Unicorns are getting minted earlier: - The median new unicorn is just over 4 years old, a 37% decline in age since 2023 - The median unicorn overall is 15 years old Charts of the Week:

Unicoin Sues Uniswap Just Weeks Before its Token Launch Unicoin has sued Uniswap Labs (@Uniswap) in New York, escalating a dispute over the UNICOIN name. The company says its mark does not infringe Uniswap’s UNI, UNISWAP, or UNICHAIN trademarks. The dispute began after Uniswap sent three demand letters since June. Those letters demanded that Unicoin stop using UNI related marks and transfer its domains. Unicoin now wants the court to cancel Uniswap’s UNI trademark registration. The lawsuit comes just weeks before Unicoin’s planned UNCN public launch.

Unconventional AI CEO @NaveenGRao explains the GPU energy problem: 99.9% of energy goes into moving data rather than computing, and non-von Neumann architectures could eliminate that bottleneck "Every computer that's been built in the last 80 years or so works on the principle of having an explicit state store we call memory. We pull data out of that memory, and we do something to it and write it back. That works great and it's a generalized machine, but the problem is almost all the energy in a computing system goes into moving data around." "99.9% of the energy's about data movement. It's not about the computation. The way these machines work, their explicit operation requires movement of data always" "There are ways to build computers, actually looking at how nature's built computation, where data sits more still. It doesn't have to move around between memory to computing elements." "We can have memory and computing in a single element. This is what we call a non-von Neumann architecture. Using the time varying physics of those elements to actually do computation for AI." @unconvAI

Unconventional AI CEO @NaveenGRao explains why modern computing may be missing a fundamental dimension of intelligence: time "When you're a researcher and you're starting this in 2005, you're gonna reach for something that exists. You can't build something new. We've always known that brains operate in different ways. It doesn't work on these same principles." "The neuromorphic community has been trying to go after some ideas like this. I think in an overly ideological way. It doesn't have to look like a brain to me." "There are some principles of the physical world that we do have to adhere to, and that is that literally every, the physics of every known thing in the universe has time. Yet our computing abstractions do not. That's actually a weird thing if you think about it. So why don't we use time?" "Mathematical operations don't have a sense of time. Multiply, divide, add, subtract, they're all timeless." "The real problem we're trying to solve is intelligence. Intelligence in the natural world has always used the time dimension. Maybe we go back to that." @unconvAI

Unconventional AI CEO @NaveenGRao says Moore's Law let computers ignore energy efficiency, but AI scaling has made that impossible: "We've never really cared about energy efficiency in a computing system. Moore's Law was kind of working and we didn't really need things to be efficient, we just needed them to be fast." "Now we're in this new place where we do need them to be efficient. We're running out of energy at the global level in several years. If we don't think about efficiency, we can't keep scaling." "The kind of almost basic thing we've seen out of computers is they achieve more things when we scale. If we wanna keep building bigger models, better models, and more of it used in the world, we have to solve this problem. It's not gonna be something that we're just gonna keep generating more and more energy." "There are thermal limits to certain form factors. If you wanna build a robot, you're just not gonna do it with an orbital data center." @unconvAI

Unconventional AI CEO @NaveenGRao explains why AI needs a different kind of computer to scale from data centers to billions of robots: "In the short term, and call that like five years, we're kind of in an energy crunch. We're already there from a regional perspective when you build data centers." "The pace of AI uptake is so fast and it's exponential, and the pace of supply is pretty linear. We really need some way to close that gap, and we believe we can do this with technology." "Long term, we want AI everywhere for robotics. I imagine a world where we'll have billions of robots kind of dynamically assembling to solve hard problems, and we need a different kind of paradigm than having to connect back to a data center for all the compute." @unconvAI