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22 results for “ai agents”
Concept17 mentions across episodes
AI agents
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AI agents
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agents
...physical AI agents? These become your your kind of like butler. Right? So in that model, I have the car. Mhmm. I have a model y hardware four, pretty incredible. Not perfect yet, but getting there. Pretty close. Right? I think I would say two out of
57:45 / 58:49
from transcript57:45 – 58:49
“MIT Professor compares proactive AI agents to raising children until age 18”
But AI agents can convert words to actions. But proactive AI is the agents really being autonomous and doing actions on their own, you know, without we having to stimulate them or prompt them and so o
1:11 / 1:29
framework1:11 – 1:29
So everything I've seen, people's intuition seems to fail on robotics. So you have this kind of general optimism. I've seen this on self driving cars. People think it's much easier problem than it is. Similar with drones. Here, I understand it a litt
1:26:59 / 1:28:02
from transcript1:26:59 – 1:28:02
Outside of that, the the default conventional AI weapon would be drones, which is, I don't know. It that makes sense that come or that that countries would compete on that. And, I think that it would be a mistake if The US weren't, trying to do more
11:15 / 12:28
from transcript11:15 – 12:28
billions of interactions, you really are almost allowed to fail never. When you have embodied systems that are put out there in the real world, you you just have to solve so many problems you never thought you'd have to solve when you're just thinkin
3:12:45 / 3:13:49
from transcript3:12:45 – 3:13:49
543210. All engine running. We have a lift off. And one small step for man, one diaphragm. The world's largest airliner, each wing is big enough to hold five tennis courts. This new technology made it possible to meet the user's crucial needs. Enter
0:06 / 1:08
from transcript0:06 – 1:08
is happening throughout each step of the process as it collaborates with a human scientist. I think this concept of fully self driving science, right, like a closed loop where you have AI that iterates on itself and then carries out an experiment the
11:15 / 12:15
from transcript11:15 – 12:15
Well, I wanna get to automation and employment, particularly on the entry level side. But first, I wanna just wanna ask the broader question of there was this idea of AI plus human. I think it was chess could beat AI for some period of time, and that
11:14 / 12:24
from transcript11:14 – 12:24
They don't wonder our navs and so what you have in nav systems is a CarPlay emerges and Android auto emerges, and it's very natural. People are like, oh, I have my phone. I just plug it in, and and it wasn't a big revolution, but the CarPlay and Andr
26:12 / 27:21
from transcript26:12 – 27:21
And somehow, at the domain, a retailer is going to take a burrito or, you know, a pair of sneakers and put them into a self driving car that's gonna come to my ranch out in Hill Country and give me what I want. Yeah? Mhmm. So which piece of the puzzl
57:00 / 58:00
from transcript57:00 – 58:00
...agents fail, and you just call us and we fix it. Yeah. Sounds like an API call, and it's hilarious. There's gonna be teleoperation markets when we get human robots, switches. There's gonna be somebody around the world that's happy to fix the fact tha
4:35:10 / 4:36:18
from transcript4:35:10 – 4:36:18
there is no single right way of doing it. You can decide how to constrain that autonomy. Right? A very I mean, a different example of how you could constrain autonomy is preauthorization use cases. Insurance preauthorization is a very ripe use case f
16:28 / 17:30
from transcript16:28 – 17:30
systems are going to translate directly, to AIs that are much much more versatile, much much more robust. And reasoning is going to impact, is gonna revolutionize not just not just language models, but reasoning is going to impact every single indust
30:52 / 31:51
from transcript30:52 – 31:51
And that someday is probably around the corner. So everything that moves. We already know that your lawnmower is gonna you know, who's gonna be pushing a lawnmower around? That's craziness. Unless you want to. I mean, it's, you know and so so I think
57:43 / 58:53
from transcript57:43 – 58:53
a game of chess with a computer, which is analyzing board positions and and applying a certain kind of intelligence to figure out what its next move should be. That's the subject of our program today, artificial intelligence. The good future of AI is
0:45 / 1:54
from transcript0:45 – 1:54
incremental improvements, like matrix multiplication. Like, it has to sit there for days thinking how to incrementally improve a thing, and that it does so recursively. And as you do more and more improvement, it'll slow down Right. Because there'll
1:08:16 / 1:09:22
from transcript1:08:16 – 1:09:22
But if we want to produce things, something as vital as artificial intelligence and we need energy. And so I'm just delighted to see pro to accelerate AI innovation, to accelerate the growth of energy so that we can sustain this this new industry and
56:58 / 58:02
from transcript56:58 – 58:02
this, you know, all the positive things about AI that we're seeing in, you know, in LLMs and in chat and you take them into the real world. So how do you put intelligence in the cars and trucks and tanks and fighter jets? And, and as roughly as those
3:01 / 4:06
from transcript3:01 – 4:06
that I'm the one who's incorrect? Mhmm. And that's going to as the systems get more and more intelligent, you're gonna have to contend with that. It's like, what what what do you is this a bug or a feature where you just came up with? Yeah. And they'
1:05:37 / 1:07:03
from transcript1:05:37 – 1:07:03
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