alt Hacker NewsThough, Modular should have been the team to do it. My theory is that they raised too much money too soon. With that kind of money, you get anxious investors waiting to see some magic on quarterly timelines. So Modular was forced to be compatible with Python as there's no other way to win quick developer mindshare. (Though I don't think they managed to do that either).
A closest counter path I would have expected Modular to follow was Zig or Oxide computers (I know not apples to apples comparision). Start actually attacking the problem with hindsight and lessons of 30 years of Python, build something fresh, and try to patiently win the market.
Rust is not going to win this market. The language has too much syntax friction to win over data science/AI folks and doesn't offer too much in parallel programming world. Julia, although beautiful attempt, couldn't gather enough support outside academia.
In fact, if Nvidia cuTile, Triton, Jax keep delivering, Python seems unmatched at the moment. It is likely to be in the similar position that C/C++ have been in embedded and firmware world.
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> My theory is that they raised too much money too soon.
That's also my feeling. And that's the curse of many VC funded companies. And they are not even in the classical state of enshitification yet.
> Rust is not going to win this market.
Agree. Rust will never win this market. Nor Zig, which has the same genetical flaws as C++ for accelerators (excessive usage of pointer semantics among others).
> Julia, although beautiful attempt, couldn't gather enough support outside academia.
I will look mean, but for me, Julia is a language that never went to the design board. It sticked to a "Let's put Python on top of LLVM and add a proper GC" with one single objective: "let's make a clone of Python but fast".
My feeling is also that it is an academia niche and will remain one.
> In fact, if Nvidia cuTile, Triton, Jax keep delivering, Python seems unmatched at the moment.
It is, and it is honestly pretty depressing.
Triton solves most of the performance issues of Python for accelerators but also introduces one (several on fact) more DSL, one more tooling ecosystem and solves none of the (long list of) issues related to Python/Numpy programming model.
Julia and the Python JITs from GPU vendors will.
Mojo already lost the moment AMD, NVIDIA and Intel decided to fully support Python and Julia.
Additionally all of the parallel programming improvements in ISO C++ are coming from them as well, Modular did not have much moat when being a follower and not a driver.