personal computer department at a business. It's similar to the gates quote about RAM (I think it was 64KB?).

These statements aren't meant to be forever quotes. Their business plan quotes.

> It's similar to the gates quote about RAM (I think it was 64KB?)

640, and Bill Gates said he either never said that, or at least never remembered having said it. I think there is no evidence anywhere that he did.

https://www.computerworld.com/article/1563853/the-640k-quote...

That exact quote? No, never. He said something like: current computers at the time had 64kb of RAM, so the OS was designed with a limit of 640kb, and he believed this would give them 10 years of future proofing. As it happened, that limit was reached much faster, in about 6 years.

MS-DOS didn't create that limit; the physical memory map of the 5150 did. So Microsoft (and Gates) would not have made that decision.

You are right. The quote must have been slightly different then. I'm sure about the 10 years part.

Or maybe he simply made a mistake. Big deal. This doesn't speak negatively of his other achievements.

He had a long career and presumably many successes, and is fallible like the rest of us. But a half-remembered zinger with no context makes for zippier posts I guess.

The early popularity of Minitel, the continued popularity of ssh/tmux, and the web browser itself indicates that bespoke client applications are not the only way. He wasn’t directionally wrong.

The simple explanation is that predicting the future is generally impossible. It doesn't matter if it's Olsen or anybody else.

I will not be spending thousands in hardware to run the worlds most mediocre llms at meh speeds. Sorry. I know for llm bros they think every output made by an LLM is magic, like every NFT guy thought every NFT collection was game changing, but there's nothing useful you can do with llms and 128gb of RAM (and there never will be) unless you have llm psychosis. Who cares.

Nothing isn't quite right but you wouldn't be using it like the hosted ones. 128gb is more than enough to run models to index my files and photos, denoise photos / AI photo masking, magic eraser type tasks for images, frame generation for gaming, etc.

Even for a lot of LLM type tasks, 128gb is likely more than enough to control a lot of PC configuration and automation with natural language.

or "640K ought to be enough for anybody."

https://quoteinvestigator.com/2011/09/08/640k-enough/

Nobody ever said that, at least not as an assertion or prediction. The actual instances of similar language are from multiple people describing their earlier thoughts before they learned it wasn’t true.

There’s no public proof this has ever been said, and if it was, if it was not taken out of context.

I have that many browser tabs.

You seriously think running LLM is the same thing as general computing?

It’s better, it’s useful even for those who don’t have a deep knowledge of computers. I’d expect more AI users than programmers, than ms-word users, than excel users.

You are confusing "using AI" with "running LLM locally".

That’s too strong of an assertion.

Local models aren’t deterministically equivalent in capabilities to foundation models. Home computers are turing complete; just like a mainframe. They are just slower. Often not slower enough to matter.

Most people are ok with slower. An AI that lets you edit a family picture, in say 30 seconds, locally is preferable to one that is instantaneous but requires you to submit that picture to examination/storage/training/sale in someone else's AI ecosystem. If i want to crop my ex out of family photos, i should not have to first give that photo to Microsoft. If want an LLM to write a book report for me, i dont want it also alerting my school. And if i write a memo for a client, and i want an LLM to check the spelling, i dont want that memo leaked either.

I'd like to think so but the existence of Google and Apple and Microsoft's cloud based photo tools with phone integration suggests that's false.

You could run a pretty good home server on $50 of gear and yet we never saw any real adoption of OwnCloud/NextCloud style products as an alternative to Google Drive/Photos or Apple Cloud.

Why should LLM/Transformers be any different? Especially when you need a proper expensive GPU to run them instead of a Raspberry Pi?

Apple's photo tools run on device, and they'll probably ship more on device foundation models at WWDC too.

On-device AI is going to be important, I think. It doesn't have to take the form of a chatbot UI to be useful.

After the latest round of cloud storage price increases my non technical wife has been asking if we can do local backups instead...

> Most people are ok with slower. An AI that lets you edit a family picture, in say 30 seconds, locally is preferable to one that is instantaneous but requires you to submit that picture to examination/storage/training/sale in someone else's AI ecosystem.

Maybe if you ask them that question, but if you show them two products, they'll definitely prefer the faster one. 30 seconds is a long time to watch a progress bar.

Plus there's the other question. If this thing is slower ... what's the price? The desktop/mini-pc version of this is $3000, after all. At this performance level what is an acceptable price for the laptops?

People definitely aren't going to accept more expensive + slower ...

Fast and public, or slow and private. Not everyone wants, or is allowed to, share their data with the AI world. And do not doubt that every bit shared with an AI service will be used for training.

The question here is about markets though. Not everyone wants x but if the vast majority of people want y, x is going to be niche and expensive.

You don't think the commercials of Google's AI photo features aren't going to have an impact on Apple users of their phones can do a worse version of that feature and it takes longer?

It’s completely technically possible to have cloud services where customer data is opaque to the provider. Some of Apple’s services are like this already, for example.

I think there’s a sweet spot currently with munging your data blindly on the server so that your client device battery still lasts all day.

Meanwhile Apple and others push on with making client side models more efficient so that eventually the server costs and complexities go away.

This.

If asked to choose between photo editing done within 3s using cloud provider vs an average of 30s using local compute, most consumers will choose the former without hesitation.

Most users' usage is also going to fall nicely in the free tier of a typical freemium pricing model, like ChatGPT today.

People who talk endlessly about local inference have no idea about user workflows and usability.

dont want to share my pics with "cloud services"

You may not, but experience shows that most people are just fine sharing the most personal stuff not only with cloud services, but with hole world through anti-social media.