Building Flywheel: accountable AI workflows, verification and provenance. Research, tools, and publications. Open to research partnerships and funding.
Revenue, revenue, revenue..
Would you all kindly take your heads out of your ass and recognize that the path forward is not incentive based?
The moment you put money over ethics, and placed material gain on that pedestal you gave up on what we are here for, in order to chase delusion. I will never be able to respect that, and will always see you as my mortal enemy.
"Harming America" is kind of a fallacy. Befause Neoliberalism and corporate incentives are something that existed prior to recent tensions with China. This is not the 40's/50's/60's anymore and the America our parents fought for is not the same one that is trading our social securities on the stock market, and using government funds to handle backroom and under the table deals internationally. At the end of the day, would you prefer corruption, coercion, and authority + globalization, or globalization that has a future where common grounds can be found amongst nations? I don't see or understand how one could remain aligned with the same values as those who came before us. Those days are over, and our leaders are not really public servants in this day and age. Maybe with erasure of qualified immunity, and serious frameworks that intensely penalize and infraction corruption when discovered then yes, we can begin working towards what the constitution was founded on. Which are ideals. And good ideals to found and run a government on. But we need to shift gears a bit with the fractured political and military stalemates of past generations.
Maybe his vision is wider than the simple feudal idealistic rivalries between nations? Maybe the US isn't all seeing, all knowing, and all benevolent. We are shovel fed just as much propaganda as Chinese are, and at the end of the day human beings both here, there, and everywhere have the same needs. Personal attachments to nationalism, and cultural issues are really effecting a lot of people's ability to think critically beyond the existing box we place ourselves in.
Someone I know asked Astra to play Factorio. It wins, but it takes forever and guzzles tokens. If you ask Astra instead to “design a system to win Factorio,” it builds software that runs 1000x faster. Mechanistic software gives you cheap leverage, and LLMs can write mechanistic software on demand.
Congratulations @JulianAssange and @Stella_Assange on the birth of your beautiful baby. Our (my wife and I) son was born yesterday and he is a beautiful light. May our children share a world that continues to fight for the liberties that every human being deserves to experience. The freedom to seek truth, and share knowledge with others in a compassionate way.
@hottaqu I would argue some minds tend to be capable of visualizing memories of the future. It is widely considered pseudoscience, but some mechanisms and what appears to occur in episodes of precognition tend to exhibit this.
The Yang–Mills result has renewed interest in physics, including @chloeallegra228.
One piece of physicists’ intuition that can seem strange is identifying particles with irreducible representations.
I’d put it this way: we discovered particles in experiments.
Concurrently, math gives us irreducible representations of symmetry groups: representations that cannot be split into smaller invariant parts.
We found that irreducible representations of spacetime symmetries happen to describe one-particle states.
So when physicists call such a representation a “particle,” they are using shorthand for the connection between a physical entity and its mathematical description.
Part of work I'm doing on a longer video for Samuel: https://t.co/5sRhxbvAug
The heatmap shows how far the sound is from the reference, as a function of the 2D tongue position. The sound you're hearing is before the gradient descent.
If it halts, all mathematics collapses.
Specifically: if it halts, simulating it is a proof. So it either doesn't halt OR everything we know about mathematics is wrong (=ZFC set theory is inconsistent). But we cannot prove it doesn't halt!
Many of us are working back to some very similar concepts. I am building universe physics simulations and world models, drawing from my experiences in horticulture, neurobiology, developmental and behavioral pathologies, and utilizing the scaling laws of physics, and it's relationships with physical space to train models in a fully realized digital representation of the environment organisms grow and develop in.
This just breaks my brain: How does a brain wire itself, starting from a single cell, using only the information encoded in a genome? We pose this as an engineering problem: Write a program that a single cell executes to build itself into a brain. The program must be small enough to fit in a genome, and fast enough to finish within developmental time. A computer scientist who knows little about biology quickly realizes why the obvious strategies, which developmental biology has rejected experimentally, fail at scale: The genome is too small to store per-synapse wiring, and axons searching blindly for targets would take too long. These same algorithmic constraints drive the design toward solutions that resemble the developmental strategies organisms actually use. That the same solution structure falls out of scaling limits as out of evolution suggests that features of neural development can be grounded in computational necessity rather than contingency alone. Where earlier thought experiments reached discouraging conclusions about the ability of a biologist to fix a radio 1, or to understand a microprocessor 2, the news here is better: The design of the brain may be recoverable, not from taking it apart, but from asking how a genome must specify it in the first place.
- Stan Kerstjens & Anthony M. Zador Cold Spring Harbor Laboratory 14 August 2026
🛸We have proposed and numerically demonstrated a passive, broadband, low-power, and magnet-free non-reciprocal photonic device on a silicon platform utilizing the mechanical Kerr effect.
In 2020, we will celebrate that many of the basic ideas behind the Deep Learning Revolution were published three decades ago within fewer than 12 months in our "Annus Mirabilis" 1990-1991: https://t.co/rph9OP76m9
Thank you for sharing new ideas for elegantly combing the concepts of visualization, mathematics, physics, light, and sound. I love the concepts, and they provide ideas for more concepts to learn. visualization and perceptibility is a gap today that is becoming quickly easy to fill. It provides a lot of reassurance considering that our learning, and the learning and cognition workflows of today will help those who come after us. :)