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121–130 of 166 posts
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Earlier quoted context omitted.
Isn't the consensus that the MOE architecture and other optimizations in the newest gen models (GPT-5, Gemini 3.0 to come, etc) will reduce inference costs by 50-75% already?
Kind of. Frontier LLMs aren't going to get cheaper, but that's because the frontier keeps advancing. Price-performance though? The trend is clear: a given level of LLM capability keeps getting cheaper, and that trend is expected to hold. Improvements in architecture and training make LLMs more capability-dense, and advanced techniques make inference cheaper.
One of the main selling points to MOE, is that the architecture is designed such that you can re-train experts independently, as well as add new experts, change the size of an experts parameters, etc, without retraining the entire model.
If 80% of you usage comes from 20% of your experts, you can cut your future training costs SUBSTANTIALLY.
I have sat with these numbers for a great deal of time, and I can’t find any evidence that Anthropic has any path to profitability outside of aggressively increasing the prices on their customers to the point that its services will become untenable for consumers and enterprise customers alike. This is where he misunderstands. Enterprise companies will absolutely pay 10x the cost for Claude. Meta and Apple are two lar…
Firstly, a huge amount of labour that can be accelerated by LLMs fall into the "bullshit jobs" category, where you can make someone faster at writing emails but the emails themselves don't really contribute much value. The majority of LLM use I see falls into this category. Many people can speed up parts of their job, but you can add as much efficiency as you want without actually impacting the bottom line -- and for various reasons that are not tractable right now, including with LLMs, businesses aren't able to get themselves to remove these roles.
Secondly, the median company is incapable of doing the things that aren't driven entirely by hype or political promises made by executives. We still exist in the universe where they prefer to have all their staff attrition out due to not getting raises, then end up paying the same amount for a bunch of folks that have no knowledge of the business when they inevitably have to replace their best talent.
With all that said, I'm sure a few savvier places would happily drop $1000 month per head if the value is there, but I really think in the average case that this would be more about marketing than any logic. People still buy Informatica in 2025 for much more money than they spend on LLMs.
Earlier quoted context omitted.
Kind of. Frontier LLMs aren't going to get cheaper, but that's because the frontier keeps advancing. Price-performance though? The trend is clear: a given level of LLM capability keeps getting cheaper, and that trend is expected to hold. Improvements in architecture and training make LLMs more capability-dense, and advanced techniques make inference cheaper.
> Frontier LLMs aren't going to get cheaper One of the main selling points to MOE, is that the architecture is designed such that you can re-train experts independently, as well as add new experts, change the size of an experts parameters, etc, without retraining the entire model. If 80% of you usage comes from 20% of your experts, you can cut your future training costs SUBSTANTIALLY.
It's not entirely impossible, but I remain skeptical until see a proof that it, first, works. And, second, that it actually has an advantage over "we'll just train another base model from scratch, but 10% larger, with those +5% performance architecture tweaks, and a new modality blender, and more of that good highly curated data in the dataset, and fresher data overall, and it'll be glorious".
Earlier quoted context omitted.
That doesn't tell us what percentage they own, though. When you invest in a company and the value goes up, your percentage doesn't change (unless there are additional investors)
that's really naive im afraid. you have to take pro rata or the percentage goes down. amzn did not take pro rata.
Amazons investment in Anthropic was in the form of convertible notes, which they have converted entirely into equity by march of this year. At that time, Anthropic was valued at 61.5 billion and Amazon (in their filings) said their investment was worth 13.8 billion, so about 22% of the company.
Then, there was another round in September where Anthropic raised 13 billion more at a valuation of 183 billion (so the new investors are buying about a 7% stake in the company). Without more details, that would lower amazons percentage to about 20% (old investors hold 93% of the company, so Amazon's 22% of the remaining 93% comes out to about 20%). There are probably other details that lower that percentage a bit, but i think the 15-19% ownership estimate is pretty accurate.
One day we will westerners will learn why the Chinese are releasing models that are optimized for cost of training n yet good enough to run locally or cheaply. when the music stops, suddenly a lot of people won't just sit on the ground but plunge into the depths of hell.
i'm starting a new trend: ask every person that is so certain about the negative outlook how big their short position is. so how big is your short position? please let us know.
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It's useful for financial planning. Less useful for overall financial reporting given how volatile it is.
I should've been more clear. How can you talk about ARR if you only have 1 year? How do you know it's recurring? What data do you have (historic) that makes you believe the revenue will happen again? Is this based on signed contracts etc so you have some guarantees?
Does it seem strange that this has 121 comments within 4 hours and somehow is ranked 131st on HN? I would think this would be front page with those type of numbers.
Earlier quoted context omitted.
i'm starting a new trend: ask every person that is so certain about the negative outlook how big their short position is. so how big is your short position? please let us know.
here's another trend: every time a person is on this hype bandwagon ask them how much are they invested in nvidia/ms/openai/etc I am not invested in anything except popcorn to watch it burst;)