> Luckily, it doesn't matter because it's a solution in search of a problem. Most consumers aren't using AI apart from google search.
This is... a view.
Maybe I live in a strange sphere of strange ("normie"-ish) people, but the people around me are for sure using AI. Mostly chatgpt to be fair. They use it to compare products that they intend to buy, identify plants in nature, create travel plans, find interesting places to visit nearby, give movie suggestions based on what they have previously enjoyed and so on and so forth. AI is becoming a very integrated part of their reality. To "google" something and digging through the search results manually is very rapidly being replaced by asking chatgpt, for better or worse.
I think this is the key takeaway for the future of AI. Give tech a few years to catch up and we will likely have the functionally equivalent to today's models running on consumer grade hardware. From there it will explode, where "it" is how we use and interact with computers. AI will be integrated into just about every workflow.
The business case in this future would be to sell the trained models to end users. The investment would be shifted towards the training of models and delivering updates, with revenue coming from model licenses, upgrades and cloud services for tasks that exceed the local capabilities.
> I thought about resurrecting my old game boy advance to introduce my little boy to the tech world.
Hello myopia my old friend.
We will wear glasses to the end.
Because my vision's slowly slipping.
Played Gameboy while I should be sleeping.
And the vision that I once could claim. Doesn't remain.
Now there's just the blur, of distance.
I (software engineer) have lived with a software engineer for 14 years. We (half jokingly, somewhat seriously) refer to non-software engineers as "real persons", or human-humans.
> There seems to be a strong bias where using AI feels like you're making a lot of progress very quickly, but compared to manual coding it often seems to be significantly slower in practice.
This metric highly depends on who uses the AI to do what, where strong emphasis is on "who" and "what".
In my line of work (software developer) the biggest time sinks are meetings where people need to align proposed solutions with the expectations of stakeholders. From that aspect AI won't help much, or at all, so measuring the difference of man hours spent from solution proposal to when it ends up in the test loops with and without AI would yield... very disappointing results.
But for troubleshooting and fixing bugs, or actually implementing solutions once they have been approved? For me, I'm at least 10x'ing myself compared to before I was using AI. Not only in pure time, but also in my ability to reason around observed behaviors and investigating what those observations mean when troubleshooting.
But I also work with people who simply cannot make the AI produce valuable (correct) results. I think if you know exactly what you want and how you want it, AI is a great help. You just tell it to do what you would have done anyway, and it does it quicker than you could. But if you don't know exactly what you want, AI will be outright harmful to your progress.
> And they don’t travel very far, so only nearby microphones would “hear” the tag. That makes the devices inherently private, Deng said, because other people wouldn’t detect any activity unless they were within a meter or so.
It would seem these things don't really produce loud noises, so probably not adding much to the noise pollution that already exists in our environments. At the same time it seems the statement kind of negates the "point" of this tech, that you don't need an active (energy consuming) device close to the source of the events that you want to detect. So not sure of how to interpret it.
I'm starting to notice how those who don't use AI end up having to hand tasks over to people who can get them done quicker.
It is anecdotal for sure, but it's a pattern that seems to be emerging around me that expectations of velocity increases, and those who don't use AI can't keep up.
I'm firmly in the LLM fanbase. Not because I can't type code (was doing it for over 17 years, everywhere from low level hardware drivers in C to web frontend to robot development at home as a hobby - coding is fun!), but because in my profession it allows me to focus more on the abstraction layer where "it matters".
I'm not saying that I'm no longer dealing with code at all though. The way I work is interactively with the LLM and pretty much tell it exactly what to do and how to do it. Sometimes all the way down to "don't copy the reference like that, grab a deep copy of the object instead". Just like with any other type of programming, the only way to achieve valuable and correct results is by knowing exactly what you want and express that exactly and without ambiguity.
But I no longer need to remember most of the syntax for the language I happen to work with at the moment, and can instead spend time thinking about the high level architecture. To make sure each involved component does one thing and one thing well, with its complexities hidden behind clear interfaces.
Engineers who refuse to, or can't, or won't utilize the benefits that LLMs bring will be left behind. It's just the way it is. I'm already seeing it happening.
I do a hybrid, where I keep lowest tier subscriptions but choose to watch content off of our media server setup at the highest available quality, without advertisement.
I don't mind paying for what I consume, but God damn is the value proposition at the floor currently. Here even the rather expensive mid tier subscription gives you 1080p at most with all the big players. It's as if they somehow converged to this model and aren't competing anymore. Coincidence, I'm sure.
