ARTIFICIAL INTELLIGENCE AND NANOTECH

If you're a regular reader here, you'll probably already know that I am increasingly skeptical, and to a certain extent, alarmed, about the breakneck speed with which artificial intelligence not only is being developed, but being "pushed" as a kind of panacea for all of humanity's ills. I think, in fact, that we are approaching a kind of idolatry with it, the kind of idolatry we've seen in the past when similar idols have been worshipped, with catastrophic results, whether governments or ideologies were the idols. It's a kind of Idol of the Cave, to invoke one of Francis Bacon's four idols, in this case, the idol of the technocrat, viewing everything through the eyes of a computer.

So today I want to indulge in more of my high octane speculation in the form of more artificial intelligence alarmism. Hopefully, I'm utterly and completely wrong about today's high octane artificial intelligence apocalypse, in which case we can all have a laugh at my Luddite sympathies and warnings, and go back to welcoming the golden age that artificial intelligence will bring. Today's high octane speculation was brought about, in part, because of the following article submitted by S.D. (with our thanks):

AI automates the creation of custom materials

Three paragraphs in particular leapt out at me:

In a landmark study published in ACS Nano, the ORNL researchers, from the Center for Nanophase Materials Sciences (CNMS), describe the creation of a fully automated system capable of building functional materials atom-by-atom. The effort grew from a conceptual framework shaped by P. Ganesh and Arthur P. Baddorf, together with An-Ping Li and Rama Vasudevan, who supervised the implementation and guided the interpretation of the results.

Turning that vision into a working platform required an unusual blend of software and hands-on experimental skill. Ganesh Narasimha prepared the core automation software based on inputs from Vasudevan, while Mykola Telychko developed the experimental setup; the two then jointly carried out the manipulation trials and assembled the resulting dataset. Wooin Yang helped design the AI’s object-detection workflow and performed the critical spectroscopic studies used to verify the materials. Narasimha said the collective effort enables “atomically precise fabrication, with significantly reduced human input.” He added that this effort is shifting the research paradigm from discovering materials in nature to engineering specific “artificial lattices,” which are orderly, repeating patterns of atoms or molecules that form a material’s underlying framework, with tailored electronic behaviors.

The team developed AI models that served as microscopic “eyes” and a “brain.” As the “eyes,” a computer vision model called YOLO (“You Only Look Once”) was used to rapidly detect molecules on a copper surface. As the “brain,” reinforcement learning enabled the model to evaluate different strategies for moving molecules and receive a numerical reward based on how well each attempt succeeded. The reward was highest when a molecule reached the intended target site and much lower when it missed. By linking higher rewards to the actions that produced them, the model learned the best combination of electrical current, bias and manipulation speed to nudge molecules into place without damaging the microscope tip. (Emphasis added)

If you've been paying attention to the nanotechnology revolution, you'll recall that the original "classical text" on the subject, Eric Drexler's Engines of Creation (1986) or his much more technical Nanosystems (1992), theorized about the ability to create tiny programmable machines or robots able to engineer materials literally at the scale of atoms and individual molecules. But this vision of atom- and molecule-sized programmable machines was akin to the era of the computer whose program ran on punchcards and magnetic tapes. The program, once set, never varied. This feature led Drexler to propose the ultimate nano-apocalypse: the "grey goo" scenario, where a nano-robot was programed to take any material it encountered and reconfigure its molecular structure into producing nothing but grey goo. One let loose in the world, the nanobots would turn everything - your favorite meal, movie, plant, person, novel...whatever - into a non-descript grey goo, a kind of "cosmos-as-tapioca-pudding" scenario.  We saw this scenario "updated" a bit during the covid planscamdemic, as various technocratic or billionaire busybodies were proposing "updatable and downloadable" quackcines that were injections of nanotechnologies that could be programmed (or reprogrammed) remotely.

But notice now what is being proposed in the article is the wedding of artificial intelligence to the nanosystems technology so that the nano-machines can program themselves and "adapt" to situations as they arise... and in a world where artificial intelligences based on large language models increasingly generate more and more gibberish with each iteration of the recursive application of its own generated data, and that "grey goo-universe-as-tapioca-pudding" scenario takes a significant step closer to reality... imagine AI-adjusted or created drugs (the computer model certainly did not give any warning that it could cause an epidemic), or composite materials for airplanes (it worked ok in the wind tunnel, we have no idea why it crashed)....

Of course, I could be entirely wrong, and we may all have a laugh at my expense someday... but if I am not wrong, I'll be holding the world's biggest "I told you so" party...

See you on the flip side...

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