Gregory Esau

Founder of Babylon, the first platform to feature Quantum Fields Intelligence Equosystems

[Jürgen Schmidhuber @SchmidhuberAI]

The #NobelPrizeinPhysics2024 for Hopfield & Hinton rewards plagiarism and incorrect attribution in computer science. It's mostly about Amari's "Hopfield network" and the "Boltzmann Machine."

1. The Lenz-Ising recurrent architecture with neuron-like elements was published in 1925 [L20][I24][I25]. In 1972, Shun-Ichi Amari made it adaptive such that it could learn to associate input patterns with output patterns by changing its connection weights [AMH1]. However, Amari is only briefly cited in the "Scientific Background to the Nobel Prize in Physics 2024." Unfortunately, Amari's net was later called the "Hopfield network." Hopfield republished it 10 years later [AMH2], without citing Amari, not even in later papers.

2. The related Boltzmann Machine paper by Ackley, Hinton, and Sejnowski (1985) [BM] was about learning internal representations in hidden units of neural networks (NNs) [S20]. It didn't cite the first working algorithm for deep learning of internal representations by Ivakhnenko & Lapa (Ukraine, 1965)[DEEP1-2][HIN]. It didn't cite Amari's separate work (1967-68)[GD1-2] on learning internal representations in deep NNs end-to-end through stochastic gradient descent (SGD). Not even the later surveys by the authors [S20][DL3][DLP] nor the "Scientific Background to the Nobel Prize in Physics 2024" mention these origins of deep learning. ([BM] also did not cite relevant prior work by Sherrington & Kirkpatrick [SK75] & Glauber [G63].)

3. The Nobel Committee also lauds Hinton et al.'s 2006 method for layer-wise pretraining of deep NNs (2006) [UN4]. However, this work neither cited the original layer-wise training of deep NNs by Ivakhnenko & Lapa (1965)[DEEP1-2] nor the original work on unsupervised pretraining of deep NNs (1991) [UN0-1][DLP].

4. The "Popular information" says: “At the end of the 1960s, some discouraging theoretical results caused many researchers to suspect that these neural networks would never be of any real use." However, deep learning research was obviously alive and kicking in the 1960s-70s, especially outside of the Anglosphere [DEEP1-2][GD1-3][CNN1][DL1-2][DLP][DLH].

5. Many additional cases of plagiarism and incorrect attribution can be found in the following reference [DLP], which also contains the other references above. One can start with Sec. 3:

[DLP] J. Schmidhuber (2023). How 3 Turing awardees republished key methods and ideas whose creators they failed to credit. Technical Report IDSIA-23-23, Swiss AI Lab IDSIA, 14 Dec 2023. https://t.co/Nz0fjc6kyx

See also the following reference [DLH] for a history of the field:

[DLH] J. Schmidhuber (2022). Annotated History of Modern AI and Deep Learning. Technical Report IDSIA-22-22, IDSIA, Lugano, Switzerland, 2022. Preprint arXiv:2212.11279. https://t.co/Ys0dw5hkF4 (This extends the 2015 award-winning survey https://t.co/7goTtI5Uwv)

[Gregory Esau @VevoRevo]

@PristineEdgexxx Thank you for sharing, @PristineEdgexxx Like your quilting, you are a rich tapestry of life's challenges and making lemonade from the lemons it throws in your path. 🙏

[Gregory Esau @VevoRevo]

I just published The Quantum Reality Show: Las Vegas!! https://t.co/dShxiKoMSz

[Gregory Esau @VevoRevo]

@Grady_Booch @OralB 😂😂😂

[Gregory Esau @VevoRevo]

@tomfgoodwin I share this weird phobia, Tom.

[Gregory Esau @VevoRevo]

Why Ecosystems
Why Quantum Fields Intelligence
I just published Hearts and Minds https://t.co/uRcmIkphfw

[Gregory Esau @VevoRevo]

Heh... exactly
“A widespread opinion is that the only valid measurement of code quality is WTFs per minute [MartinCleanCode]. Maybe it is a good idea for a startup to create a device that will count the WTFs?” https://t.co/Yy6L6XjcAV

[Gregory Esau @VevoRevo]

You Know Who You Are
I just published The Suicide Squad https://t.co/krhbPaZKTn

[Gregory Esau @VevoRevo]

I just published The Quantum Ecosystem Economy https://t.co/lztSK9DOl4

Join the Revolution.

[Gregory Esau @VevoRevo]

@MariThomas88 Google now personifies Evil

[Gregory Esau @VevoRevo]

@expertsdotcomvp Haha! Good one! "Social media management". Yuck, yuck.

[Gregory Esau @VevoRevo]

I don't often (well, never) retweet @elonmusk , but when I do...
The search for gods always ends badly.

[Elon Musk @elonmusk]

Old joke about agnostic technologists building artificial super intelligence to find out if there’s a God.

They finally finish & ask the question.

AI replies: “There is now, mfs!!”

[Elon Musk @elonmusk]

Old joke about agnostic technologists building artificial super intelligence to find out if there’s a God.

They finally finish & ask the question.

AI replies: “There is now, mfs!!”

[Gregory Esau @VevoRevo]

The fun times are just beginning. Institutions designed for when information moved at the speed of a horse are fatally flawed for the digital information age.

[Balaji @balajis]

We're in a new era.
People know banks may abruptly fail.
People know regulators won't warn them beforehand.
So people are seeking safe haven.
Billions exiting via digital wires.
But to where?
Today, big banks and money market funds.
Tomorrow, assets without counterparty risk.

[Gregory Esau @VevoRevo]

Uh-huh

[Gregory Esau @VevoRevo]

Aye

[Gunnar Morling 🌍 @gunnarmorling]

🗣️ "Distributed SQL engines execute queries on several nodes. To ensure the correctness of results, engines reshuffle operator outputs to meet the requirements of parent operators"

Nice into to data shuffling in distributed SQL engines, by @devozerov.

https://t.co/9zHoDEU2uZ

[Gregory Esau @VevoRevo]

Omg, yes.

[Allen Holub. https://linkedIn.com/in/allenholub @allenholub]

I think software orgs are a company in the sense of a company of musicians or a theater or dance company. The process is primarily creative, cooperative, collaborative. There are mechanics, but software is art. Mechanics are a small part of what we do.

[Gregory Esau @VevoRevo]

It's not just skills, it's craft.

[Gregory Esau @VevoRevo]

@johncutlefish Omg yes

[Gregory Esau @VevoRevo]

Indeed

[Bernard J. Baars, PhD @BernardJBaars]

Try to stop your inner speech for ten seconds. I find it impossible to do for more than five seconds or so. It is the simplest possible demonstration, but it shows how DEPENDENT we are on the flow of inner speech, which is one dimension of our working memory.