I mean once campfire is full featured free and easy to self host. Completely open source slack replacement.
I imagine it's also infinitely better than anything an in house team could vibe code.
You don't need AI for a cheap slack alternative.
That's why I don't buy any of this.
Companies are not bothering with the free/open alternatives.
Unless the real power of LLMs is making it easy for greg in HR to self host these existing alternatives. But, that a trillion dollar market does not make.
> But we’ve hit the ceiling for SSE. That terrible Claude UI refresh gif is state of the art for SSE. And it sucks.
This is nothing to do with SSE. It's trivial to persist state over disconnects and refresh with SSE. You can do all the same pub sub tricks.
None of theses companies are even using brotli on their SSE connection for 40-400x compression.
It's just bad engineering and it's going to be much worse with web sockets. Because, you have to rebuild http from scratch, compression is nowhere near as good, bidirectional nukes your mobile battery because of the duplex antenna, etc, etc.
Just to add. The main value of websockets was faster up events pre http2. But, now with multiplexing in http2 that's no longer the case.
So the only thing you get from websockets is bidirectional events (at the cost of all the production challenges websockets bring). In practice most problems don't need that feature.
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if 100% of the money they spend is in inference priced by tokens (they don't say about subscriptions so i asume they lost money), yes they make money, but their expenses are way higher than inference alone.
so they can make the gpu cost if they sell tokens but in reality this isnt the case, becouse they have to constaly train new models, subscription marketing, R&D, And overhead.
antropic in general lost way less money than their competitors
i will take this number in particular the projected break even but googling say
Gross margin in this case is how much money they do whit the GPU
"
Gross Margins: Projected to swing from negative 94% last year to as much as 50% this year, and 77% by 2028.
Projected Break-even: The company expects to be cash flow positive by 2027 or 2028. "
i will not be as bullish to say they will no colapse (0 idear how much real debt and commitments they have, if after the bubble pop spending fall shraply, or a new deepseek moment) but this sound like good trajectory (all things considered) i heavily doubt the 380 billions in valuation
"this is how much is spendeed in developers
between $659 billion and $737 billion. The United States is the largest driver of this spending, accounting for more than half of the global total ($368.5 billion in 2024)"
so is like saying that a 2% of all salaries of developers in the world will be absorbed as profit whit the current 33.3 ratio, quite high giving the amount of risk of the company.
Does a GPU doing inference server enough customers for long enough to bring in enough revenue to pay for a new replacement GPU in two years (and the power/running cost of the GPU + infrastructure). That's the question you need to be asking.
If the answer is not yes, then they are making money on inference. If the answer is no, the market is going to have a bad time.
GPUs do not wear down from being ran at 100%, unless they're pushed past their voltage limits, or gravely overheating.
You can buy a GPU that's been used to mine bitcoin for 5 years with zero downtime, and as long as it's been properly taken care of (or better, undervolted), that GPU functions the exact same as a 5 year old GPU in your PC. Probably even better.
GPUs are rated to do 100%, all the time. That's the point. Otherwise it'd be 115%.
No, you're fundamentally wrong. There's the regular wear & tear of GPUs that all have varying levels of quality, you'll have blown capacitors (just as you do with any piece of hardware), but running in a datacenter does not damage them more. If anything, they're better taken care of and will last longer. However, since instead of having one 5090 in a computer somewhere, you have a million of them. A 1% failure rate quickly makes a big number. My example included mining bitcoin because, just like datacenters, they were running in massive farms of thousands of devices. We have the proof and the numbers, running at full load with proper cooling and no over voltage does not damage hardware.
The only reason they're "perishable" is because of the GPU arms race, where renewing them every 5 years is likely to be worth the investment for the gains you make in power efficiency.
Do you think Google has a pile of millions of older TPUs they threw out because they all failed, when chips are basically impossible to recycle ? No, they keep using them, they're serving your nanobanana prompts.
GPU bitcoin mining rigs had a high failure rate too. It was quite common to run at 80% power to keep them going longer. That's before taking into account that the more recent generations of GPUs seems to be a lot more fragile in general.
Yeah what's crazy is most of these companies are making accounting choices that obscure the true cost. By extending the stated useful life of their equipment, in some cases from 3 years to 6. Perfectly legal. And it has the effect of suppressing depreciation expenses and inflating reported earnings.
I imagine it's also infinitely better than anything an in house team could vibe code.
You don't need AI for a cheap slack alternative.
That's why I don't buy any of this.
Companies are not bothering with the free/open alternatives.
Unless the real power of LLMs is making it easy for greg in HR to self host these existing alternatives. But, that a trillion dollar market does not make.
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