As each new tool drops it makes me wonder if I should convert. Currently I mostly code in vs code or chat with Claude code but I don’t really mix the two even though I know I can with the Claude add on. My gf uses colab with Gemini and it seems rather spiffy for data science. And now antigravity. I just wonder when it will end and devtools will slow down their development cycle a bit.
For me this feels irrelevant. These tools are marketed for developers for their day-to-day jobs that involve building products. Devs don't look up information on people or build some complex mathematical things daily. They build things that consist of different parts, which in turn can consist of different contexts and can be a combination of other things as well. It can be a straightforward approach or it can be a legacy codebase that also need to incorporate new features with new stacks. The real test is in the real world scenarios. But every time it's about a narrowly scoped thing, the tests, the marketing. And they try to build an image that the combination of these scoped tasks can somehow bring you the ability to build at large scale. They don't say it, but they implicitly mean it with the way they present all this. Computers can compute, they can detect patterns and do analytics part, they can build assumptions based on the data they have. But they need the data, they need parameters, they need not only an operator, they need the source for the material they base their computations and output on. And somehow all the marketing completely ignores this fact. And this is damaging.
As and old physicist and a computer programmer these days, I am so jealous of the things you can build these days "vibe coding". That someone with moderate knowledge of programming can build these things is fascinating.
Now, on the physics part, I would like to "see" the phase transition that you have in 2D. I don't know if that is missing from this simulation or if I am not looking at it with the correct eyes.
I really enjoy using the poem Love and Tensor Algebra as a visualisation benchmark for models. There's something about it that requires a sense of abstract processing.
In my eye, GPT models always perform horribly at this, with Claude and Gemini coming in close second/third.
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In my eye, GPT models always perform horribly at this, with Claude and Gemini coming in close second/third.