We lack robust frameworks for 'forward engineering' stochastic thermodynamic computation over molecular free-energy landscapes (which is basically what a "chemical soup" is doing) like we do for analog/optical/digital computing. This is why, as a field, medicine is so heavily empirical and reverse engineering oriented.
I think counter to the assumption of myself (and many), for long form agent coding tasks, models are not as easily hot swappable as I thought.
I have developed decent intuition on what kinds of problems Codex, Claude, Cursor(& sub-variants), Composer etc. will or will not be able to do well across different axes of speed, correctness, architectural taste, ...
If I had to reflect on why I still don't use Gemini, it's because they were late to the party and I would now have to be intentional about spending time learning yet another set of intuitions about those models.
This was a common argument against LLMs, that the space of possible next tokens is so vast that eventually a long enough sequence will necessarily decay into nonsense, or at least that compounding error will have the same effect.
Problem is, that's not what we've observed to happen as these models get better. In reality there is some metaphysical coarse-grained substrate of physics/semantics/whatever[1] which these models can apparently construct for themselves in pursuit of ~whatever~ goal they're after.
The initially stated position, and your position: "trying to hallucinate an entire world is a dead-end", is a sort of maximally-pessimistic 'the universe is maximally-irreducible' claim.
People could trivially switch their search engine to Bing or Yahoo, but they don't.
If ads are so overpriced, how big is your short position on google? Also ads are extremely inefficient in terms of conversion. Ads rendered by an intelligent, personalized system will be OOM more efficient, negating most of the "overvalue".
I'm not saying they should serve ads. It's a terrible strategy for other reasons.
Not at all. Vanishingly few things during the development process of a novel thing have truly objective measures. The world is far too complex. We all act and exist primarily in a probabilistic environment. A subjective evaluation is not so different than simply making a prediction about how something will turn out. If your predictions based on subjective measures turn out to be more correct than others, your subjectivity is objectively better.
Hence the author's main point: a good taste is one that fits with the needs of the project. If you can't align your own presuppositions with the actualities of the work you're doing then obviously your subjective measures going forward will not be very good.
I don't think the concern is whether a user can compile git from source on said platform, but rather whether the rust standard lib is well supported on said platform, which is required for cross compiling.
There is no evidence to indicate this is the case. To the contrary, all evidence we have points to these models, over time, being able to perform a wider range of tasks at a higher rate of success. Whether it's GPQA, ARC-AGI or tool usage.
> they are delegating to other approaches
> Faking intelligence is not intelligence. It's just text generation.
It seems like you know something about what intelligence actually is that you're not sharing. If it walks, talks and quacks like a duck, I have to assume it's a duck[1]. Though, maybe it quacks a bit weird.