But what happens when search gets so optimized for delivering ads through AI, that your AI starts giving you crappy ad-driven results (which is already happening).
We'll need a way to hook up the agent to a subscriber search service.
How did Hacker News become the place where you announce a hack and all the comments are like "I don't like this because I feel it might be in a legal gray area"?
It didn’t, there are a few (shallow) replies which are downvoted to the bottom of the page. But perhaps when you looked at the page these comments were new and you were just unlucky.
The discussion about IP with these reverse engineered products in itself is interesting, although a bit repetitive with new clones every day.
I feel you. We take a risk when we check our work less and we own the consequences. That's not new, and it doesn't make us bad. It's just the human condition from time immemorial. The solution is not obsessively combing through every detail of our work, it's better monitoring and control on the places where mistakes can have an impact.
That's not the conclusion. I started using AI after the Jacobian conjecture counterexample and have used a particular problem to learn how to use AI and to explore it's capabilities. I'm not a great mathematician but I'm full faculty with 25+ years of research experience and lots of articles and I just proved in a few weeks something that had resisted my efforts for some years.
The exploration process is much easier now. Ideas are quickly testable and multiple tests can help identify a technical obstruction. The tool requires good guidance and input but as it trains on people like me it will need those less.
At the very least our way of doing things must change. More pessimistic views seem to me defensible.
GP never said it was the conclusion. He was praising you, after you on your own volition decided to comment here to let know others about your experience with AI.
It seems to me you're a very privileged individual, I'd suggest you practice gratitude regularly in your life.
You sound a bit troubled. I was responding to the leading the way part. I'm hardly doing that. I just jumped on the bandwagon. What I do see is a tool that forces me to change behaviors learned over decades and potentially renders useless many of them while facilitating others. That's not all a rosy picture.
As for privilege, don't assume everyone lives and works in the US or gets paid lots of money to be a professor.
I think upweighting the live components of academia is inevitable in the age of automatically produced writing, but I also find it depressing that people think so little of writing that they imagine it obsolete because of AI.
AI writing is aggressively, aggressively mediocre. It is only good for how cheap it is. If you're indifferent to how much better good human writing is than AI writing, you should not be the one to evaluate human writing.
> the problem may be less about knowing a particular technique and more about the agent’s ability to keep its actual goal as the primary constraint.
I think the limiting factor is often the human's ability to articulate the goal and hold the agent accountable.
The working memory of technical people and the way they communicate often seems to prioritize how they're doing a task and not why they're doing it. So when they talk to you about their problem, they give you the human equivalent of modem noises and stack traces. This is such a common problem on tech support and Q&A forums like StackOverflow that it spawned its own terminology and website: https://xyproblem.info/
The agents don't respond to XY problems any better than a colleague does, and usually much worse.
An effective colleague asks why, and we need a similar relationship between the agent and its human supervisor.
> Makes sense. The kids can see that education isn't really going to be a sellable skill when AI ends up coming into full force.
If true, this is a disastrously foolish thing to believe. Education is only going to become more important as supervising increasingly advanced AI agents becomes more difficult. We need people who understand all different domains of human endeavor at the deepest level possible.
I mean, what's the alternative? AI does everything for me and I play Fortnite all day? Might as well plug yourself into the Matrix.
The situation will probably be like with airline pilots. The plane is mostly an automated system, but we simply don't let automation to work through exceptional situations, without human review. Therefore, lots of pilot training (and their presence) is still required.
But it's also hard to guess what exactly skill should the pilots have. It's clear that lots of things from manual aircraft do not translate well to automated.
Children of the Magenta Line seems very topical, especially wrt AI
>In 1997, American Airlines captain Warren VanderBurgh gave a lecture warning about the dangers of autopilot. He titled it "children of the magenta line," after the magenta coloured course line the flight computer draws across a cockpit display. He noticed that pilots were so used to following that line, to managing the automation rather than actually flying the plane, that they lost their own skills to manually fly the plane. This wasn’t a problem until it was a problem.
>VanderBurgh’s concern was not about autopilot itself but rather the complete dependency on autopilot at the expense of the internal knowledge of how it works and the loss of the judgment to know when to use it. In 2009, his warning came true in the very worst way possible over the Atlantic. When Air France 447’s sensors iced over, the autopilot handed a perfectly good airliner back to its crew, the pilots, confused and out of practice, stalled it into the sea.
Just like kids eventually take over most of the daily tasks for their parents (for people in countries where you don't have any kind of retirement fund and assisted living, etc.). Same will happen here - on one hand because the human population keeps growing older without any replacement and on the other because all the new tech will be too complicated for humans to understand.
It seems unlikely that we'll be able to keep up with AI in any capacity. Your alternative seems like the inevitable outcome of AI succeeding, and it doesn't sound so bad.
Strong resonance with the famous essay "The Rise of Worse is Better" [1], which contrasted the (better) "MIT/Stanford style of design" with the (worse) "New Jersey approach".
MIT/Stanford:
> Simplicity -- the design must be simple, both in implementation and interface. It is more important for the interface to be simple than the implementation.
New Jersey:
> Simplicity -- the design must be simple, both in implementation and interface. It is more important for the implementation to be simple than the interface. Simplicity is the most important consideration in a design.
TFA maps "simplicity" to "MIT/Stanford simplicity" (simplicity for the user) and "smallness" to "New Jersey simplicity" (simplicity for the developer).
I wonder if the root of the tension between the two schools comes down to the ambiguity of the user/developer distinction. Developers are also users. Simplicity of implementation is helpful to developers when they are working directly on implementation, while simplicity of interface is helpful to developers when they are using other developers' work.
I appreciate the New Jersey simplicity as a user (with development skills) too, though. It's usually just a matter of time before I have to dive into the program/library/whatever internals to fix a bug.
Pretty much anything. I mean, even consider a text editor, monospace font, no syntax highlighting. It's already pretty daunting. Doable, certainly, but a big task. We're lucky people already made some, and we can copy their designs even when we choose not to copy their exact code.
From the authors, Charles Simonyi went to Microsoft as one of the original Word implementers, while Excel was born on Mac OS and only later ported to Windows.
I think you're right on that point of contention, it's too far to assert a universal and clear good/bad dynamic here because that line between developer/user is contextual and fuzzy.
Another interesting irony I'll note, Lisp is the "New Jersey approach" towards symbolic AI. Americans clinging to their Lisp systems were deeply entrenched in a "worse-is-better" mindset. Your interface, the computational model, didn't need to be designed for logic programming, that was wholly secondary. Do everything as much as possible in Lisp, and then offload the relational description to a small (not simple) library. American knowledge engineers were looked at as overpaid procedural hackers with zero mathematical elegance and very little credibility. More or less the same perception these self-same Lisp-machine users had for Unix and C programmers.
It's all about perspective, at the end of the day. Where we draw the line in the sand on these categories is free-to-choose, yet it also determines everything. We're always someone else's villain under different semantics.
We'll need a way to hook up the agent to a subscriber search service.
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