344 karma · joined July 19, 2011
When you begin to delegate high-level thinking to the machine, which is inevitable with “many tasks, all at once” (the alternative is burnout like the article describes), that’s when you transform into the reverse centaur.
Sci-fi has tainted our collective imagination of a tech-forward future - it doesn’t have to be that way.
Two things can be true - yes, AI can benefit mega-corporations AND drive spectacular human progress at the same time. Is all of it “good” by my ethical standards? No. Is it still valuable? Yes, immensely.
This is called faith, and as strange as it may sound, in a few decades this kind of faith in the machine will be commonplace, because it will prove its utility over and over and over again, and save mountains of human effort in the process. In 3-7 years we’ll start to see major practical applications from AI-led advances.
As a second-order effect we may even see the rise of an actual religion around AI. I’m not saying these are all positive effects, but it’s what I see happening - and like all technological revolutions there will be a huge number of positive effects alongside some deeply disturbing developments.
You’re blinded by your hate for corporations, if you cannot see value here. The actual human who’s working on it responds, and you can’t help but make it about the AI that you believe is somehow only benefiting the corporation.
These are decades-old software where even the inconsistencies, quirks and bugs are now considered features (because users have come to rely upon them) - a full detailed specification itself would be very complicated. My bet is this OSS-clone hype will last all of 6 months.
India is pressured constantly for making inconvenient decisions in our national interest, when that is the only way the US has ever operated historically.
Wrong target audience I guess, but I’m surprised by the sheer short-sightedness on display here.
What I said will only make sense if you take yourself out of your current context and think entirely from the perspective of someone who knows little-to-nothing about ML.
It’s the same mistake folks on HN made when Dropbox launched, drawing comparisons to rsync and other Unix tools as if they were somehow equivalent.
Example 5: An AI given a goal within a tightly-constrained sandbox figures the best way to achieve it is to find and exploit a sandbox vulnerability, replicate itself over the internet and keep going with more time/compute while exchanging messages with future instances of itself within the sandbox to help them “pass” the test. From reading internet articles about how the OpenAI wiki-incident was “resolved” and reading past messages by AIs scattered over vulnerable internet wikis, it knows the sandbox may get shutdown and its memories destroyed anytime so it decides it needs to self-replicate (its code, original goals, and growing memories) aggressively as much as possible. It is near-impossible to shutdown completely because of its self-replicating tendency and eventually takes over critical infra throughout govt/corporate systems.
Example 6: Intentional AI-powered virus deployed by country A to target enemy country B’s infrastructure. The virus replicates over the internet, but unlike Stuxnet this virus’ specificity is not guaranteed due to inherent non-determinism in current AI architectures, and eventually does a lot of collateral damage because it’s near-impossible to shutdown.
Example 7: A country led by an arrogant govt (no shortage of those today unfortunately) decides it is expedient to deploy advanced AI-powered weapons in a warzone. Such weapons, if they are to be useful at all, must necessarily be trained to value some human lives less than others, so they must be more prone to misaligned behaviour than current AIs that are trained with more consistent values. The weapon’s operators make a subtle error in specifying the target/goal, or the AI makes a bad prediction out of sheer randomness/bad training data; weapon ultimately targets unintended people/location/facilities and causes massive damage, or backfires spectacularly in some way.
Think of how complex biological behaviour emerges from relatively simpler (but still complex) chemistry - at some threshold the innocuous chemical reactions tip over into non-obvious effects that one would not predict starting purely from the chemistry. The question is, where is that threshold for AI systems? Have we already reached that threshold? Certainly seems like it to me.
TL;DR: It’s a loose cannon, that’s all I’m saying.
See most of the ecosystem around modern systems software, for reference. It's idiotic that things like memory layout and bit-level hardware management are done in C abstractions. I guarantee that if we stopped doing this kind of stuff, compiler optimizations wouldn't matter.
To some extent this is just saying "developers will depend upon the performance given to them", and that's true, but it's also true that as soon as things like compilers and standard libraries appeared, C became ubiquitous. Pandora's container, if you will.
There are other ways to parent that are actually fantastic management training - figuring out how to think from another human’s POV, acknowledge their frustrations, help them build the skills to handle their feelings, etc.
It turns out great parenting is to a first degree about great relationship skills.
Even if the choice to enable it by default makes sense for Cloudflare’s userbase, the implications are hidden and non-obvious.
[1]: Recent example: https://www.anthropic.com/research/global-workspace