In my view, intelligence includes an ability to learn and adapt to never-before-seen situations. And then general intelligence is an ability to apply that across a wide variety of domains.
Machines can certainly recognize patterns and achieve goals through brute force trial and error. They can also use the results of previous iterations to change their behavior in future iterations, which we could call learning. I wouldn’t necessarily say they are good at brand new situations, but there has definitely been progress.
However, last I checked, a seemingly very intelligent LLM still struggles to play Chess at a basic level, let alone drive a robot or other non-language tasks. Its architecture and ability to learn seem a long way off from being general.
Vision models, being able to encompass language and much more, seem to me like a theoretically closer step to AGI. Yet, there is a lot more to the world than just what we can see.
On the other hand, in humans, vision certainly is not necessary for intelligence. So there is something more fundamental, neither vision nor language, that high levels of intelligence are based upon. Once we figure that out, I think we will be able to build AGI.
> In my view, intelligence includes an ability to learn and adapt to never-before-seen situations.
This is exactly what ARC AGI tests
> And then general intelligence is an ability to apply that across a wide variety of domains.
My experience with Fable is that it can certainly apply that in a wide variety of domains
> However, last I checked, a seemingly very intelligent LLM still struggles to play Chess at a basic level
People also struggle to play Chess at a basic level. They only succeed by studying the game for a long time. I will concede that humans can do this and LLMs generally cannot.
While you are mostly accurate in your definition, I’d argue we have discovered that intelligence is emergent/empirical not analytical. There is not a substrate we have yet to discern. Intelligence does not have to approach humanity to be AGI.
Unfortunately, they don’t have to be very successful to have an impact. Even just their introduction to the marketplace normalizes the concept, just a bit. Google Glass failed and so have other camera-equipped glasses, but notice that they keep popping up. Look how many companies have made them, and for how many years. Collectively, it’s moved the needle. I know someone who uses them regularly, mostly for recording rollercoaster rides, but that’s still plenty for a surveillance company.
Facial recognition is becoming common enough that it’s no longer very surprising if you’re in a crowded public space. Malls argue they need it to catch thieves, airports argue they need it to catch terrorists, and so on and so forth.
Privacy is like Humpty Dumpty, except he’s being poked to death.
Shout out to AVA for running all tests async by default, which not only finds order-dependent issues, but also race condition and other timing related issues.
Amazon built their own in-house logistics network because UPS et al. weren’t cutting it. They offer one-hour delivery for a lot of basic items where I am and it’s not even a particularly urban area. I think in urban centers those same items have 15 minute delivery. They are also the only ones who will consistently deliver on Sunday, when your local store might not even be open.
There are still lots of good reasons to shop local, but I’m not sure speed is the best reason.
In my experience, Etsy and Amazon are both following the same trajectory. Lower quality, lower value, fake and imitation products becoming more common, etc. On Etsy, it used to be the norm that a product would be unique, interesting, and probably handmade. Now, there’s a decent amount of 3D/screen printed junk that might also have some AI slop thrown in for good measure. The corporations have also moved in, just like they did with Airbnb.
The most common issue for me is what happened when I bought a custom dog bowl, thinking the ceramic was made by the seller. Later stumbled upon something similar and realized it was just an off the shelf bowl and the dog’s name had been painted on. That not worth nothing, and it was still probably nicer than what I could’ve gotten on Amazon, and maybe I should’ve asked before buying. But there’s just a lot of that, “make a quick buck” type of stuff and it’s not always obvious.
Most chat support people were contractors hired from third party companies that were given dossiers about their products that were often quite out of date because poor management has always been a thing.
Last time Coinbase had a breach I wrote in to support chat to see what I needed to do. They said there was no breach. I sent them a link to their own blogpost about it. They responded with "wow this is the fist time I'm hearing about this."
> At minimum, a half-way decent support person would ask a few people internally or search Slack before answering.
