[masswerk]

Minsky was actually a pioneer in the field, when it came to working with real networks. Compare

[0] “A Neural-Analogue Calculator Based upon a Probability Model of Reinforcement”, Harvard University Psychological Laboratories, Cambridge, MA, January 8, 1952

[1] “Neural Nets and the Brain Model Problem”, Princeton Ph.D dissertation, 1954

In comparison, Frank Rosenblatt's Perceptron at Cornell was only built in 1958. Notably, Minsky's SNARC (1951) was the first learning neural network.

[riku_iki]

> when it came to working with real networks. Compare

my understanding is that that no one knows what that SNARK thing was, he built something on the grant, abandoned it shortly after that, and only many years later he and fanboys started using it as foundation of bold claims about his role in the field.

[masswerk]

Well, his papers are out there to read.

[riku_iki]

Yes, and I read them: https://dspace.mit.edu/bitstream/handle/1721.1/6103/AIM-048....

vague esssay without specifics

[masswerk]

So you may like better,

> “Multiple simultaneous optimizers” search for a (local) maximum value of some function E(λ1, …, λn) of several parameters. Each unit Ui independently “jitters” its parameter λ1, perhaps randomly, by adding a variation δi(t) to a current mean value μi. The changes in the quantities λi and E are correlated, and the result is used to slowly change μi. The filters are to remove DC components. This technique, a form of coherent detection, usually has an advantage over methods dealing separately and sequentially with each parameter.

(In “Steps”)

:-)

[riku_iki]

can you provide link, and what conclusions you derived from this text if your interest is meaningful discussion?

[masswerk]

The link has been already provided above (opus cit), it's directly connected to the very question of gradients, providing a specific implementation (it even comes with a circuit diagram). As you were claiming a lack of detail (but apparently not honoring the provided citation)…

(The earlier you go back in the papers, the more specifics you will find.)