If it's not worth publishing, it's not a result at all. That being said, the problem really is that since LLMs excel at sifting through piles or papers, publishing more would aggravate the problem instead of alleviating it.
Perhaps that's good, though. The market for truly minimal phones seems to be rather small. I've had a chance to buy a new Commodore phone and they are really cool, but in the end I decided against it because I wasn't even sure my banking apps were going to run on it and I do need some social media on my phone even if I don't use them often. For example, everybody uses Whatsapp where I live. If you need to buy another phone to complement your minimal phone, it's kind of pointless.
That's why I prefer my Wisephone 2. You can still use slack, whatsapp, teams, banking apps, spotify, google maps, etc. But there is no browser, email, youtube, tiktok, etc., either.
The UK left and wasn't even able to make proper deals for exiting the EU, their own Brexit caught them by surprise and it was total chaos for a long time. They could now try to get closer integration with the EU but there doesn't seem to be much will for it in the UK.
Governments don't necessarily have the connection between your ID and what you do online, though, and some governments are known to massively buy publicly available data from data brokers to circumvent existing laws. By "some governments" I mean the US government, by the way. That's not a conspiracy either, it's well-documented.
The technology was first released into the public 4 years ago. Now it's proving major theorems in research mathematics. It doesn't take a genius to realize that this might indicate an extinction-level shift over the next few hundred years.
Academic work is based on worldwide sharing, the sharing is not the problem, it's the lack of attribution. Unsurprisingly, these companies neglect standards of academic honor and attribution. Some human researchers also used to do that but in a discipline like mathematics this used to be a small problem because people tend to be so specialized that very few people could just grab someone's research and quickly piggyback on it, and if they do, colleagues will generally understand what happened. Unfortunately, AI is changing this.
You are both using a different definition of sharing I believe. When people have an expectation of privacy, use by others should be forbidden. Tech has gone completely off the rails with the use of private data.
I have the setting turned on in Gemini Pro even though I work on proprietary code because 1. the setting allows for some (very limited) "memory", and 2. I consider my source code almost public even when it's not open source because I don't work on programs that involve extremely high level of know how or proprietary algorithms. It's mostly CRUD that can be copied in a myriad of ways, whether people use my methods or other methods.
If Gemini can improve based on my code and sessions (maybe doubtful but who knows) and others can benefit from it, that would be a welcome side-effect.
It seems completely trivial to feed sessions to their own LLM and ask it to look for various things in them, from detecting problematic use cases to finding interesting mathematical work.
let's say that they ask a single question for each session they get. they are immediately doubling the compute they need in processing and then post-processing the same session twice.
nothing trivial about it. not saying they cannot feed "their own LLM" saying it isn't trivial especially at scale.
if you do not trust me try it without the "at scale" part.
It's trivial and a solved issue for the companies developing frontier AI models. Obviously, you don't even need AI for searching every prompt every user has ever written to find interesting topics, but you can create automated summaries and use AI on them if you want. There is no "scaling issue" here for companies who are used to processing almost everything that has ever been written anyway.
I didn't want to insinuate that it's trivial for small companies or individuals to do big data mining at that scale, sorry if I made that impression.
I don't trust your judgment, it's in my opinion even hilarious given that we're talking about companies worth almost a trillion dollar (4 trillion in the case of Google). Be that as it may, it was nice chatting with you!
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