I'm inclined to agree with you, but you could make the same argument for exploiting natural resources and the environment. I don't think it's being done right at the moment, and it does not seem to be benefiting people as much as certain companies.
To be honest, living in Switzerland and speaking with peers, we're just exhausted by the constant AI hype. For a lot of us, the fact that Europe isn't frantically trying to scrape the entire internet and every book in existence for the next massive model isn't a bad thing. The big players are doing their thing, like with the nuclear arms race. We regulate a lot, too much a lot of the time, but sometimes that trickles down to other places too. A lot was done right, imo.
ETH Zurich and EPFL universities recently put out an open model called Apertus (was on the HN front page a few months back), it's not a frontier model, but they built it properly regarding copyright and data transparency.
It might look a bit slow or old-fashioned, but focusing on doing things ethically and legally feels like a much better path than just joining the race to scrape everything.
> We need open weights companies now more than ever.
If you're objective it to democratize AI, sure. But for those fed up with it and the devastating effects it's having on students, for example, can opt to actively avoid paying for products with AI (I say this as someone who uses it every day, guilty). At some point large companies will see that they're bleeding money for something that most people don't seem to want, and cancel those $100k/mo deals. I've already experienced one AI-developer-turned company crash and burn.
Personally, I don't think this LLM-based AI generation will have any significant positive impacts. Time, energy (CO2) and money would have been far better spent elsewhere.
Being a moderately frequent user of Opus and having spoken to people who use it actively at work for automation, it's a really expensive model to run, I've heard it burn through a company's weekend's credit allocation before Saturday morning, I think using almost an order of magnitude more tokens is a valid consumer concern!
I have yet to hear anyone say "Opus is really good value for money, a real good economic choice for us". It seems that we're trying to retrofit every possible task with SOTA AI that is still severely lacking in solid reasoning, reliability/dependability, so we throw more money at the problem (cough Opus) in the hopes that it will surpass that barrier of trust.
You could make the same argument for any language. It still requires you to think and implement the solution yourself, just at a certain level of abstraction.
Perhaps I was a little harsh, this was a few years back when I was evaluating Elixir for a client, but ended up going back to a TS/Node.js stack instead. While the Phoenix documentation is stellar, I found it difficult to find good resources on best practices. I was probably doing something stupid and ran into internal and difficult to understand exceptions being raised on the Erlang side, from Cowboy if I recall. In another case, I was trying to validate API JSON input, the advice I got was to use Ecto (which I never really groked) or pattern match and fail. In JS, libraries like Zod and Valibot are a dream to work with.
The result was a lot of frustration, having been thoroughly impressed by Elixir and Phoenix in the past, knowing that I already knew how to achieve the same goal with Node.js with less code and would be able to justify the choice to a client. It didn't quite feel "there" to pick up and deploy, whereas SvelteKit with tRPC felt very enabling at the time and was easily picked up by others. Perhaps I need another project to try it out again and convince me otherwise. Funnily enough, a year later I replaced a problematic Node.js sever with Phoenix + Nerves running on a RPi Zero (ARM), flawless cross-compilation and deployment.
No, they aren't. You have to use BigInt, which will throw an error if you try to serialise it to JSON or combine it with ordinary numbers. If you happen to need to deserialise a 64-bit integer from JSON, which I sadly had to do, you need a custom parser to construct the BigInt from a raw string directly.
This stands to reason. If you need to bridge different languages together like in your case, they need to speak a common tongue. REST/GrahQL/gRPC solve this problem in different ways. There is no technical limitation keeping you from serving HTTP traffic from Erlang/Elixir, but from my own experience it isn't a pleasant experience. JavaScript or Python are dead simple, until you realise that 64-bit integers are not a thing in JS, and need to be handled as strings. Similarly, tuples will give you hell in Python.
On the other hand, if you don't need to cross that boundary, the BEAM will very happily talk to itself and let you send messages between processes without having to even think about serialisation or whether you're even on the same machine. After all, everything is just data with no pointers or cyclic references. That's more that can be said for most other languages, and while Python's pickle is pretty close, you can probably even share Erlang's equivalent of file descriptors across servers (haven't tried, correct me if I'm wrong), which is pretty insane when you think about it.
> I have found the real value of Erlang to be internally between trusted nodes of my own physical infrastructure as a high-level distributed "brain" or control plane
I think this is pretty high praise, considering it's about as old as C and was originally designed for real-time telephone switches.
The public key is generally not considered a secret and is therefore "less guarded". Anybody with access to the public key is able to encrypt and create legitimate looking files that are indistinguishable from the original files. You can still only decrypt them using the private key, but you can no longer trust the contents of the file as your own.
A solution would be to encrypt with the public key, and then _also_ sign with the private key. When reading, you work in reverse order. You verify the signature using the public key, and then decrypt the file using the private key.
But then if you're just using both, why not use fast and robust symmetric encryption instead? Not only will decryption be garbage if the file has been tampered with, but you can also create a signature to detect it (HMAC).