Month: April 2021

Engram

Almost all neuroscientists base their search—for the physical basis of memory (the engram)—on the assumption that temporal-pairing causes learning. They are dedicated to this assumption—even though, as Rescorla pointed out 50 years ago, experimental attempts to define temporal-pairing have always failed. This failure is as striking now as it was 50 years ago. Anything that gets neuroscientists to abandon the idea that temporal-pairing is a useful scientific concept is a step toward discovering the physical basis of memory. Each neuron contains billions of (almost) incomprehensibly-tiny molecular machines. Molecular biologists have developed an astonishing array of techniques for visualizing/manipulating the actions of these little machines. These techniques will allow molecular biologists to follow the machines inside this huge neuron to the engram—to the tiny machine that encodes the experience-gleaned facts so that these learned/remembered facts can inform later behavior.

2021-11-19: This feels like a really big deal:

Biology feels different right now. New broadly enabling technologies and tools are driving forward progress in nearly every specific field at a rapid pace. The large scale adoption and application of a powerful set of common tools has created a virtuous cycle of further technology refinement and engineering. The rate of iteration is increasing, and previously intractable problems are now within reach. While RNA-seq and MPRAs are both valuable approaches, they come with some limitations. Fundamentally, each measurement represents a single static slice of a dynamic process which is only inferred by attempting to piece together the slices. The quality of the reconstruction is limited by sampling density. What if we could measure these systems continually as they occurred in a way that didn’t require destructive sampling? Here, the fundamental idea is that “DNA is the natural medium for biological information storage, and is easily ‘read’ through sequencing.” This forms the basis for this new technology: ENGRAM (ENhancer-driven Genomic Recording of transcriptional Activity in Multiplex). The workflow of this technique is very similar to that of the MPRA introduced above, but with an important twist. Instead of destroying the cell and sequencing a ratio of barcodes, the transcription event is recorded by the insertion of a barcode into a locus of DNA in the cell via prime editing. They went further and showed that they could effectively multiplex this technique by reading out all 3 signals in response to stimulants in a single population of cells. Even more, they showed a proof-of-concept for reading out the order in which events occurred.

Human Challenge Trials

we need far more human challenge trials, and far less garbage people like ethicists.

In interviews, former challenge trial participants described motives for their participation that ranged from the light-hearted — several imagined it would be a fun story to tell at scientific conferences and parties — to the serious. Some spoke of altruistic motives, often shaped by personal experiences. “I spent a couple years in Africa; I was in the Peace Corps. I think for me, seeing that firsthand, and knowing that there might be some way that maybe I can be a part of figuring out whether or not we can make a vaccine for malaria definitely played a big part in it for me.”

Innovation Wealth

People who don’t look any deeper than the Gini coefficient look back on the world of 1982 as the good old days, because those who got rich then didn’t get as rich. But if you dig into how they got rich, the old days don’t look so good. In 1982, 84% of the richest 100 people got rich by inheritance, extracting natural resources, or doing real estate deals. Is that really better than a world in which the richest people get rich by starting tech companies? Why are people starting so many more new companies than they used to, and why are they getting so rich from it? The answer to the first question, curiously enough, is that it’s misphrased. We shouldn’t be asking why people are starting companies, but why they’re starting companies again. In 1892, the New York Herald Tribune compiled a list of all the millionaires in America. They found 4047 of them. How many had inherited their wealth then? Only @20% — less than the proportion of heirs today. And when you investigate the sources of the new fortunes, 1892 looks even more like today. Hugh Rockoff found that “many of the richest … gained their initial edge from the new technology of mass production.”

See also income inequality

Virtual Courts

In July the Conference of Chief Justices and the Conference of State Court Administrators jointly endorsed a set of “Guiding Principles for Post-pandemic Court Technology” with a blunt message: The legal system should “move as many court processes as possible online,” and keep them there after the risk of infection passes. The pandemic, they wrote, “is not the disruption courts wanted, but it is the disruption that courts needed.”

Tenants facing eviction in Arizona and parents threatened with losing their children in Texas also proved much more likely to make their court dates when they could do so online. Likewise citizens summoned for jury duty: In Texas, 60-80% show up online. That’s 2x as many as formerly appeared in person. The trend bodes well for diversifying juries, which tend to skew white and affluent.

As these trade-offs become clearer, some initial consensus is emerging as to what virtual courts should and shouldn’t do post-pandemic. Just about everyone, even a skeptic like Douglas Hiatt, agrees that they should keep handling the routine business—from scheduling and settlement conferences to contested traffic tickets and uncontested divorces—that fills most court time.

Microwave boilers

Arrays of these devices beam microwaves into water in a boiler, heating it up. The pipes that carry the water are also made of microwave-sensitive materials, as is the insulation that lags them. And a heat exchanger recycles residual waste warmth. The upshot is a boiler that is 96% efficient. The best existing gas boilers rarely exceed 90%.

nft_ptr

C++ std::unique_ptr that represents each object as an NFT on the Ethereum blockchain.

Why?

Biggest issue facing $125 billion security industry: Memory safety.
“~70% of the vulnerabilities addressed through a security update each year continue to be memory safety issues.” – Microsoft Security Response Center

The world’s largest codebases are written in C++
Browsers, operating systems, databases, financial systems

C++ memory management is hard to understand, opaque, and not secure

As we all know, adding blockchain to a problem automatically makes it simple, transparent, and cryptographically secure.

Thus, we extend std::unique_ptr, the most popular C++ smart pointer used for memory management, with blockchain support

Non-Fungible Tokens and std::unique_ptr have the exact same semantics:
each token/object is unique, not fungible with other tokens/objects
each token/object is owned by 1 owner/unique_ptr
others may view the NFT/use the object, but only the owner can transfer/destroy the NFT/object.
absolutely no protection against just pirating the image represented by the NFT/copying the pointer out of the unique_ptr

Written in Rust for the hipster cred.

2021-11-11: Funny and poignant web3 critique here:

Even at comparable stages in their development, the World Wide Web and Web 2.0 were not quite so … self-referential? They were about other things — science and coffee pots and links and camera lenses — while Web3 is, to a first approximation, about Web3. For all the Web3 rhetoric around the potential rewards for “users”, Ethereum only recognizes “wallets”. One user can control many wallets; one BOT can control many wallets; Ethereum doesn’t know the difference, doesn’t care. Therefore, Web3’s governance tools are appropriate for decision-making processes that approximate those of an LLC, but not for anything truly democratic, which is to say, anything that respects the uniform, unearned — unearned!—value of personhood.