You can also use a mutex that doesn't own data in Rust if you need to.

Sight correction, at least in my understanding (physics major but only undergrad) this explicitly isn't communication.

It's not possible to use entanglement to transmit information faster than light, even though the entanglement itself could be simultaneous.

It's been brought up elsewhere in the thread but GCP deleting an entire tenant's account rules them out entirely from any serious business IMO.

The Gemini team that completely fucked up recent deploy by blocking queries originating from Google Cloud Functions is a masterpiece as well.

Full downtime for 2 days, no apologizes, no answers, had to pay 3% extra for support, no credits.

Special award to the dude representing Google trolling on Twitter that they will do another "wild Friday release".

Shitty.

Super cool to see you here.

I've also looked at ray for running data pipelines before (at much much smaller scales) for the reasons you suggest (unstructured data, mixed CPU/GPU compute).

One thing I've wanted is an incremental computation framework (i.e., salsa [1]) built on ray so that I can write jobs that transparently reuse intermediate results from an object store if their dependents haven't changed.

Do you know if anyone has thought of building something like this?

[1] https://github.com/salsa-rs/salsa

I asked the same question to one of the core devs at a recent event and he (1) said that some people in finance have done related things and (2) suggested using the Ray slack to connect with developers and power users who might have helpful advice.

I agree this is a very interesting area to consider Ray for. There are lots of projects/products that provide core components that could be used but there’s no widely used library. It feels like one is overdue.

Other folks have built data processing libraries on top of Ray: Modin and Daft come to mind.

But I'm not aware of anything exactly like what you're referring to!

Personally I think chemistry is going to trail a long way behind biology for a while (in terms of ML solutions). The data, supporting libraries, and funding doesn't seem to be on the same level.

One of the (many) problems with the market is that consumers have imperfect information. In this case specifically it's almost never possible to have an accurate picture of a company's security in advance of a mistake like this one.

I'm sure it's no where near good enough yet, but a legal model getting the answer right 83% of the time is still quite impressive imo.

Syngas can also be converted to other products through gas fermentation.

Seconding this, I'd love to add an interface like this to a RAG setup.