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Let me tell you a little bit about my second book, and how it relates to my first book. 1/
worldscientific.com/worldsci…
Will Kinney retweeted
A research system I built for @psipbc, using a non-public Anthropic model, has proved the Aaronson-Ambainis conjecture! Open since 2008, this is one of the most fundamental questions in quantum computing. It concerns when quantum computers can have exponential speedups. 1/n
Today Physical Superintelligence PBC is announcing a proof of the Aaronson-Ambainis conjecture, one of the central open problems in quantum complexity, with major implications for quantum computing speedup.
psi.inc/research/aaronson-am…
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If this proof holds, it means that quantum computers are only polynomially faster than classical computers for general problems. Shor's algorithm is an exception, not the rule.
Today Physical Superintelligence PBC is announcing a proof of the Aaronson-Ambainis conjecture, one of the central open problems in quantum complexity, with major implications for quantum computing speedup.
psi.inc/research/aaronson-am…
Thread 👇
For the many people in the replies: yes, this is being caused by the magnetic field driving the Lavet stepping motor, not the quartz oscillator.
en.wikipedia.org/wiki/Lavet-…
Yeah I love being on committees with guys like this.
Gone for three days, and Faye is already bigger and stronger and more of a hazard to herself and others. 🤎
Will Kinney retweeted
If any science-philanthropist is willing to support the Indian National Strings Meeting 2026, please drop me a message.
Incidentally, this year we will felicitate Ashoke Senon his 70th birthday.
This is good advice.
Replying to @JosephPConlon
Right now the old rules are broken and no one knows the new ones.
This is precisely the best time to do a PhD — the chance to overtake all the old folk and make big lasting contributions.
It is messy right now — aim straight at the mess. 6/9
😮
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…




















