1. Evals (once you have your rubric defined and tuned using a reasoning model, jev can be great for running periodic evals especially those that run daily.

2. e-commerce catalog classification 3. quick search using anything as context and query mapping to a pre-defined set.

What makes you think these companies (and I'm not a fan of all their motives) are not interested in developing research? The motives may be self-serving, but it is undoubtedly and objectively accelerating research.

However, as it has happened in the past, once there is a technological wedge, technological advances will move forward, whether some community likes it or not, and human ingenuity will find ways such that the benefit is greater than the risk.

"In other words, Stripe did not buy a router. It bought a strategic frontier AI systems security and alignment asset. We believe combining this asset with Stripe’s existing infrastructure strengthens the ecosystem’s independent alignment capabilities in ways that would be difficult for any single lab to accomplish by itself. As such, this acquisition is net positive for the health of the independent frontier ecosystem."

Contrast with the clarity reflected in the letter Stripe reportedly sent to its investors.

"We see capital and intelligence are becoming the two digital flows undergirding every business ..... going forward every developer will also need a straightforward and reliable way to manage their intelligence pipeline" So basically Stripe already enables companies to manage capital. It now also hopes, with the acquisition, to jump to the forefront of managing intelligence / tokens for them. By bundling two core capabilities for AI forward companies they increase their offering attractiveness to businesses.

At this price range $0.87per 1M they will get a lot of usage of people trying it out. Given the benchmark numbers, for many people and many use cases this will become their primary driver. There are people and use cases where Fable, Sol will work better but those are likely not the target of DeepSeek anyway.

In terms of performance and price pareto curve I don't think any model can beat this today (though openAI is doing some exciting recent work in efficiency) - which is a remarkable feat for the DeepSeek team.

Either way, what a time for consumers of these models :)

Eventually the pricing should be more stable.

For coding I still use 5.5 w/ Codex and prefer that to other models + harness combinations.

They somehow conflate their value with 'safety'. While it's an admirable internal quality for the company to have, their treatment of their user base (developers, users) has been bordering on indifference and their stance bordering on arrogance.

As competition heats up, there is a very real chance of them shooting themselves in the foot with friction such as this (to be fair not completely in their control but also they had their share of responsibility that led to this)

So the same person, was using similarly competitive tools, and showing that the output was hard to discern (indirectly the implication was also that implementation was fairly trivial in both of those). A better analogy would not be different process and widely different tools but for example two power drills. Sure, folks could still prefer one over the other, but that's a different claim that saying X is objectively better than Y when both are directly competing on very similar dimensions.

Assuming you meant Claude code: I'd love to learn more about "Codex and Claude are very different" because maybe I'm assuming just based on my use case where I use both of them interchangeably for the same thing (coding web and mobile apps)

I think a more appropriate rephrasing would be 'You cannot simply make a claim that (model + harness) X is better than Y, but then have no discernible difference on dimensions you care about'. In the case of latest of claude code vs codex with gpt 5.5) both are similar enough in the dimensions people will care about in evaluating (vs. differing wildly in cost or time taken).

And then compare the $45B revenue from Anthropic to see if it's mostly break even or if one of Anthropic/SpaceX came out ahead on the contract.