Yes I was the exact same. I got curious during the GPT-3 release and went over to AI Dungeon. It was just running GPT-2. Hmm wow interesting. This felt new! Then I subscribed so I could use GPT-3 powered AI Dungeon. My jaw dropped. I was talking to that model for weeks. There was a whole human universe in there. You never knew what you could get it to spit out. There were glimmers that this could be huge. It was wild and untamed and practically useless, but there was a behemoth under that prompt.
I was sure this would eventually turn into something. I naturally wanted to converse with it as a chatbot, though it could only stay on task for a few turns. RL and guardrails would come later but it was clearly the foundational step towards AGI for me. From something I thought I would never see in my lifetime to very real and in front of me.
ChatGPT didn't even really rock my world, everything since that moment has been another baby step. But when you take a look back from 2026 models to 2020 it's astounding how far and how fast we've come.
World in this context means that these videos are interactive, just like a video game. In the linked examples you can see the keyboard and mouse inputs. The model is trained to maintain about a minute of scene consistency so you can look around and objects out of view will reappear when you look back in that direction.
I think this is interesting because it collides my intuition from the pre-adtech world with the post. Surely collecting telemetry on nearly every mile you drive could never be a sensible use of time or money, right? What kind of insanity is that? But then of course I know that every click on every website is recorded for all time and that data must be many thousands of times less valuable.
Worked in enterprise for most of my career, uniformly the business side asks for every single piece of data possible to be collected and kept in case they need it.
They basically never need 95% of it and most of it is never looked at again.
That 5% that does gets used ends up been collapsed to a single 100,000ft view somewhere that the decision makers in the company can see it and immediately treat as gospel.
Which is fun when you are the new hire, get asked to look at that dashboard and it turns out it's not calculating the totals correctly at all.
Then you have all the people in that business who collate reports for more senior report readers who never look at them but still collate them and those more senior report readers never pass it up anyway.
Enterprise is a serious weird kafakaesque place at times, it helps to just ignore the weirdness since you can't change it.
Does if it’s a private held company or contributes to profitability in either case.
Doesn’t matter to me in the slightest, a company can have all the inefficiency it can afford as long as I get paid and treat reasonably well it is not my concern how they allocate resources.
Also it's increasingly a liability for potential ransom. The less sensitive data you keep, the lower your exposure to ransom demands, even if your systems have vulnerabilities (hint: they all do).
>Surely collecting telemetry on nearly every mile you drive could never be a sensible use of time or money, right? What kind of insanity is that?
They're not collecting in depth telemetry on every mile you drive, as you drive it. They're literally just every couple of days sending the number on the odometer up to their server. Most carmakers do it simply so they can sell you oil changes
This information is much more valuable to insurance companies than selling you some oil change (which hardly anyone gets from the manufacturer anyways).
Service is a way more lucrative line of business for dealers and manufacturers than you imagine. They may be trying to sell your data to insurance companies but for the most part they can't do that without telling you, and I've never been told that is happening, but I surely get an email from Jeep every month with the status of my tires and oil life remaining and a big sell pitch on taking it to my local Mopar dealer for service
You would be shocked the number of people who are utterly convinced that all servicing needs to be done at the dealership to maintain warranties, and how many dealerships will encourage this thinking, or outright try to deny warranty claims when a vehicle was not serviced by them.
> They're not collecting in depth telemetry on every mile you drive, as you drive it.
I mean, yes and no. It is most likely that the majority of carmakers are not collecting detailed telemetry. But we know from data breaches that some cars collect pretty detailed information.
To me this is the singular drive behind AI development. Big shops realized they can collect orders of magnitude more data than they can keep up with, so they started pushing to develop more and more sophisticated algorithms to process it all. Eventually that lead to LLMs that (maybe someday) can ingest it all, process it all, and reason about it all.
Reducing the network latency helps with this exactly. OpenAI can make better timed decisions when to begin responding so it'll feel less like an interruption. I've also seen some research on full duplex voice models that handle interruption more like an organic conversation and low latency will help there as well
“A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.”
