Tesla what s written in the numbers

current valuation might imply 30 to 50% market share in the future but let’s look at it like a tech and not a car company

sustainable advantage in batteries? It is claimed by Musk, is it real ?

Tesla is an operating system with around a car, car design turned upside down. Will it translate into a sustaiable advantage vs car producers?

Tesla first at autonomous drive with Autopilot, famously claimed in a keynote where Tusk promised your Tesla could work for you as a Taxi while you don’t use it

Imagine Tesla can pack all these unique features in a skateboard other producers can customize with fancy bodies. The skateboard is the operating system in a android-mobile phones analogy

There is a tech story that holds, but theere is also 3 checks to performs, answer the 3 questions, will Tesla really be able to be consistently ahead of all car makers in the world ? In the end, will it be economies of newtok and winner takeall like in software and social networks? Let’s see

Bayes is lean

an ignorant definition lerts me understand Bayes success in recent times

“Bayes’ core insight of gradually getting closer to the truth by constantly updating in proportion to the weight of the evidence” really lean statistics 🙂

the quote from Tetlock book on Superforecasters, I haven t read it. I neither read Lean startup, I don’t really remeber Bayes Theorem so I might be wrong in putting together things I do not study, but still the quote is suggestive

It come from here https://arbital.com/p/bayes_rule/?l=1zq

I did not know arbital, it is in less wrong territory I guess, I am going to study Bayes there

BTW all orginitase here “What relevance does this have for the LW-Yudkowsky-Bayesian rationalist project?” found in this SSC article about metis vs high rationalism. I think it’s all in the zeitgeist https://slatestarcodex.com/2017/03/16/book-review-seeing-like-a-state/

step back “seeing like a state” recycled as “seeeing like an algorithm” ref TikTok, I think misusued nd rather sinister but here it is Eugene Weiwei https://www.eugenewei.com/blog/2020/9/18/seeing-like-an-algorithm

il giorno delle parole @@@morfiche

“I clarify: that was truth, not humor. The GPT setup is precisely isomorphic to training a (huge) neural net to compress online text to ever-smaller strings, then using the trained net to decompress random bytes.”

isomorphic: mapping between 2 structures that preserver the structure and can be reversed.

” as organisms become more and more complex through evolution, they need to model reality with increasing accuracy to stay fit. At all times, their representation of reality must be homomorphic with reality itself. Or in other words, the true structure of our world must be preserved when converted into your brain’s representation of it.”

from here https://savsidorov.substack.com/p/tldr-the-interface-theory-of-perception

Homomorphism in Algebra is a structure-preserivng map between 2 algebric structures of the same type (not reversible like isomorphic?)

Fad chasing pigs

the story of Soros and Druckenmiller (was it at quantum fund?) taking opposite sides on the dotcom boom

Brain links 16 sep 2020

Joscha Bach on GPT-3 https://www.youtube.com/watch?v=FMfA6i60WDA GPT-3 moves in a semantic space, masters relations between words, but can only deepfake understading

Joshua built the MicroPSI architecture based on PSI Theory https://en.wikipedia.org/wiki/Psi-theory#MicroPsi_architecture

Curious Wavefunction makes a history of information and thermodynamics http://wavefunction.fieldofscience.com/2020/07/brains-computation-and-thermodynamics.html

ends it with the idea that our brain is a mixture of digital and analog processes, as posited by Von Neumann

Sav Sidorov another Joscha Bach video with highlights https://savsidorov.substack.com/p/tldr-joscha-bach-artificial-consciousness

“Some people think that a simulation can’t be conscious, and only a physical system can, but they got it completely backwards. A physical system cannot be conscious, only a simulation could be conscious.”

AI = General methods + power of the computers

like Communism was Eletrification + power of the soviet.

The bitter lesson o fRich Sutton http://www.incompleteideas.net/IncIdeas/BitterLesson.html

Screenshot 2020-09-11 at 11.09.08

from Gwern May newsletter on scaling and metalearning:

“The scaling hypothesis regards the blessings of scale as the secret of AGI: intelligence is ‘just’ simple neural units & learning algorithms applied to diverse experiences at a (currently) unreachable scale.”

