Insight
Rao: Deterministic digital silicon is ill-suited for stochastic neural networks
“A neural network is actually a stochastic machine, and so why are we using the substrate that is highly precise and deterministic? For something that's actually stochastic and distributed in nature.”
Prediction Not checkable as stated
Rao: Unconventional AI can build analog circuits isomorphic to intelligence
“So we believe we can find the right isomorphism in electrical circuits that can subserve intelligence.”
Prediction Not checkable as stated
Rao: Unconventional AI is building a substrate superior to matrix multiplication
“We are trying to build a better substrate than matrix multiply.”
Insight
Rao: The boundary between hardware and software is an arbitrary choice
“Software and hardware is, is not really a natural boundary. It's just where we decide to draw the line and say, okay, this is something I make configurable or I don't.”
Assertion Not checkable as stated
Rao: Computer architecture has remained fundamentally unchanged for 80 years
“We've been building largely the same kind of computer for 80 years. We went digital back in the 19 forties”
Assertion Not checkable as stated
Rao: Computing is currently constrained by energy at a global level
“We're at a point in time where computing is, is, is bound by energy at the global level, which just was never true in all of humanity.”
Prediction Open · timeframe Dec 2035
Rao: AI will require 400 GW of new power capacity over 10 years
“By some estimates, we need 400 gigawatts additional capacity over the next 10 years. To power the demand for AI.”
Insight
Rao: Dynamic substrates with physical time and causality are required for AGI
“My intuition says that anything where the basis is dynamic, which has time and causality as part of it will be a better basis than something that's not.”
Opinion
Rao: Current AI models are nowhere close to AGI
“I don't think they're anywhere close to AGI because, I mean, they still make stupid errors. They're very useful tools, but they're not what, it's not like working with a person, right?”
Prediction Not checkable as stated
Rao: Unconventional AI aims to build manufacturable analog chips within five years
“A couple of things that we set out to do when we built, we were starting this company was see if we can find a paradigm that's analogous to intelligence within five years. And then at the five year mark, we should be able to build something that's scalable fro…”
Prediction Open · timeframe Dec 2028
Rao: TSMC will partner with Unconventional AI for chip manufacturing
“TSMC is absolutely going to be a partner forward, you know, met with them recently and, you know, we want to work closely with them to make sure we get what we need, get fast turnaround times to prototype and all of that.”
Opinion
Rao rejects AI doomerism, calling AI the next evolution of humanity
“I, I'm the opposite of an AI doomer. I think AI is the next evolution of humanity. I think it takes us to a new level, allows us to collaborate, understand each other and understand the world in much deeper ways.”
Prediction Open · timeframe Dec 2028
Rao: Unconventional AI's first prototype will be the largest analog chip ever
“Like when we build this chip, our first prototype, it's going to be probably one of the larger, maybe the largest analog chip people have ever built, which is kind of weird.”
Disclosure
Rao: Unconventional AI focuses on physics of learning, not traditional chips
“First off, it's not a chip company per se. Most of what we're doing is really kind of looking at first principles of how learning works.”
Insight
Rao: Analog computing is inherently more efficient by leveraging physical substrates
“Analog still is inherently more efficient because you, it's actually analogous computing is the way to think about it. Like, can I build a physical system that is similar to the quantity I'm trying to express or compute over? You're effectively using the physi…”
Insight
Rao: Traditional numeric computing lacks physical time, simulating it instead
“In the real world, every physical process has time. And in the computing world, like the numeric computing world, we actually don't have that concept. You simulate time with numbers.”
Insight
Rao: Transformers succeeded because they maximized GPU hardware efficiency
“Transformers are really they're a big innovation because they made the constructs of the GPU work extremely well.”
Assertion Not checkable as stated
Rao: Over 40 years of academic research proves analog AI compute viability
“There's also 40 plus years of academic research, which is showing a lot of promise here. People have built different devices, albeit not in the latest technology with professional engineering teams, but they have built proofs of concept that actually show some…”
Assertion Partly supported
Rao: Human brains run on 20W, mammalian brains on 0.1W
“Human brains run on 20 watts of energy. That's, that is true. But if you look at mammalian brains generally, actually extremely efficient, like a squirrel or a cat, it's like a 10th of a watt.”
Assertion Supported
Rao: US holds roughly 50% of global data center capacity
“The U S is about 50% of the world's data center capacity.”
Assertion Supported
Rao: Data centers consume 4% of the US energy grid
“And today we put about four percent of the energy grid of the U S energy grid into those data centers.”
Prediction Not checkable as stated
Rao: Unconventional AI will release open-source tools for its analog hardware
“And we will be releasing some open source and things around this to let people play around.”
Assertion Supported
Rao: Early analog computers failed to scale due to manufacturing variability
“Analog computers were actually some of the first computers, and they worked really well. They were very efficient, but they couldn't be scaled up because of manufacturing variability.”