Of course not. The extremely vast majority of support staff aren't connected to "internal people" and certainly don't have any access to the main company's Slack.
Most of all, those people are paid very little on very tight length-per-interaction targets. They can't spend any time at all looking for stuff outside the docs package or chatting with peeps outside the immediate costaff.
Its an organic cycle, as the company grows big the number of relevant areas grow too and inter team communication becomes way too costly/impractical. The big company becomes a group of informal small companies, each running in their own direction and at times competing with each other. Areas like customer support are not really good candidate for career growth so they get least resources and manpower.
Everything I said applies to overseas labor, too. I’ve worked at both types of companies, those that co-locate support with the product teams, and those that pay bottom dollar and don’t care at all about support.
With the latter type, there’s still almost always a line of communication to corporate. And the support staff still try to help. They are decent human beings, even if the end result kind of sucks.
The cookie banner is a significant accessibility problem, for blind and low vision users, among others. I would like to see a stronger push to attack it from that angle.
Mistral and ElevenLabs seem to be doing pretty well.
Also, here in the U.S., we’ve managed to screw up so badly on data privacy and basic rights that the EU has been systematically replacing their entire tech stack with sovereign components.
I understand the appeal, but let’s be honest. Costco is designed for rich people who think they are frugal. You drive your big SUV there to load up on months worth of food and goods, which you can only do because you have a big house with enough storage for all of it. And who cares if some of it goes bad because you can always go back for more and hey it was so cheap anyway. You even pay a membership for the privilege.
I think average familiy could do better at financing so that they can affort to plan for 1 month or more on groceries. For me, it's not about rich, it's about planning, I must know exactly what I need before I go there. It save time and but stability, I have at least 1 month buffer on common goods shortage.
I’m not sure you have to be that rich to pay the $300 per year membership to buy food at loss leading prices. The bulk sizing of everything at Costco is overblown anyways. I wish it was bigger
I know it's not your point, but the idea that SUVs have more cargo space is a myth. They are large cars with really thick hulls but they do not compete with station wagons, minivans, etc when it comes to cargo space
We don't know from which perspective they're speaking. They might live in a dense European city in an apartment without a car and without parking, and with a supermarket 10 minute's walk away.
It’s safe to default to America. Anyways, an SUV is not a sign of wealth in a crowded city. It’s typically the opposite - they can’t afford a car for the city, so they use the one they already have. If you really want to use that idea, you’d default to trucks. 90% are $100,000 pavement princesses.
Music producer here. High resolution audio is useful for editing and anywhere there might be downstream processing or format conversion that may or may not be high quality, let alone lossless. The article covers that pretty well.
However, the article claims that the final distribution doesn’t need to have a bit depth of more than 16. That does not match my experience. I can tell the difference between my renders that are 16 bit vs 24 bit. I cannot tell the difference between 44.1 kHz and higher sample rates, and that’s consistent with the math (Nyquist-Shannon), but bit depth is a different matter. Would be fun to participate in a double-blind test that includes my own tracks and others.
What? You still operate your ADCs without active cooling?
I'm writing in jest, but long time ago, -hp- used actively cooled FETs (not a very popular approach today as that caused problems with condensation and we have better FETs now).
Machines can certainly recognize patterns and achieve goals through brute force trial and error. They can also use the results of previous iterations to change their behavior in future iterations, which we could call learning. I wouldn’t necessarily say they are good at brand new situations, but there has definitely been progress.
However, last I checked, a seemingly very intelligent LLM still struggles to play Chess at a basic level, let alone drive a robot or other non-language tasks. Its architecture and ability to learn seem a long way off from being general.
Vision models, being able to encompass language and much more, seem to me like a theoretically closer step to AGI. Yet, there is a lot more to the world than just what we can see.
On the other hand, in humans, vision certainly is not necessary for intelligence. So there is something more fundamental, neither vision nor language, that high levels of intelligence are based upon. Once we figure that out, I think we will be able to build AGI.
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