The Best of LessWrong

#11

Money can buy a lot of things, but it can't buy expertise. In fields where performance is hard to judge, simply throwing money at the problem won't guarantee good results – it's too easy to be fooled. Even kings and governments can't necessarily buy their way to the best solutions.

#17

My computational framework for the brain

Steve Byrnes lays out his 7 guiding principles for understanding how the brain works computationally. He argues the neocortex uses a single general learning algorithm that starts as a blank slate, while the subcortex contains hard-coded instincts and steers the neocortex toward biologically adaptive behaviors.

#20

Anti-Aging: State of the Art

Aging, which kills 100,000 people per day, may be solvable. Here's a summary of the most promising anti-aging research, including parabiosis, metabolic manipulation, senolytics, and cellular reprogramming.

#21

Interfaces as a Scarce Resource

The structure of things-humans-want does not always match the structure of the real world, or the structure of how-other-humans-see-the-world. When structures don't match, someone or something needs to serve as an interface, translating between the two. Interfaces between complex systems and human desires are often a scarce resource.

#34

How uniform is the neocortex?

The neocortex has been hypothesized to be uniformly composed of general-purpose data-processing modules. What does the currently available evidence suggest about this hypothesis? Alex Zhu explores various pieces of evidence, including deep learning neural networks and predictive coding theories of brain function. [tweet]

#41

Swiss Political System: More than You ever Wanted to Know (I.)

The Swiss political system is known for its extensive use of direct democracy. This post dives deep into how that system works, exploring the different types of referenda, their history, impacts, and quirks. It's a detailed look at a unique political system that has managed to largely avoid polarization.

#43

Transportation as a Constraint

John examines the problem of "how to transport things?" through the lens of "what's the taut constraint on the system?" He asks questions across history, from "how could Alexander the Great's army cross 150 miles of desert?", to how modern supply chains work, to what would happen in a future world with teleportation.

11Steven Byrnes

I wrote this relatively early in my journey of self-studying neuroscience. Rereading this now, I guess I'm only slightly embarrassed to have my name associated with it, which isn’t as bad as I expected going in. Some shifts I’ve made since writing it (some of which are already flagged in the text): * New terminology part 1: Instead of “blank slate” I now say “learning-from-scratch”, as defined and discussed here. * New terminology part 2: “neocortex vs subcortex” → “learning subsystem vs steering subsystem”, with the former including the whole telencephalon and cerebellum, and the latter including the hypothalamus and brainstem. I distinguish them by "learning-from-scratch vs not-learning-from-scratch". See here. * Speaking of which, I now put much more emphasis on "learning-from-scratch" over "cortical uniformity" when talking about the neocortex etc.—I care about learning-from-scratch more, I talk about it more, etc. I see the learning-from-scratch hypothesis as absolutely central to a big picture of the brain (and AGI safety!), whereas cortical uniformity is much less so. I do still think cortical uniformity is correct (at least in the weak sense that someone with a complete understanding of one part of the cortex would be well on their way to a complete understanding of any other part of the cortex), for what it’s worth. * I would probably drop the mention of “planning by probabilistic inference”. Well, I guess something kinda like planning by probabilistic inference is part of the story, but generally I see the brain thing as mostly different. * Come to think of it, every time the word “reward” shows up in this post, it’s safe to assume I described it wrong in at least some respect. * The diagram with neocortex and subcortex is misleading for various reasons, see notes added to the text nearby. * I’m not sure I was using the term “analysis-by-synthesis” correctly. I think that term is kinda specific to sound processing. And the vision analog is “vision

13DirectedEvolution

What this post does for me is that it encourages me to view products and services not as physical facts of our world, as things that happen to exist, but as the outcomes of an active creative process that is still ongoing and open to our participation. It reminds us that everything we might want to do is hard, and that the work of making that task less hard is valuable. Otherwise, we are liable to make the mistake of taking functionality and expertise for granted. What is not an interface? That's the slipperiest aspect of this post. A programming language is an interface to machine code, a programmer to the language, a company to the programmer, a liaison to the company, a department to the liaison, a chain of command to the department, a stock to the chain of command, an index fund to the stock, an app to the index fund. Matter itself is an interface. An iron bar is an interface to iron. An aliquot is an interface to a chemical. A fruit is an interface, translating between the structure of a chloroplast and the structure of things-animals-can-eat. A janitor is an interface to brooms and buckets, the layout of the building, and other considerations bearing on the task of cleaning. We have lots of words in this concept-cluster: tools, products, goods and services, control systems, and now "interfaces." "As a scarce resource," suggests that there are resources that are not interfaces. After all, the implied value prop of this post is that it's suggesting a high-value area for economic activity. But if all economic activity is interface design, then a more accurate title is "Scarce Resources as Interfaces," or "Goods Are Hard To Make And Services Are Hard To Do." The value I get out of this post is that it shifts my thinking about a tool or service away from the mechanism, and toward the value prop. It's also a useful reminder for an early-career professional that their value prop is making a complex system easier to use for somebody else, rather than ticking the bo

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