AI Algorithms
topic on 8 shows · 13 statements across 13 episodes
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13 statements about AI Algorithms, every show
Hoffman: Google achieved 40% data center energy savings using AI
“Google applied its algorithms to its own data centers, which are some of the best tuned grid systems in the world. 40% energy savings.”
Morgan: B Capital Uses an AI Algorithm to Quantitatively Rate Founding Teams
“So we have an AI algorithm to actually rate the founding teams. And it's based on their experience, their education you know, were they successful or not? How close to what they've studied? Are they working?”
Riparbelli: AI algorithms will achieve 10x to 100x efficiency gains
“Someone will come up with an algorithm that can, that is like 10, a hundred times as efficient as what it is today.”
Teo: AI will not overtake physicians for the imaginable future
“I don't think physicians can be overtaken so easily. Not at all, for the imaginable future.”
Dubois: Humanity remains far from AGI and self-replicating robot threats
“The more Skynet type of scenario where it's kind of self replicating, where it starts to kind of think for itself. I don't see that happening. And I mean, I'm an AI expert. I live in this world every day. While the, while these AI algorithms are very convincin…”
Mulchandani: Hardware commoditization will make running AI models cheap at scale
“The availability of, you know, hardware commoditization and other pieces will get to a point where we'll be able to run all kinds of interesting algorithms At scale with really cheap, readily available hardware, right?”
Andreessen: AI will program human neurochemistry with hyper-optimized media
“You could imagine AI algorithms for creating screenplays and songs that basically are essentially programming human neurochemical biology. And then the dystopian version of this is in the optimal possible state, right? So like basically the AI gets so good at …”
Silicon Valley must embrace European-style democratic oversight for AI models
“You know, the Valley probably needs to be a bit more open to the European approach. The reality is that, you know, we have to figure out as a society which bodies we trust to make decisions which influence recommendation algorithms or AI algorithms, right? And…”
Tamiste: Computer vision requires narrow niches because general vision AI does not exist
“You can only do it in a specific niche. And in computer vision, we're doing it in the CCTV camera angle because you can at least not yet make an AI algorithm that can, you know, look at everything.”
Mays: Diverse product teams are essential for robust AI algorithms
“The value of having diversity, particularly in product teams, because you have people who've come up in different educational backgrounds, different philosophical backgrounds, different religious backgrounds. They've experienced different pressures through the…”
Novartis spent years just cleaning healthcare data before running AI algorithms
“We've had to spend most of the time just cleaning the data sets before you can even run the algorithm. That's just taken us years just to clean the data sets. And I think people underestimate how little clean data there is out there and how hard it is”
Stoica: Many published AI research algorithms are hard to reproduce
“Many of the algorithms which are published are hard to reproduce.”
Dixon: AI winners will be determined by data, not algorithms
“Is who kind of wins in AI, and I think that will probably come down to who has the best data, because the algorithms are, you know, all published and out there, and the frameworks are out there, and so it's not really, that's not really gonna be a differentiat…”