Central Europe here myself (Switzerland to be precise) signal and telegram are the dominant IM and Instagram is just as dead as Facebook, sure some might use it but nobody expects anyone else to to.
> What's left for humans to do? Live on UBI, explore this wonderful world, colonize other planets..
If AI is so good then why would feeble humans travel to other planets? AI will use robots to discover them which don't need food, sleep, etc.
Humans on UBI will have a basic existence. UBI does not mean everyone will live in luxury, since luxury housing, locations are limited, so you'll get some simple aparment, simple food and bus tickets.
Evrything else will be luxury which those can get who can still be valuable in the system due to some unique skill.
> Software Engineering as science will be largely dedicated to AI development
Which will require fewer people.
Simple software engineers who work on CRUDs and are not PhD-s and stuff will go away. Most of software is like this. The few percent who work on kernels, AI models, etc. will still have work. The rest won't, or rather much less people will be needed to simply use AI to do that work.
Yep. The CRUD-ish part of CS is gonna end up like the typewriter pools from the '60s. Claude code is already way better than most subcontractors I've worked with, and without any weird interpersonal or contractual issues usually associated with whatever sketchy agreements their employers have with my employers.
I can see the ground crumbling in a linear fashion, moving straight towards my direction. In a sense, I've already made peace with that. I know what my skill ceiling is.
I'm decent enough to work on an ecommerce, customer portal or whatever. I'm also fully aware I'm never going to be able to write a kernel module, improve some low level loop in a database runtime in C, or do some sophisticated data analytics or fluid simulation modeling.
My time as developer is nigh. I won't really miss it one bit, to be honest.
Honestly I've been thinking about moving into hospitality, tourism or any other field where AI as zero chance of being able to make a serious dent. At least until robots will be able to give an interactive guided of a museum or a national park.
Sometimes I feel the same but then I sit in a refinement meeting and have to handhold the stakeholders through the process of finding out what they actually want, what they don't want, which trade offs they find acceptable and which they don't. And while AI is infinitely patient, my feeling is that being good at this is a super individual people skill and I know that more often than not the people I am talking to are kind of happy they are talking to a person instead of a machine. However when it comes to actually implementing the stuff, AI reliance is now necessary with the timelines given.
But right now AI assisted development isn't really making you more productive by an order of magnitude. It's easily a game of whack-a-mole right now. I estimate that an excellent programmer equipped with Claude Code only sees a 30-40% improvement in speed right now
What you speak of may happen, but I doubt it will happen in the next 10 years.
Sure that's a theory that sometimes plays out, but similarly one also sees almost exponential growth or improvement, yet followed by a plateau for a long time until the next breakthrough.
Software engineering has been getting more efficient for decades and over that time there’s been a massive increase in the number of software engineers.
The Mythical Man-Month describes teams of ten engineers operating before the Internet. Today (pre-LLMs) that’s probably 1-2 people.
Depends how much you are using it - for a casual user the $20 tier gives you just about enough use for hobby projects etc.
Or if you are doing full time development then you just need to pony up for the 20x tier if you want to use it.
Running Codex locally removes so much friction and is so fast compared to either running it on the web (where it has to build environments online etc which consumes time) or compared to copy-pasting chatgpt that it's just a no-brainer.
I don't know about Chatgpt but I used Kimi (they have a Chinese-only plugin that does desktop control - works fine if you enable it even if you don't know Chinese). Observing how it works, it's mostly using the accessibility features of the user interfaces - it fetches a sort of DOM for the desktop applications. Only rarely it has to take a screenshot.
Yeah, maybe like 10:1 bot to human traffic. I'm just a rando blogger so I have principally machine readers - which is not a thing I mind. But I do use Cloudflare everywhere and I could just as well have PEBKACked a setting somewhere to block the traffic. Amusingly, I used to have like 100x the readers in the 2000s posting just as inane takes. I've been left behind by the refinement of the craft!
Are open weights models secure? E.g. if a Chinese model is run by an American provider then can it still do bad things, like inserting backdoors into generated code or accessing external URLs (if browsing is enabled) to send info to them?
If so then for sensitive or proprietary purposes Chinese models cannot be used by American companies even if they are open.
Nothing, but the article is about American AI, so using Chinese models by American companies can be risky. And it's risky for the Chinese to use American models.
So every country or block needs to run their own models to avoid opening a security hole for other countries.
And to provide "correct" answers to questions like "island of Taiwan belongs to which country". It seems that there is not single agreed point of view on national borders.
A model absolutely could be trained to engage in malicious behavior like that, but it seems impractical for an actual attack. What you want as an attacker is to insert a backdoor exactly where you want it an not where you don't because every backdoor increases your chance of getting caught. A malicious model inserts backdoors and exfiltrates data everywhere and you care about maybe 0.01% of it. The other 99.99% is negative value to you. In practice this malicious model would be caught almost instantly.
A hosted model is different because you could prompt inject specific customers, but I assume from this question you mean a malicious open source model being hosted by an honest provider.
I think we'll pretty quickly see a best practice emerging that any generated code will be subject to an additional pass scanning for vulnerabilities. The scan will be done by a different model than the one that created the code. That will help catch vulnerabilities created by models, whether intentional or not.
This should be done regardless of which model was used - American or otherwise.
I would say you should assume your models are constantly being attacked by various forms of prompt injection. By that token (puns) if you treat all models as adversarial you’d probably taking a very sane approach. That said - evidence of this sort of thing should be easy to find and report on. The fact we haven’t seen it leads me to believe it is not there.
But those links are Googled after the model started to answer, they are not the links to the training data
Imagine an artificial “librarian” that read all the books and spits hallucinated quotes for you
But doesn’t let you enter the library, open a single book or even see the sources for those hallucinated quotes
But instead Googles some sources based on hallucinations after generating them ;-)
It’s better than nothing but you can Google them, too, while training data (the library) is completely hidden from you, even the public domain parts of it - zero attribution
There should be at least some correlation. When building the model they give more weight to some pages (e.g. Wikipedia) which have bigger trust (pagerank?). And when they provide links in answers, those matches are listed first which have better pagerank for the query.
So if it sources something in Wikipedia, it is more likely to provide Wikipedia as a trusted source for it.
The problem is when an answer is hallucinated, false, it may provide a source for it which contains the invalid info.
In the US: 25–34 years: Around 25.7% to 25.9% (the largest single demographic group).
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