A notification on my phone. I don't know what produced it exactly, but it was probably connected to my google account (sigh!) somehow.
It's something that happens rarely enough for me to not having developed an automatic "aw hell nah, no f-ing way" filter towards it anyway, and I (naively) did click the notification and "got hit" by the article.
This drives me nuts. It's been going on for years that a simple "if this, do that" deal is encoded in an overly elaborate 10 minute long YouTube video where at least 9 minutes of it is filler. You know, when you start skimming the comments to see if anyone bothered with summarizing it.
AI amplifies the problem by making it easier to produce filler, but the problem is whatever metrics are behind the monetization. You need users to "engage" with your content for at least x amount of time to earn y amount of money, while instead the earnings should be relative to and directly derived from how useful the content is to how many users.
Exactly we don't, and what's worse is that the "content" is getting to the point where we need _content_ blockers.
I recently got hit by an "article" that promised to tell me which three AAA games would be released with PS Plus soon. A three point bullet list was all I wanted. Instead I got pages after pages of word-manure about nothing at all for reasons I don't even understand. At the end of it I still couldn't tell you which three games the article was supposed to tell me about.
I foresee a bleak feature where we will deploy AI as "content blockers" to extract the useful content from the word-manure that is becoming the preferred way of working among internet "authors".
Yeah. In these cases it's not like anyone is going to spin up their own instance and start competing with you.
Government / handles society-critical things code should really be public unless there are _really_ good reasons for it not to be, where those reasons are never "we're just not very good at what we're doing and we don't want anyone to find out".
Some months back I would have agreed with you without any "but", but it really does help even if it only takes over "typing code".
Once you do understand the problem deep enough to know exactly what to ask for without ambiguity, the AI will produce the code that exactly solves your problem a heck of a lot quicker than you. And the time you don't spend on figuring out language syntax, you can instead spend on tweaking the code on a higher architecture level. Spend time where you, as a human, are better than the AI.
I've recently worked extensively with "prompt coding", and the model we're using is very good at following such instructions early on. However after deep reasoning around problems, it tends to focus more on solving the problem at hand than following established guidelines.
Still haven't found a good way to keep it on course other than "Hey, remember that thing that you're required to do? Still do that please."
I (deep, deep in embedded systems) have seen this too often, that code is incredibly complex and impossible to reason around because it needs to reach into some data structure multiple times from different angles to answer what should be rather simple questions about next step to take.
Fix that structure, and the code simplifies automagically.
I think it boils down to how companies view LLMs and their engineers.
Some companies will do as you say - have (mostly clueless) engineers feed high level "wishes" to (entirely clueless) LLMs, and hope that everyone kind of gets it. And everyone will kind of get it. And everyone will kind of get it wrong.
Other companies will have their engineers explicitly treat the LLMs as collaborators / pair programmers, not independent developers. As an engineer in such a company, YOU are still the author of the code even if you "prompted" it instead of typing it. You can't just "fix this high level thing for me brah" and get away with it, but instead need to continuously interact with the LLM as you define and it implements the detailed wanted behaviors. That forces you to know _exactly_ what you want and ask for _exactly_ what you want without ambiguity, like in any other kind of programming. The difference is that the LLM is a heck of a lot quicker at typing code than you are.
This will be a fun little evolution of botnets - AI agents running (un?)supervised on machines maintained by people who have no idea that they're even there.
This reminds me of the "if you were entirely blind, how would you tell someone that you want something to drink"-gag, where some people start gesturing rather than... just talking.
I bet a not insignificant portion of the population would tell the person to walk.
Spread the risk and reduce the probability of extinction.
We know for a fact that earth is doomed, on top of our own continuous efforts to kill ourselves off. No not recent climate change type of doomed, but the evolution of our sun is continuously pushing the habitable zone outwards. We might be able to deal with that particular annoyance by hiding underground when it becomes an emergency in half a billion years or so, but our utopia won't be as utopic anymore.
Eventually however, the sun will balloon to a red giant at which point we better have a plan in place other than staying on this planet.
This is... a view.
Maybe I live in a strange sphere of strange ("normie"-ish) people, but the people around me are for sure using AI. Mostly chatgpt to be fair. They use it to compare products that they intend to buy, identify plants in nature, create travel plans, find interesting places to visit nearby, give movie suggestions based on what they have previously enjoyed and so on and so forth. AI is becoming a very integrated part of their reality. To "google" something and digging through the search results manually is very rapidly being replaced by asking chatgpt, for better or worse.