In the country where I live there are two university degrees: Computer Science (depends on Mathematics) and Information Engineering (depends on Engineering). I took the latter, where there is more maths (despite not depending from the Maths department), physics, electronic, automation. I now work with healthcare data: a highly regulated field. Can you please explain what is _not_ engineering, given this context?
Eventually yes, perhaps. But first heat gets trapped in Earth's atmosphere, because pollution and greenhouse gases make it hard for it to dissipate into space. It's called global warming, and no - it's not a hoax.
Since the author is referring to a specific model, I think it makes sense to ignore how the model (or local models in general) may improve over time.
It's like buying a car: I drive that car and get attuned to its characteristics; I don't think how that car (or similar cars) may improve. That's my tool and I want to make the most of it.
It is true that switching a local models it technically very cheap, but there's a considerable time investment in squeezing the most out of it, which may not work on a newer version of that model.
Hopefully, EU-based Yann LeCunn's AMI Labs will develop foundational world models at some point. As I see it, the main problem in EU is not lack of talent: it's lack of investments. Mistral itself recently secured 4B, which is 50 times less than what it could have made in the US.
If I were Dario Amodei, I would start relocating Anthropic to the EU, where there's a huge interest in supporting domestic AI. Also, EU politics are so fragmented that a suspension like this one would be very hard to be agreed.
The article essentially says that, for a junior to be hired, they should demonstrate the same experience as a senior: deploy real system that solve real problems, know how systems behave in production, etc. That is precisely the skillset that someone builds up in a professional environment, i.e. after being hired.
In my view and experience (20+ years in the field) the value of junior colleagues is not in what they already know how to do, but in the freshness of their ideas, and the ability to learn the skills required to bring those ideas to fruition.
So, I agree that the hiring pipeline is broken, but for a different reason: companies stopped looking at juniors as a long-term investment.
I can think of a few reasons for that. In any case, that mindset is to blame, not the "kids" and their education.
The readme says "This app deliberately does not support breath retention, rapid breathing, or any pattern not grounded in the slow-breathing clinical literature." Also links to relevant literature.
In the mid 90s, one of the main use cases advertised for the Web was sharing recipes. I didn't know anyone who primarily searched for recipes online, clearly those ads were targeted at a different demographic group.
Possibly. And possibly the fact that breaking experience for iOS users would result in a massive backlash, while the volume of non-iOS/non-Android users is negligible in comparison. Some of them will convert to mainstream OSes, the rest will succumb.
I started reading this article with keen interest, expecting some deep fix involving arcane model weights. Instead it was "Never talk about goblins", justified by Codex being "quite nerdy". Bottom line: even OpenAI have to raise their hands when facing the complexity of LLMs.