Well yes, that is exactly the point! The very purpose of the ARC AGI benchmarks is to find a pure reasoning task that humans are very good at and AI is very bad at. Companies then race each other to get a high score on that benchmark. Sure there’s going to be a lot of “studying for the test” and benchmaxing, but once a benchmark gets close to being saturated, ARC releases a new benchmark with a new task the AI is terrible at. This will rinse and repeat till ARC can find no reasoning task that AI cannot do that a human could. At that point we will effectively have AGI.
I believe the CEO of ARC has said they expect us to get to ARC-AGI-7 before declaring AGI.
The evidence is that humans are able to win these games. AGI is usually defined as the ability to do any intellectual task about as well as a highly competent human could. The point of these ARC benchmarks is to find tasks that humans can do easily and AI cannot, thus driving a new reasoning competency as companies race each other to beat human performance on the benchmark.
> AGI is usually defined as the ability to do any intellectual task about as well as a highly competent human could
I think one major disconnect, is that for most people, AGI is when interacting with an AI is basically in every way like interacting with a human, including in failure modes. And likely, that this human would be the smartest most knowledgeable human you can imagine, like the top expert in all domains, with the utmost charisma and humor, etc.
This is why the "goal post" appears to be always moving, because the non-commoners who are involved with making AGI and what not never want to accept that definition, which to be fair seems too subjective, and instead like to approach AGI like something different, it can solve some problems human's can't, when it doesn't fail, it behaves like an expert human, etc.
Even if an AI could do any intellectual task about as well as a highly competent human could, I believe most people would not consider it AGI, if it lacks the inherent opinion, personality, character, inquiries, failure patterns, of a human.
And I think that goes so far as, a text only model can never meet this bar. If it cannot react in equal time to subtle facial queues, sounds, if answering you and the flow of conversation is slower than it would be with a human, etc. All these are also required for what I consider the commoner accepting AGI as having been achieved.
By that definition, does a human at the other end of a high-latency video call not have AGI because they can't react any faster that the connection's latency would allow them to have? From your POV what's the difference between that and an AI that's just slow?
> does a human at the other end of a high-latency video call not have AGI because they can't react any faster that the connection's latency would allow them to have
Correct. A person who'd mentally operate that slowly would be considered to have some cognitive disability. For example, would likely not be allowed to drive a car.
You could be fooled in thinking it is a human behind a slow connection, but layman would not consider it real AGI in my opinion, since you have to handicap the human, it seems like lowering the bar just to pretend you reached AGI.
You might recognize it's pretty close to AGI, if it has all the other qualities, but it needs to also operate at a similar response time, uptime, and so on.
My point is, everyone that's not trying to build AGI defines it as, same as an idealized smartest human would be in every way. I truly think this is how most people imagine AGI in their head, and until you have that, they'll say it's not AGI, and industry folks will claim the goalpost keeps moving, when in reality they kept setting their own post.
I think step 4 is the agent swarm. Manager model gets the prompt and spins up a swarm of looping subagents, maybe assigns them different approaches or subtasks, then reviews results, refines the context files and redeploys the swarm on a loop till the problem is solved or your credit card is declined.
I think this is clearly the way forward for Apple. The rest is just UX and refinement.
I recently set up a Shortcut on my Apple Watch that lets me bypass Siri and talk directly to ChatGPT. I used a custom pre-prompt in the Shortcut to tailor the length and detail for watch use. I have 2 versions I can launch from my watch face, one that responds with voice and the other that response with text. I find myself using them all the time, it’s so convenient to be able to ask any little thing that’s on my mind. A version of LLM Siri with full access to the phone and application APIs would be like a superpower.
I was sure this would eventually turn into something. I naturally wanted to converse with it as a chatbot, though it could only stay on task for a few turns. RL and guardrails would come later but it was clearly the foundational step towards AGI for me. From something I thought I would never see in my lifetime to very real and in front of me.
ChatGPT didn't even really rock my world, everything since that moment has been another baby step. But when you take a look back from 2026 models to 2020 it's astounding how far and how fast we've come.
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