Agreed, Friston's Bona Fides are impressive. (Aside: His fame in neuroscience comes from him having written important FMRI software that everybody cites.)
That's also why I worked with his team and read a lot of his papers for a while.
His principal idea was originally that neurons perform free energy minimisation. This idea makes a lot of sense, once you understand what free energy means. But, to the best of my knowledge, it has not at all been empirically verified for neurons (I'd be delighted to be proven wrong in this belief). So he went the route of generalising the free energy principle: "the free energy principle asserts that any “thing” that attains a nonequilibrium steady state can be construed as performing an elemental sort of Bayesian inference".
Terms
"can be construed"
and "elemental sort of Bayesian inference" do a lot of work here. Updating and generalising one's research hypothesis is legitimate (albeit one could be more explicit about this), but it weakens the claim being made. Anyway, under a charitable interpretation of those terms, I agree that this is
true, but, at the same time doesn't say much. Indeed, under the
charitable interpretation it basically equates doing free energy
minimisation with existence. Friston has lately said that the FEP is
not falsifiable.
Take it from the horse's mouth (i.e. a Verses employee): "the free energy principle just applies to stones, it applies to birds, it applies to any kinds of animals" on Machine Learning Street Talk [1].
Here is my current position: from a mathematical principle this general one cannot derive scalable ML algorithms!
> he seems to have joined only in 2022, they were 4 years old at the time.
The company founders have a cryptocurrency and (later) metaverse background.
Benefit of doubt is a great concept. The other extreme is: extraordinary claims require extraordinary evidence. Why should we restrict ourselves to a binary choice? Can we not think in a more nuanced fashion, in Bayesian terms? In other words look at all available evidence and assign probabilities?
"We are the next DeepMind" is easy to say ... The DeepMind founders had a stellar predigee in computer games, AI and neuroscience, the Verses founders have a cryptocurrency background.
Verses also released [1] last month. What both the Atari and the Mastermind announcements have in common is the lack of details, including
code. Why do they not show their code? How do we know their figures are real? We've just had the OpenAI vs FrontierMath discussion [2, 3]. Presumably, being able to play Pong, a 1972 computer game, is unlikely to be their moat ...
Interesting also their 2024 MLST presentation [4]. Does that inspire confidence? It was that video that made my priors on Friston having had a breakthrough in ML change downwards dramatically ... But do not take my word for it, please make up your own mind.
So I'm not the only who wonders about the hyperbole emanating from Friston et al! Some more morsels:
- The CEO is an "International Bestselling Author" [1].
- The company blog states that Friston has "successfully [decoded] the underlying mechanisms of intelligence as it functions in the brain and biological systems" [2].
But they got $10M investment from G42, an Emirati VC [3]. Note that G42 have also invested in Cerebras and OpenAI [4]. So their PR works.
Geoff Hinton was denied an academic position at the University of Sussex's CS department where he had done postdoc work (That department is now 'famous' for consciousness studies and integrated information theory https://osf.io/preprints/psyarxiv/zsr78. I bet they are kicking themselves now ...)
> "Academia will one day wake up, and realize that"
Charlie Munger famously said, "Show me the incentive and I'll show you the outcome" ...
- https://www.activeinference.institute/
- https://spatialwebfoundation.org/