Daniel retweeted
FC Augsburg believes it's quite terrible to have 17 other Bundesliga clubs sitting on a bunch of the league's limited supply of points.
Daniel retweeted
Apparently this is where the AI era started 😅
If I had beaten that bot in 2017, maybe the world would be a very different place now
I had a chance to stop AI, but …
Daniel retweeted
『球体タイヤ: 全ての方向に移動できるタイヤ』
コンセプトや試作機(デモ)の動画は見かけるが実用化は如何に…。
youtu.be/Tr83-rCwG4k
#BallTire #SphericalWheel #SphereTire #omnidirectional #concept #design #mobility #futuretech
Daniel retweeted
In 2016 I set out to solve Brood War with self-play RL from scratch. Today I believe that this quest has been completed youtube.com/watch?v=Lfo4C0xz… (by a 300M params model).
On July 25, we hacked OpenAI.
Two bugs let us take over ChatGPT/Codex accounts of OpenAI employees (+some unaffiliated users) and reach connected services: Outlook, Slack, GitHub, etc.
We proved it with a PR in OpenAI’s internal codebase . It took us <72h. 🧵
Daniel retweeted
This result is amazing, but not for the reasons people think.
It has very little to do with puzzle solving since it's a linear game and you just have to strictly follow any of the detailed walkthroughs.
The impressive parts are efficient 3D navigation, spatial reasoning, combining instructions from multiple sources, micro adjustments after failed attempts and not getting stuck. The cherry on top is the relatively low cost (167$).
Daniel retweeted
Fukushima's video (1986) shows a CNN that recognises handwritten digits [3], three years before LeCun's video (1989).
CNN timeline taken from [5]:
★ 1969: Kunihiko Fukushima published rectified linear units or ReLUs [1] which are now extensively used in CNNs.
★ 1979: Fukushima published the basic CNN architecture with convolution layers and downsampling layers [2]. He called it neocognitron. It was trained by unsupervised learning rules. Compute was 100 times more expensive than in 1989, and a billion times more expensive than today.
★ 1986: Fukushima's video on recognising hand-written digits [3].
★ 1988: Wei Zhang et al had the first "modern" 2-dimensional CNN trained by backpropagation, and also applied it to character recognition [4]. Compute was about 10 million times more expensive than today.
★ 1989-: later work by others [5].
REFERENCES (more in [5])
[1] K. Fukushima (1969). Visual feature extraction by a multilayered network of analog threshold elements. IEEE Transactions on Systems Science and Cybernetics. 5 (4): 322-333. This work introduced rectified linear units or ReLUs, now widely used in CNNs and other neural nets.
[2] K. Fukushima (1979). Neural network model for a mechanism of pattern recognition unaffected by shift in position—Neocognitron. Trans. IECE, vol. J62-A, no. 10, pp. 658-665, 1979. The first deep convolutional neural network architecture, with alternating convolutional layers and downsampling layers. In Japanese. English version: 1980.
[3] Movie produced by K. Fukushima, S. Miyake and T. Ito (NHK Science and Technical Research Laboratories), in 1986. YouTube: youtube.com/watch?v=oVYCjL54…
[4] W. Zhang, J. Tanida, K. Itoh, Y. Ichioka. Shift-invariant pattern recognition neural network and its optical architecture. Proc. Annual Conference of the Japan Society of Applied Physics, 1988. First "modern" backpropagation-trained 2-dimensional CNN, applied to character recognition.
[5] J. Schmidhuber (AI Blog, 2025). Who invented convolutional neural networks? xitter.cf/SchmidhuberAI/status/1…
guys you do know you can just disable thinking, and instead give it a "deep_think" tool, and it will call it with internal CoT reasoning format right?
gl fixing that
Daniel retweeted
Oyarzabal: "Estáis en una onda un poco negativa, no sé muy bien el motivo" elmundo.es/deportes/futbol/m…
Daniel retweeted
Back in the day, there were so many cell phone options, it was rare to see someone with the same one as you.
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A day in Manhattan, warped so that distance ≈ drive time. Drive times swell in the morning and evening rush hour, then contract in the night.
Daniel retweeted
After AlphaGo, the skill of human Go players noticeably improved. I suspect we will see a similar pattern in math.
Daniel retweeted
Codex grew programmatic policies with no neural nets: max score on Breakout, and SOTA-level scores on MuJoCo.
Maybe heuristics were not too weak. Maybe they were just too expensive to maintain. Maybe it's the next paradigm.
trinkle23897.github.io/learn…




































