stri8ted

This model was likely trained months before deepseek released their paper.

I suspect the only reason those alternative providers have better up-time and more generous quotas, is because they don't have nearly the same amount of demand. Notice that Deepseek recently had to increase their pricing, once it gained it popularity.

> instead the queue of people in front of it will increase.

This can ultimately result in the system breaking. I don't think Anthropic engineers are that much worse than their peers, such that they are 10x more prone to causing outages due to bad deployments.

Reduced weekly limits, higher prices than competitors, paying well above spot price for space-x compute, all point to supply issues.

Demand > supply. It's impressive that customers have not migrated en masse to other providers, given the frequency of these outages. Perhaps switching costs are greater than some would believe. Or, qualitative differences between models continue to exist, despite matching on public benchmarks.

Translation, moderation, classification, guardrails, etc..

This is brutal, especially for small transactions. Note each failed attempt is another screening fee. Unfortunately, there is no good competition.

Demand > supply

Same

By what measure is there an overbuild? Every metric I look at, shows inference unable to satisfy current demands.

20k is small potatoes for the marketing impact.

They are doing both. Distilling Mythos down to affordable models, so they can continue to fund the business. And training Mythos level models at the high-end, to expand the frontier.

You seem to assume training on pelican would not result in improved performance on other similar tasks. Why?

Still has a 1.78T market-cap. It will be OK.

Its actually useful, when you are launching into a long monologue and want periodic acknowledgement that its "listening".

Way too expensive. Google vision OCR (which they failed to compare against), is $1.50 per 1k pages. Vs $4 from Mistral.

What metrics are you using to classify it as a downfall?

Is there something in the post that you find implausible or don't believe to be true?

I doubt this is representative of real world usage. There is a difference between a few turns on a web chatbot, vs many-turn cli usage on a real project.

Entire segments of the podcast sphere are making their money talking about these so-called unspeakable subjects. Why don't you share what you really think.

Those are the same thing

48 GB is not consumer hardware. But fundamentally, there are economies of scale due to batching, power distribution, better utilization etc.., that means data center tokens will be cheaper. Also, as the cost of training (frontier) models increases, it's not clear the Chinese companies will continue open sourcing them. Notice for example, that Qwen-Max is not open source.

Do you have any evidence to support this view?

Price Input: $2.50 / 1M tokens Cached input: $0.25 / 1M tokens Output: $15.00 / 1M tokens

https://openai.com/api/pricing/

Flock has put out a report claiming 10% crime in the US is solved using their technology. There are of course counter argument, that claim this is not valid.

https://www.flocksafety.com/customers/how-many-crimes-do-aut...

I take into account publicly available information (news articles), factor in personal anecdotes, and reason about human nature and incentives. I know the extent of reported abuses, and I do my best to extrapolate. It's not perfect, but such is life.

To be clear, even if we all agreed on the data, I still would not expect everyone to take the same position. There are subjective differences in values.

It's clearly true there have been abuses as a result of this technology. And its also clearly true criminals have been caught as a result of the cams, that otherwise would not have been.

If you believe the costs of the the abuses, and potential abuses, exceed the benefit, then at least be honest about the trade-off, because there are real benefits.

Personally, I believe the costs, on net, are worth the benefits. And in so far as the costs can be further reduced, without loosing most benefits, then great. This is not right or wrong. It's just a question of values, and how you weight the costs vs benefits.

Don't down-vote this all at once.

Can you show some comparisons for WER and other ASR models? Especially for non english.

How is this content related to HN? Are there any submission criteria?

Exactly. As far as I'm concerned, the benchmark is useless. It's way too easy and rewarding to train on it.