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The next chapter of the Microsoft–OpenAI partnership

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Re: The next chapter of the Microsoft–OpenAI partnership

#171

> Once AGI is declared by OpenAI, that declaration will now be verified by an independent expert panel. > Microsoft’s IP rights for both models and products are extended through 2032 and now includes models post-AGI, with appropriate safety guardrails. Does anyone really think we are close to AGI? I mean honestly?

Most people didn't think we were anywhere close to LLM's five years ago. The capabilities we have now were expected to be a decades away, depending on who you talked to. [EDIT: sorry, I should have said 10 years ago... recent years get too compressed in my head and stuff from 2020 still feels like it was 2 years ago!] So I think a lot of people now don't see what the path is to AGI, but also realize they hadn't seen…

Also possible we get something "close enough" to AGI and it's really fucking useful.

AGI is the end-game. There's a lot of room between current LLMs and AGI.

Re: The next chapter of the Microsoft–OpenAI partnership

#172

Earlier quoted context omitted.

There are a lot of humans that can’t drive a car (well). Part of the problem with “AGI” is everyone has their own often totally arbitrary yard sticks.

The "G" part of AGI implies it should be able to hit all the arbitrary yard sticks

Humans are the benchmarks for AGI and yet a lot of people are outright dumb:

> Said one park ranger, “There is considerable overlap between the intelligence of the smartest bears and the dumbest tourists.”

[1] https://www.schneier.com/blog/archives/2006/08/security_is_a...

Re: The next chapter of the Microsoft–OpenAI partnership

#173

Earlier quoted context omitted.

Jesus, we've gone from Eliza and Bayes Spam Filters to being able to hold an "intelligent" conversation with a bot that can write code like: "make me a sandwich" => "ok, making sandwich.py, adding test, keeping track of a todo list, validating tests, etc..." We might not _quite_ be at the era of "I'm sorry I can't let you do that Dave...", but on the spectrum, and from the perspective of a lay-person, we're waaaaay c…

I think "we" have accidentally cracked language from a computational perspective. The embedding of knowledge is incidental and we're far away from anything that "Generally Intelligent", let alone Advanced in that. LLMs do tend to make documented knowledge very searchable which is nice. But if you use these models everyday to do work of some kind that becomes pretty obvious that they aren't nearly as intelligent as th…

They're about as smart as a person who's kind of decent at every field. If you're a pro, it's pretty clear when it's BSing. But if you're not, the answers are often close enough.

And just like humans, they can be very confidently wrong. When any person tells us something, we assume there's some degree of imperfection in their statements. If a nurse at a hospital tells you the doctor's office is 3 doors down on the right, most people will still look at the first and second doors to make sure those are wrong, then look at the nameplate on the third door to verify that it's right. If the doctor's name is Smith but the door says Stein, most people will pause and consider that maybe the nurse made a mistake. We might also consider that she's right, but the nameplate is wrong for whatever reason. So we verify that info by asking someone else, or going in and asking the doctor themselves.

As a programmer, I'll ask other devs for some guidance on topics. Some people can be absolute geniuses but still dispense completely wrong advice from time to time. But oftentimes they'll lead me generally in the right way, but I still need to use my own head to analyze whether it's correct and implement the final solution myself.

The way AI dispenses its advice is quite human. The big problem is it's harder to validate much of its info, and that's because we're using it alone in a room and not comparing it against anyone else's info.

Re: The next chapter of the Microsoft–OpenAI partnership

#174

> Once AGI is declared by OpenAI, that declaration will now be verified by an independent expert panel. > Microsoft’s IP rights for both models and products are extended through 2032 and now includes models post-AGI, with appropriate safety guardrails. Does anyone really think we are close to AGI? I mean honestly?

Yes. As a proxy, you can look at storage. The human brain is estimated at 3.2Pb of storage. The cost of disk space drops by half every 2-3 years. As of this writing, the cost is about $10 / Tb [0]. If we assume about 3 halvings, by 2030 that cost will be around $2.50 / Tb, which means that to purchase a computer roughly the storage size of a human brain, it will cost just under $6k. The $6k price point means that (hi…

Moore's law also started coming to an end a few years ago.

Re: The next chapter of the Microsoft–OpenAI partnership

#175
post #148

Earlier quoted context omitted.

Most people didn't think we were anywhere close to LLM's five years ago. The capabilities we have now were expected to be a decades away, depending on who you talked to. [EDIT: sorry, I should have said 10 years ago... recent years get too compressed in my head and stuff from 2020 still feels like it was 2 years ago!] So I think a lot of people now don't see what the path is to AGI, but also realize they hadn't seen…

> Most people didn't think we were anywhere close to LLM's five years ago. That's very ambiguous. "Most people" don't know most things. If we're talking about people that have been working in the industry though, my understanding is that the concept of our modern day LLMs aren't magical at all. In fact, the idea has been around for quite a while. The breakthroughs in processing power and networking (data) were the ho…

I worked in Microsoft's AI platform from 2018-2022. people were very aware of LLMs & AI in general. it's not magical

AGI is a silly concept

Re: The next chapter of the Microsoft–OpenAI partnership

#177

Earlier quoted context omitted.

Love that we have reached AGI, but OpenAI's LLM can't even drive a car...

There are a lot of humans that can’t drive a car (well). Part of the problem with “AGI” is everyone has their own often totally arbitrary yard sticks.

The vast majority of humans can be taught to drive.

Re: The next chapter of the Microsoft–OpenAI partnership

#178

> Once AGI is declared by OpenAI, that declaration will now be verified by an independent expert panel. > Microsoft’s IP rights for both models and products are extended through 2032 and now includes models post-AGI, with appropriate safety guardrails. Does anyone really think we are close to AGI? I mean honestly?

They’ll devalue the term into something that makes it so. The common conception of it however, no I don’t believe we are anywhere close to it. It’s no different than how they moved the goalpost on the definition of AI at the start of this boom cycle

> they moved the goalpost on the definition of AI at the start of this boom cycle

Who is this "they" you speak of?

It's true the definition has changed, but not in the direction you seem to think.

Before this boom cycle the standard for "AI" was the Turing test. There is no doubt we have comprehensively passed that now.

Re: The next chapter of the Microsoft–OpenAI partnership

#179

Earlier quoted context omitted.

Plenty of businesses fail to find a way to make a profit

OP said necessary, not sufficient

OP said "will". That doesn't sound like "necessary, not sufficient" to me.

Re: The next chapter of the Microsoft–OpenAI partnership

#180

> Once AGI is declared by OpenAI, that declaration will now be verified by an independent expert panel. > Microsoft’s IP rights for both models and products are extended through 2032 and now includes models post-AGI, with appropriate safety guardrails. Does anyone really think we are close to AGI? I mean honestly?

LLM derived AGI is possible but LLM by itself is not the answer. The problem I see right now is that because there’s so much money at stake, we’ve effectively spread out core talent across many organizations. It used to be Google and maybe Meta. We need a critical mass of talent (think Manhattan Project). It doesn't help that the Chinese pulled a lot of talent back home because a big chunk of early successes and innovations came from those people that we, the US, alienated.
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