For Food's Sake

In a perfect world, this would destroy the artificial food industry

Want to know how processed your food is? There's an algorithm for that

Jun 2023, phys.org

https://medicalxpress.com/news/2023-06-food-algorithm.html

The fingerprint of food processing:

"In the paper what we do is really say that we believe that nutritional information, so the chemicals that are measured as nutrients in the nutritional facts, somehow encode the fingerprint of food processing," says Giulia Menichetti, senior research scientist at Northeastern's Network Science Institute and lead author of the research. "Because when we process a food, when we modify some staple ingredients, we change its chemistry in many different ways."

That "fingerprinting" is the way that researchers can glean insight into just how many chemical alterations have been made to a given food using the U.S. Department of Agriculture's Food and Nutrient Database for Dietary Studies.

The machine learning classifier called FoodProX is from the Foodome project. 

The researchers note how the NOVA system, which splits foods into four classifications, from "unprocessed or minimally processed" to ultra-processed, is fundamentally limiting because it doesn't account for the different gradations of processing within each separate category.

More than 73% of the U.S. food system is ultra-processed. And tobacco companies own the food companies, in case you didn't know, like I didn't know. Companies never die, they only change their names, and the people who run them. Companies are transcendental intelligent entities, a sentient superorganism. In this case, it is a superorganism that is literally devouring the human population, eating the years off of our collective life expectancies in order to survive. Or are we all just cells that must be sloughed, part of a normal-functioning healthy system?

via Center for Complex Network Research at Northeastern University: Giulia Menichetti et al, Machine learning prediction of the degree of food processing, Nature Communications (2023). DOI: 10.1038/s41467-023-37457-1

https://dx.doi.org/10.1038/s41467-023-37457-1

(I believe the Center for Complex Network Research at Northeastern University was the original home of the Barabasi Lab [link])

Image credit: AI Art - Will Sing For Food - 2024

To Repeat: The food industry is really the tobacco industry in disguise, and that most Americans eat one extra meal a day in junk food.

--US tobacco companies selectively disseminated hyper-palatable foods into the US food system: Empirical evidence and current implications. TL Fazzino, D Jun, L Chollet-Hinton, K Bjorlie. Addiction v119i1pp62-71 Jan 2024, 08 September 2023 https://doi.org/10.1111/add.16332

--Snacks contribute considerably to total dietary intakes among adults stratified by glycemia in the United States. K Heitman, CA Taylor, et al. PLoS Global Public Health. October 26, 2023. https://doi.org/10.1371/journal.pgph.0000802

Bonus:

AI Art - Cigarette Food Robot Confusion - Three Ladies Smoking in the Kitchen - 2023

Image credit: Note the thumbnail image above, and how AI Art doesn't understand how we use our mouths, and anytime you want a picture of someone eating, or smoking a cigarette for that matter, it looks like this. Meanwhile, consider the these image generator models are trained on The Internet, which we all know is 99% porn. Now remove the porn images from the trained model, i.e., "unlearn" the porn, and this is what you get - a robot that doesn't understand what a mouth is. 

Wearable Eyeballs

From the microcosm to the macro, here's a couple headlines that are only related by their mention of solar panels.

Flea-sized solar panels embedded in clothes can charge a mobile phone
Dec 2018, phys.org

Team locates nearly all US solar panels in a billion images with machine learning
Dec 2018, phys.org

It sounds improbable that our clothes will one day power our electronic devices. But as our ability to draw electricity from the sun gets better, and as our devices demand less energy for more computation output, it seems inevitable.

The second headline reminds us that Big Data has found its match in Deep Learning. And this is one of the best examples, where satellites orbiting the Earth, their persistent gaze, from so omnipotent a vantage point, are generating data about us and our planet that we never thought we would see.

Beginning a few years ago we saw a similar thing perhaps even more ingenious - satellite images were used to measure the extent of infrastructure in regions without organized or reliable records for such things. A metal roof shines differently than no roof at all. And roads covered in asphalt (which contains tiny, sparkling glass pieces) will also shine differently. So the data is there. What I will call low resolution data, digested on such a large scale, becomes high resolution data.


