Oh wow the theoretical implications in neuroscience exite me here - is this a potential model of Fristons Markov Blanket concept
“ Probably the most ambitious and all-encompassing version of the ‘Bayesian turn’ in cognitive science is
the free energy principle (FEP). The FEP is a mathematical framework, developed by Karl Friston and
colleagues (Friston, Kilner, and Harrison 2006; Friston et al. 2010; Friston 2010; Friston et al. 2017a;
Friston 2019), which specifies an objective function that any self-organizing system needs to minimize in
order to ensure adaptive exchanges with its environment. One major appeal of the FEP is that it aims for
(and seems to deliver) an unprecedented integration of the life sciences (including psychology,
neuroscience, and theoretical biology). The difference between the FEP and earlier inferential theories
(e.g., Gregory 1980, Grossberg 1980, Rao and Ballard 1999, Lee and Mumford 2003) is that not only
perceptual processes, but also other cognitive functions such as learning, attention, and action planning
can be subsumed under one single principle: the minimization of free energy through the process of active
inference (Friston 2010; Friston et al. 2017). ”
Isn't the FEP basically just loss minimization over KL-divergence? In other words, it's the same thing we already do with ML and already have been doing for years? I've never understood where this differs to the status quo, or why this isn't just a relabelling of techniques/concepts. Although I didn't look too deeply.
Yeah you are right to basics of the paper and I am extrapolating a bit here:
I think the remarkable result of this paper is that they add a local Lagrange multiplier λ at each layer, which accumulates constraint/prediction error over the inference dynamics.
At equilibrium, in the linear case, those local multipliers converge to exactly the same gradient signal that backpropagation would calculate globally
Now what is Predictive coding: its a network that can minimize prediction errors through local recurrent interactions instead of an explicit global backward pass.
Now I am making the leap to Fristons more philosophical and mathematical work not the paper - so that is me making the allusion
But a light bulb moment for me dawned when I read it
This process (PC-ALM) gives us a concrete example of how globally coherent inference/credit assignment can emerge from purely local dynamical interactions.
PC-ALM lets a recurrent dynamical system relax toward a state in which the backprop gradient is represented locally throughout the network.
That distinction is potentially important for neuroscience.
A brain doesn’t obviously have a central routine saying:
loss.backward()
it certainly has recurrent neural populations whose states continuously influence neighboring populations.
This paper is demonstrating that, at least mathematically, those sorts of local recurrent dynamics can generate the same credit information that backprop obtains through the chain rule. The authors explicitly motivate predictive coding as a biologically plausible local-learning alternative because standard BP requires globally coordinated error variables and update ordering.
Think about it also give plausible evolutionary to chain intelligence through cells coming together and creating nested networks
This has got to be how the neurological intelligence sausage gets made
What it eventually means for ML I’m
Not sure but hopeful it opens a door
Thanks for the run down. I definitely see the appeal in pursuing local error correction mechanisms. I can see this opening doors too, or some extension of this. Certainly feels like the right way forward.
I’m glad there’s a lot of people commenting negatively below to PGs modus operandi (rationalizing maximum greed in seemingly thoughtful measured essays that make him seem like a kindly philosopher instead or digital robber barron)
Like Ayn Rand, and PT Barnum before them VCs and Tech Bros will be looked at with great hostility in next years as having destroyed society with their brand of hyper-capitalism all in the name of “disruption”
I think he specifically speaks against maximum greed here? "create more value than you capture", "have the best product", "Being generous makes you more powerful" etc.
I think its a wolf in sheep's wording - PG is a master of reasonableness to amplfiy greed behind nice sounding words - note he always says “caring about value , caring about market, product etc” but not caring about people their lifestyle or human value or even established ethical companies - everything is a hammer in the nail of disruption
Meanwhile he moves his family to England and Europe to take advantage of small town life, more govt protection less screen time for his kids etc
The VC model is about funding supergrowth potential sustainably for PROFITS not society
Its all about extracting every ounce of profitability in any situation not about caring for employees, customers etc with the expectation that trickle down disruption will benefit society
We’ve had 20 years of this in the us -are we better off?
A part that rubs people wrong is that they have no choice and competition doesnt exist outside the vc ecosystem. VC can subsidize a non profitable model for a decade often with an ipo that isnt profitable for another decade of net zero value creation. It isnt capitalism.
It is a pay to play game where if you are not in the club, you have little chance of playing let alone winning.
The cherry on top is the culture of cheating, lying, stealing, and all kinds of other “disruptive” tactics is actively encouraged and cheered on. This is while claiming to be altruistic too.
The public is growing a strong deep hatred of sv, whose only response seems to be calling everyone poor and laughing. It is sad, because I still think technology is a force for good.
Another bunch of nerds who now have their panties in a bunch because AI threatens their fragile egos and core identity and who they are..
I’m being somewhat harsh here but come on - human endeavors are messy and it’s surprising how much our egos are getting bruised here over seeing the value of these tools
Dont get me wrong Also, there’s no AI Utopia coming this is it guys, were stuck with oligarch Tech Bro funded AI and big funded Govt AI so forget any egalitarian motives- we have to fight for our rights from other humans as always as well but AI as a technology in itself being able to truly solve unsolved intellectual problems is still a boon for society - who cares who gets credit?
You mean a effing cult like heavens gate.. call all this rationalist crap for what it is - a religous movement with leaders and prophets and even a demiurge like God
All this just means that most AI Researchers and Techis are sci-fi geeks and might be getting a bit too invested in that season of Black Mirror, Neal Stephenson, Cyberpunk or whatever else has evil AI in it -which is to say, they are by and large all sci-fi geeks, who are notoriously unreliable about predicting the impact of tech in the future.
Are LLMs really gonna kill us.. via inference runs? I hope I am not being foolish :)
20 years ago tech was gonna 'change the world' for the better. now 'Don't be Evil' is sign of the naiveté of industry
I'm not a doomer. I despise the fear campaign they're pushing for regulatory capture. But the world is still going to be a very unbalanced and dangerous place if they're able to succeed in their goals of hoarding power for themselves above all others.
Nowhere in this essay is it mentioned why its good to start a startup..
Given the 20 years of twisted and evil greedy nature of most successful VC level startups and their founders, tech bros and VCs and the evil of MBA optimized Private Equity should we not instead teach young people to run away from startups and greed?
Paul Graham is selling a drug to society
That drug has infected the world.. we need to review what value all this disruption is providing anyone
Seems like you two are converging on the same problem
reply