This is related somehow, distributed intelligence and fungi from The Curious Wavefunction, Life Distributed http://wavefunction.fieldofscience.com/2020/09/life-distributed.html

Gurren Lagann gnostico

lo realizzo leggendo questo articolo

La tana del bianconiglio: teorie del complotto e gnosticismo

e altre cose interessanti sul carattere gnostico di cultura pop cyber contermporanea, le pilllole rosse di Matrix, Musk e Qanon

oltre al pensatore che ci vede la gnosi in Qann abbiamo

il game developer che ci vede un ARG https://mssv.net/2020/08/02/what-args-can-teach-us-about-qanon/

il FT Alphaville che ci vede una riedizione di bitcoin https://ftalphaville.ft.com/2020/08/24/1598288383000/From-bitcoin-to-QAnon–bits-to-qbits/

https://ftalphaville.ft.com/2020/08/24/1598288383000/From-bitcoin-to-QAnon–bits-to-qbits/

il cacciatore di nazisti che ci vede i Protocolli di Sion https://www.justsecurity.org/72339/qanon-is-a-nazi-cult-rebranded/?fbclid=IwAR0FXrgcxxc4uLcaQaNroEFueqs22kRfqQCFV8tGG5nV0Qc5-_XeuRsvw7Q

Luther Blisset ci riconosce il suo Q? Devo controllare https://www.internazionale.it/reportage/wu-ming-1/2020/09/02/mondo-qanon-prima-parte

Expert Forecasts

IEA-wrong-fcast_panelsBCE-wrong-forecasts

ECB inflation forecasts from 2012 to 2020 mostly wrong in the same direction, in 2020 they changed their direction, maybe they are a reverse benchmark 🙂

IEA sistematically undervalued renewables potential in their yearly forecasts

beware the experts, don’t believe what they say, there’s always room for things to go the way you like best

Scaling hypothesis in AI

start from Gwern here https://www.gwern.net/newsletter/2020/05#gpt-3

parameters scaling in GPT-3 does not run into linear scaling of performance nor dimishing returns. Rather it shows metalearning enhancing the performance

It was forecast by Moraves and since we are in a fat tail phenomenon this holds true: “the scaling hypothesis is so unpopular an idea, and difficult to prove in advance rather than as a fait accompli“. Before GPT-3 another epiphany on the scaling was the google cat moment which started the deep learning craze

Another idea which I like is that models like GPT-3 are definitely cheap and if they show superlinear growth it is a no brainer to go for bigger and more complex models, it is along way before matching the billions of expenses for Cern or nuclear fusion.

Carig Venter synthetic bacteria project cost us 40 milion, ground braking orojects costing so little should not be foregone

BTW to grasp the idea of how there could be a scaling benefit in growing deep learning sizes, go no further that a simple, unfounded but suggestive analogy with Metcalfe law of networks, network value grows with the square of nodes.

from growth to risk

1960 the year singularity was cancelled on SSC. History developed mainly in Malthusian trap, with industrialization we got out of the trap and started growing product percapita in an exponential growth. That stopped in the 60’s

German sociologist Beck sensed that capitalism was getting into its second stage, from growth to risk priority. Adam Tooze on Foreign Policy

see also Parrow with normal accidents

Noah Smith on “What happened in 1971 along the lines of singulraty cancelled in 1960. https://twitter.com/Noahpinion/status/1306264582046937088

Assuming that the secular trend was not negated, we are simply in the through of the secular cycles, how long would be this cycle and how high would the upswing carry us ? Check also Turchin and Kondratiev for longer cycles

Turchin Cliodynamics “Cliodynamics is entirely different. Its roots are in nonlinear dynamical systems. We don’t go out looking for cycles; but we don’t shy away from them when there is robust evidence for them. In Structural-Demographic Theory, in particular, oscillations arise because of nonlinear feedbacks between different interacting components of the social system (state-level society).”

with a nice chart:

fuck wordpress and the blocks editor, BTW, when a platform interface becomes baroque for some dynamics clear only to the programmers it’s probabluy time to move, it used to be easy to add an image, no longer