It'll take a solid year and about 30k.
Any chance of even talking to a VC as an outsider?
171–180 of 661 posts
It'll take a solid year and about 30k.
Any chance of even talking to a VC as an outsider?
Earlier quoted context omitted.
Alphabet 2024 revenue: 350 billions dollars Anthropic 2024 revenue: 1 billion dollars Unreasonable doesn’t even start to capture it. Anthropic being worth 10% of Alphabet is beyond insane.
Valuation includes expected future growth, it's not just present value of future revenue given today's numbers. You may not agree with the market's estimation of that, but comparing just present revenue isn't really the right comparison.
I feel like the money itself makes less and less sense these days. It's just numbers that are becoming increasingly detached from the real world
Before you pat yourself on the back for being so smart and grounded... Remember, every technology you use today followed this pattern, with winners emerging that absolutely did go on to be extremely profitable for decades. Most of us remember the .com era. But in the early 1900s there was literally hundreds of automotive startups (actual car companies, and tens of thousands of supplier startups) in the metro-detroit…
Substitute fiber and routers for GPUs and this starts to look familiar.
people don't even remember the era before the current brands. like the time a bell offshoot almost crashed canada because they siphoned all the telephone money into bad routers.
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It's not clear to me that each new generation of models is going to be "that" much better vs cost. Anecdotally moving from model to model I'm not seeing huge changes in many use cases. I can just pick an older model and often I can't tell the difference... Video seems to be moving forward fast from what I can tell, but it sounds like the back end cost of compute there is skyrocketing with it raising other questions.
Its not clear to me that it needs to. If at the margins it can still provide an advantage in the market or national defense, then the spice must flow
Earlier quoted context omitted.
It's not clear to me that each new generation of models is going to be "that" much better vs cost. Anecdotally moving from model to model I'm not seeing huge changes in many use cases. I can just pick an older model and often I can't tell the difference... Video seems to be moving forward fast from what I can tell, but it sounds like the back end cost of compute there is skyrocketing with it raising other questions.
We do seem to be hitting the top of the curve of diminishing returns. Forget AGI - they need a performance breakthrough in order to stop shoveling money into this cash furnace.
That's still a pretty good deal for an investor: if I give you $15B, you will probably make a lot more than $15B with it. But it does raise questions about when it will simply become infeasible to train the subsequent model generation due to the costs going up so much (even if, in all likelihood, that model would eventually turn a profit).
The compute moat is getting absolutely insane. We're basically at the point where you need a small country's GDP just to stay in the game for one more generation of models. What gets me is that this isn't even a software moat anymore - it's literally just whoever can get their hands on enough GPUs and power infrastructure. TSMC and the power companies are the real kingmakers here. You can have all the talent in the w…
In this imaginary timeline where initial investments keep increasing this way, how long before we see a leak shutter a company? Once the model is out, no one would pay for it, right?
I predict a lot of people are going to lose a lot of money.
Clear, testable predictions are possible if you try.
Wait did I see “ Ontario Teachers' Pension Plan” as an investor? Are they putting Canadian public funds into Anthropic?
The compute moat is getting absolutely insane. We're basically at the point where you need a small country's GDP just to stay in the game for one more generation of models. What gets me is that this isn't even a software moat anymore - it's literally just whoever can get their hands on enough GPUs and power infrastructure. TSMC and the power companies are the real kingmakers here. You can have all the talent in the w…
As humans don't actually work like LLMs do, we can surmise that there are far more efficient ways to get to AGI. We just need to find them.