On what are you possibly basing this? The fact that there hasn't been a new model release in 6 weeks?
You can now have a model work on a task non-stop for a day or more. This was unthinkable 12 months ago, and unstable 6 months ago.
If you are searching for evidence of capability, just look at the amount of projects, blog posts and videos on game remixes, hardware reverse engineering, new compilers and runtimes that has started coming out in the last 6 months. Slop? Sure, but this kind of slop didn't exist at this level 6 or 12 months ago.
https://news.ycombinator.com/item?id=50422069
It's really very hard to pin down progress in this domain, companies are definitely targetting benchmarks.
One bit of evidence I would look at is the maths results this last year which have been impressive, that was a huge expensive brute force effort, but it is still good progress.
Opus 5 vs. 5.5 is a clear stepup.
Problem is, you need to do a diverse set of experiments to recognize it. Blender support got relevant better,t he amount of corrections got less etc.
But everyone has a different view of this, it'll be interesting to see how it plays out.
Before Opus 5.0, anything with 3d was not doable at all. Starting with Opus 5, it can build you cloth simulators and more.
But I do expect a combination of fast progress to continue alone due to the fact that hardware will catch up and will be faster.
And when we reached a real bottleneck, the next thing will be to put the frontier model on a chip and advancing world models and other architectures.
We are still 'just' steamrolling LLMs.
Opus 5.5 is capable of completing very long running tasks and managing many threads of work with subagents without getting confused in a way that simply wasn't possible before.
Why is this? Competing on price, or compute somehow getting more expensive?
Anthropic has no value proposition - just being 3-6months ahead in frontier models vs. open-weight doesn't justify trilion dollar valuation.
My company buys Claude because it’s a trusted name with a user-friendly interface and integrations with a lot of business apps.
This “open weight models will take over based on price” is analogous saying that Linux and LibreOfficr will displace Windows and Microsoft Office in the workplace because they’re drastically cheaper.
Another analogy is that people talk a lot about the resurgence of audio CDs, but if you look at sales numbers it’s about 4% of peak audio CD sales from the year 2000. Sometimes in society a trend is more that people keep saying that a trend is happening rather than a trend is really happening.
That surprised me. I didn't expect K3 to be as good as it was and now with 3.1, it's clear (imo) that the gap is closing. Anthropic still has a minor edge but from the 'feel' of these open models, that gap is negligible, not a moat.
You can't just literally drop LibreOffice into an organization and have it automatically and seamlessly work.
LLMs are, definitionally, fungible. Their input is tokens. Their output is tokens. They have minor variations in chat templates and can be trained to perform better in a particular harness (like training GPT in Codex).
Do you or your friends at work use redis? Postgres? Are they hosted at "Redis Inc" and "Postgres Inc"? No, they're commodities hosted at a huge number of places.
In that context I don’t think I’d describe 10% as “high risk.”
So maybe it's not high risk enough for you, but it is definitely high risk enough for the market.
But the best approach is just comparing rates. Go to https://archive.epa.gov/epawaste/nonhaz/municipal/web/pdf/bo... , and you will see a huge list of companies whose bonds are classified by armies of analysts as "less risky" than these 10% Anthropic bonds. Is Anthropic less risky than AT&T, or BP, or Firestone Tire & Rubber Co? The market says "no".
currently US long term bonds have very low yield and are being issued less as usual buyers move to gold/stock -- trust in US gov. has eroded especially in fiscal matters. The budget keeps growing, interest rates are still too low to combat inflation and debt is ever-expanding, without drastic measures taken to stabilize the situation: thus, high bond yield - we pay you premium to have at least someone buy it due to trustworthiness not being the sole attractor anymore
Recently CoreWeave's bond yields spiked to 16% which represent an 18.8% probability of default per year.
You gotta be kidding. HuggingFace, a website to download files, was sold for 13B.
This is what keeps me up at night. That fiber that got overbuilt in 1999 is still there spitting photons. That Vera Rubin gathering dust on a shelf will be a paperweight in 5 years.
1. Open source models lag frontier models in capability by about 2-3 quarters
2. New frontier models get optimized for the next generation of GPUs
So the GPUs are left being only able to serve either obsolete or open source models, which in either case makes them significantly less valuable.
(And then of course once they start running they last at best 4 years)
- margins shrinking at Anthropic
- Google getting thwacked by missed earnings
- OpenAI missing funding target
- price war
- Microsoft revising capex projections down
- Plateauing of model capability improvement
What's weird to me is that you don't see a lot of people making deals that seem way too good to be true but yet the total numbers are absolutely gigantic. Throw on the fact that the stranded assets will have a shelf life, it really seems terrifying. Yet everything is being priced as pretty darn risky. I think maybe there can be a big slowdown without a dramatic pop. A sort of grind down. But there's not a lot of room for error to prevent a pop so I guess it will happen? I don't know its very weird.
Also of course this is all predicated on models not making another dramatic leap. The signals out of the cutting edge labs don't really suggest they have a model that would be as dramatic of a leap as Mythos was when it came out in the hopper. Their code quality seems about as mediocre as what the publicly available models can do. The OpenAI math results are very impressive but that's ripe picking for AI. Also they keep talking about a coordinated training slowdown which is textbook antitrust so they seem to want the government to force their hands off the "spend money on R&D" button.
So I don't really know. I guess I would say purely on vibes that this doesn't feel like a bubble but the size of the build out is just so massive that there really isn't a big window for a success case.