Exactly, these companies will keep leveraging more and more because they know the govt will step in and print whatever number of trillions of dollars needed to fix the accounting. Then they’ll tell us “core” inflation is only 2.8%.

And that’s why they’re trying underhanded tactics to inflate earnings and IPO directly into the index funds, so every American’s 401K will legally have to rebalance and invest in them. They’re racing to fleece retirement funds before the bubble bursts.

Not financial advice, of course :p but people should really consider getting their stuff out and into self-directed funds or whatever it is US people do to not depend on auto-allocated funds.

Of course they don’t, that’s why they’re building bunkers. Thinking it’ll slow us down, as we’ll open their bunkers like cans of tuna. A bunker only works for so long, then the survivors start hunting for them like delicious shipwrecks.

Money printer go brrrrrrr

Although, most people aren’t talking about Alphafold when they’re talking about AI. They’re usually specifically referring to the generative transformer models that are currently all the rage.

I doubt anyone would care too much about a linear regression model, or multi-layer peceptron , for example.

Both Uber and Spotify (and AWS too) had economics of scale going for them - the more users they have, the more the infrastructure could be leveraged. This does NOT work for LLMs. More users means using more compute, more advanced tasks (like coding) uses exponential amounts of compute. A single user running a complex task can make 8 Blackwell GPUs run full tilt, and you don’t even have any guarantee that the output will be useable.

There are a few narrow areas where LLMs might be successful, like scanning for security vulnerabilities or searching large amounts of documents. The massive amount of money invested will never be recouped with these usage scenarios.

solving something like the Erdős unit distance conjecture

Tell me you listen to media news cycle without understanding what that actually mean without telling me that.

That’s not exactly what happened, isn’t it.

Not to bring up what’s also been accomplished in cyber security

Multiple new vectors of attacks, automation of attack pipelines…

That’s simple, because the people making laws and overseeing the adherence to those laws are great buddies with those same CEOs.

So, corruption.

Though i do agree with you, there is no such thing as too big to fail. Government shouldn’t have any handouts to corporations.

late to streaming, but practically the first subscription based system to watch movies/tv online.

First years of Netflix were the best, the product began degrading quite early on. but that was mostly companies realizing that instead of licensing their content on Netflix, they can make their own platforms.

Late to streaming? Netflix was the first big time streaming service that I ever heard of. The main reason their streaming service was able to take off like it did is that nobody else of significance thought that streaming was worth pursuing. What other companies were offering streaming services at anything approaching scale before Netflix?

Imagine having a streaming service so bad it fails twice

I love that nobody watched anything on Yahoo! Screen except for that one season of Community

You’re right that people can and do max out the expensive plans. Its very difficult to say how often. I just think a majority of anthropics customers are businesses, who often pay per token for easier scaling etc. According to the company, enterprise employees use about $150-$250 per month, (possibly max plans have similar use, which would support your view) but thats in API tokens which they probably have big margins on, so it’s less likely anthropic are burning money on inference. If you want to convince me otherwise, its not enough to say that it can happen, it has to be frequent enough to outweigh the B2B sales. They are however likely losing money overall due to training costs etc.

lfm2 works like greased lightning on the NPU built into the current macbook M5.

I’ve got an old 1060ti in my server. Ollama shares it with just a couple other containers. Electricity here is majority hydro with some natural gas, $0.08/kWh.

It’s a little slow, but I can comfortably run qwen3:14b. Of course that’s not all done on the GPU, a large part is offloaded to server ram (generally 32GB available so more than enough headroom)

My server and my gaming PC combined last month came out to $13.32

I remember my computer not being fast enough to even play an MP3 file. Two years later, my computer was capable of running 3D accelerated games, browsing the internet at broadband speeds and playing videos.

Sometimes technology advances fast. We could be entering such an era as there are major investments taking place and global competitors will rise to the occasion to market these to a broader audience.

I think it will be entirely possible for consumers to use a decent LLM on their computer in a few years time.

Because when you’re old enough to remember what AIM chat it’s could do 25 years ago, it stops being impressive what today’s chatbots can do…

C’mon, that’s just silly.

Why not? Why Microsoft develops it’s .NET ecosystem? Why Google develops Go/Dart? It costs them lots of money and they give it for free.

The answer is: they don’t earn money on it directly, but these tools are a way to tie programmers to their cloud services. If you use .NET you’ll probably end up on Azure. If Go - probably you’ll use GCP.

So I suspect the same will be with LLMs. At some point they will say: “hey, you can use this LLM however you want, but as you are already using it, then you may want to know our platform is optimized for it”

A large majority definitely hate it to the point of having blinders on for sure.

On one side you have corpo hype/lies, and the other is LLM is slop garbage and terrible for anything, also developers wrote perfect code before LLMs and now everything that breaks is AI slop caused.

Profit ≠ success

An older co-worker seems to ask AI for help during work, we are blue collar. But the Owner of the company does not seem to use it whatsoever.

I ask Claude on occasion, to see if it will say something smart (it was mostly useless as fuck).