Jürgen Schmidhuber ✓
@SchmidhuberAI · Switzerland, KSA · joined 20 Aug 2019
OG of: P and T in ChatGPT, 100x deeper learning, meta learning and RSI, neural distillation, GAN/World Model... Co-authored most-cited AI paper of 20th century
217 501Followers
0Following
374Posts total
3.7MViews on collected posts
Son gönderiler
Yeni gönderiler aranıyor…
I agree. @Nature tolerates plagiarism. Aside from the Jason Arday case: Geoffrey Hinton never retracted or corrected his Nature papers that republished/misattributed fundamental techniques invented by others whom he failed to cite. Well-known report on this:
50.1K views · 195 likes
· 9 reposts · 5 replies
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This "recurrent depth" is essentially what's in Sec. 5.3 of the 2015 paper: On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models https://t.co/0sqotWZqxp. This paper went beyond the
253K views · 955 likes
· 69 reposts · 28 replies
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Wait until each agent in the collective tries to maximise money in a reinforcement learning (RL) "Economy Of Minds" (EOM)! From the 2023 paper on "Mindstorms in Natural Language-Based Societies of Mind" (NLSOMs, https://t.co/Z3vGwoRLLv):
... A central aspect of our NLSOMs is
17.8K views · 139 likes
· 10 reposts · 13 replies
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2026 update: 1st backprop-CNN for vision (Wei Zhang et al, 1988) https://t.co/1pQriY6LTt
8.5K views · 33 likes
· 4 reposts · 1 replies
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The first modern backprop-trained CNN for vision was published in 1988 in Japan by Wei Zhang (a Chinese researcher), J. Tanida, K. Itoh, Y. Ichioka. Wei brought it to Silicon Valley, earning 1998 FDA PMA approval for radiology’s 1st AI, reading 10M+ mammograms/yr in the US. https
64K views · 226 likes
· 18 reposts · 13 replies
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14:26
2026 update: Canada adopted the old motto "AI For All" or "AI∀" of our AI company NNAISENSE, founded in 2014 😀 See Prime Minister @MarkJCarney's post: https://t.co/gjhxrNSsEH
66.2K views · 117 likes
· 4 reposts · 5 replies
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We just launched Canada’s new AI Strategy: AI For All.
We’re taking control of our future — with AI that’s governed by Canadian values, AI that’s accountable to Canadians, and AI that serves all Canadians.
1.3M views · 3.4K likes
· 383 reposts · 3.1K replies
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@SchmidhuberAI It’s ironic that Schmidhuber credits Fukushima with inventing CNNs while overlooking several other deep-learning researchers—such as Galushkin—whose work dates back to the 1960s.
https://t.co/kmFWbQ9Uhi
23.6K views · 65 likes
· 3 reposts · 3 replies
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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: https://t
742K views · 3.3K likes
· 513 reposts · 72 replies
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4:22
Can someone explain how certain folks are called “godfathers” of deep learning when this guy who was professor at MIPT published the book describing neural networks trained with backpropagation back in … 1974.
In fact modern edition of his book is available on Amazon. https://t.
90.8K views · 568 likes
· 95 reposts · 12 replies
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Yann LeCun’s 1989 convolutional neural network demo, the foundation for the CNNs we still use today.
It's amazing how far we've come since then! https://t.co/rblFlu2CHa
750.4K views · 4.3K likes
· 446 reposts · 99 replies
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1:00
@SchmidhuberAI Schmidhuber predicted deepseek in the 80s
3.8K views · 34 likes
· 1 reposts · 2 replies
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It has been said that AI is the new oil, the new electricity, and the new internet. And the once nimble and highly profitable software companies (MSFT, GOOG, ...) became like utilities, investing in nuclear energy, among other things, to run AI data centres. Open Source and the h
291.2K views · 1.5K likes
· 329 reposts · 114 replies
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Kunihiko Fukushima was awarded the 2021 Bower Award for his enormous contributions to deep learning, particularly his highly influential convolutional neural network architecture. My laudation of Kunihiko at the 2021 award ceremony is on YouTube: https://t.co/bYl3QpbR9N https://t
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Aynı büyüklükteki hesaplara karşı
Son 90 güne ait 5 gönderi, 100K–1M takipçi aralığıyla yan yana. geniş kitleye gösteriliyor, ama izleyenlerin azı tepki veriyor.
Medyan görüntülenme50 109bu hesap5 983100K–1M için medyan
Erişim, %23.04%bu hesap1.49%100K–1M için medyan
Etkileşim, %0.43%bu hesap0.93%100K–1M için medyan
| Ölçüt | Bu hesap | 100K–1M için medyan | Oran |
|---|---|---|---|
| Gönderi başına medyan görüntülenme | 50 109 | 5 983 | 8.38× |
| Erişim (görüntülenme ÷ takipçi) | 23.04% | 1.49% | 15.5× |
| Etkileşim oranı | 0.43% | 0.93% | 0.46× |
Bu aralıktaki diğer hesaplar → Başka bir hesapla karşılaştır → Bu kıyas değerleri nasıl kuruluyor →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
291.2K29 Jan
3.8K
750.4K28 Nov
90.8K29 Nov
742K2 Dec
23.6K
28.6K
1.3M4 Jun
66.2K5 Jun
64K13 Aug
8.5K15 Aug
17.8K2 Sep
253K
50.1K3 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.69%29 Jan
0.96%
0.64%28 Nov
0.74%29 Nov
0.52%2 Dec
0.30%
0.47%
0.60%4 Jun
0.19%5 Jun
0.41%13 Aug
0.45%15 Aug
0.92%2 Sep
0.43%
0.42%3 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.
What the audience does
Likes61.3%14 951 in total
Reposts7.8%1 892 in total
Replies14.1%3 440 in total
Quotes4.5%1 099 in total
Bookmarks12.3%2 991 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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