Notes:
Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep
Learning [pdf]
Stanford et al, 2018

Chatbots Start Speaking Their Own Language and It's not Esperanto

Facebook Shuts AI System After Bots Start Speaking Their Own Language, Defy Human Instructions
July 2017, Hindustan Times

Don't even get 'em started. As I tear through Kim Stanley Robinson's Auroroa, a hard science fiction novel about a starfleet trying to colonize the Tau Ceti system where the ship itself, due to its quantum-computer-powered artificial intelligence system, becomes conscsious, I read this headline.

I'm not surprised, nobody is surprised, that these chatbots, these intelligentities, have surpassed our ability to decode what the f they're doing. Deep learning neural networks, for example, are unintelligible to us (correct this, I read a paper recently about some folks successful in figuring out how to read the hidden programs developed by these learning networks). Computers, ultimately, speak a language of computation, 1's and 0's. So it should be no surprise that, given a complex task of negotiating mock global diplomacy matters, these systems tack at a better way for working with each other.

Still, it is symbolic. And only to humans do symbolic things matter. Maybe there's a reason for that; maybe this is the beginning. That distance between now and the inevitable transition to the post-human world keeps getting shorter.

Post Script
It Begins: Bots are learning to chat in their own language
July 2017, Cade Metz, WIRED

Art and AI

Frederic Bazille’s Studio 9 Rue de la Condamine (1870) and Norman Rockwell’s Shuffleton’s Barber Shop (1950)

When A Machine Learning Algorithm Studied Fine Art Paintings, It Saw Things Art Historians Had Never Noticed
The Physics arXiv Blog via Medium, Aug 2014
Source document: Toward Automated Discovery of Artistic Influence

There's some stirring in the dusty world of art history, with the rise of encultured robots threatening human livelihoods. A promising young algorithm is set upon the world, fed with centuries of art imagery, design principles, and historical documentation. Our little algorithm then grows up and learns how to identify patterns in the art world better than its teacher.

In the two compared images above, this little art-historian algo recognized similar compositional patterns that had never been seen before - a hidden Norman Rockwell, see above.

First of all, as an art history major in college, I look at all the compared/related images discovered by the AI, and I am not so impressed. Maybe the general concept is what fails to impress me. When you follow the art world long enough you get to know something about how influence works, and about the power that one thing can have on an artist's work. And I say that there is no such thing as one thing.

The nature of the artist is to take the world at large, a fuck-tonnery of pre-filtered miasma, and to make sense, or at least to fight with it in a way that leaves a record of the battle, and for the benefit of humankind. To say that one painting influenced another because they have similar stylistic elements or design principles is kind of silly. I do understand that subconscious influence has its way with the creative process. But that refers to life as well as art. The new style checker cab, or Triangle shirtwaists, or bubble tea or middle-hipster Americana folk music or The Beatles or African masks or even syphilis could influence an artists' work.

Charge of the Lancers - Umberto Boccioni - 1915

Take ^Futurism, for example. It is inspired by, among other things, the fragmentation of society, be it from national upheaval circa the World Wars, or from the way the landscape looks while riding a speeding train which propelled people faster past the countryside than they had ever moved before. How does an algorithm find that?

I heard Picasso's mistress Françoise Gilot, in her bio of Pable Picasso, say some of his lobster paintings were a response to her hard-shelled personality which came to a head prior to their separation. Algorithms can see that? Nah man.

I know someone can come on here and argue with me, successfully, that artists do influence each other in simple visual ways, and at times, the visual connections can supplement a lack of historical data surrounding their work. But still, there is a need for socio-biographical data in all this, and I wonder if our little algo could be even better trained.

Now, all this having been said, I just finished watching this: Davos talk about the future of artificial intelligence, with IBM CEO Ginni Rommetti. She says that the goal of IBM's artificial intelligence (Watson, by the way, in case you forgot) is to extend human faculties, not replace them. According to her premonitions, the art historian is not doomed, rather it will be enriched and extended by our algorithmic overlords.