The Soviets went nuts on money printing in the years before the collapse. https://t.co/ccDFEykUlY ...

The swarm intelligence algorithms have amazing names. They're all named after bees, fireflies, wolves, whales, dragonflies, cuckoos, and the like.It does feel there's something here in terms of getting crypto crowds to cooperate, and getting AI agents on the same page.CITATIONS(1) Particle Swarm Optimization (PSO)Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, 4, 1942–1948. IEEE. https://t.co/fTQ5ZZ1ESo(2) Ant Colony Optimizat ...

Ants are dumb...but ant colonies are smart.More generally, there's the idea of swarm intelligence.Quite a lot of research in this area.Might be applied to crypto and AI agents specifically.And distributed systems more generally. ...

From @antiartificial, five years ago.Indecency (@antiartificial):@BrianRoemmele Oddly enough I recently came upon this graphic annotating the spectrum. https://t.co/gieOIejJ7K ...

Here’s what the sounds meant. https://t.co/1YrOvwR8qeMorning Brew ☕️ (@MorningBrew):AOL says it will discontinue dial-up internet on September 30May this sound echo in eternity:https://t.co/I0zKIPERbX ...

This is in jest.That said, there’s something amazing about a system where every human can get repeatedly replaced over hundreds of years but the organization keeps compounding. Onchain entities and AI agents will take this much further.Original from here:Object Zero (@Object_Zero_):@tc1415 The Aberdeen Harbour Board has been trading since 1136 and predates Magna Carta. https://t.co/DdocJEYxQk ...

Corporations solved immortality. Partially. https://t.co/d0yy3KzI4i ...

RT David Sacks (@DavidSacks)A BEST CASE SCENARIO FOR AI?The Doomer narratives were wrong. Predicated on a “rapid take-off” to AGI, they predicted that the leading AI model would use its intelligence to self-improve, leaving others in the dust, and quickly achieving a godlike superintelligence. Instead, we are seeing the opposite:— the leading models are clustering around similar performance benchmarks;— model companies continue to leapfrog each other with their latest versions (which shouldn’t be possible i ...

You don’t need to use the concepts exactly, but ideas from real-time OS development could be baked in as constraints during AI training and evaluation.Soft real-time may be sufficient. Unless it’s a car crash if it doesn’t work, like hard real-time. https://t.co/OpEnybplIy ...

We could address this via constrained execution.Constrain output length, like the 140 character limit on Twitter.Or constrain the runtime, like real-time mode in Linux. https://t.co/f9nVR7FS7IAndrej Karpathy (@karpathy):I'm noticing that due to (I think?) a lot of benchmarkmaxxing on long horizon tasks, LLMs are becoming a little too agentic by default, a little beyond my average use case.For example in coding, the models now tend to reason for a fairly long time, they have an inclination to ...