Intro LO:
The Scientific American article below might be a good example why the future of technology is with machine learning rather than with artificial intelligence (AI). This quote from online news source 1440 may help understand:
“Researchers found 70,500 previously unknown RNA viruses using an AI model that combines machine learning with protein structure prediction to identify viral sequences in genomic data. The breakthrough not only reveals an array of unique viruses, including some found in extreme environments, but also sheds light on AI’s potential in exploring the “dark matter” of the RNA virus universe. The findings could also aid in understanding disease origins and microbial evolution. See an overview of RNA here.“
A quote from 1440 Daily Digest, 12 October 2024
I suppose humans will always get distracted and will either lose perspective, or lose focus – or both. It’s highly unlikely that machines will ever lose attention.
Hence, the technological revolution of 1800-2100 is about machines:
- engines (1800-1900),
- computers (1900-2000),
- machine-learning, artificially intelligent, robots (2000-2100).
Nobel Prize in Physics Awarded for Breakthroughs in Machine Learning
Scientific American, Space & Physics title: Nobel Prize in Physics Awarded for Breakthroughs in Machine Learning
Date: 10 October 2024
By: Lee Billings, Senior Editor, Space and Physics
“The 2024 Nobel Prize in Physics was given to John Hopfield and Geoffrey Hinton for development of techniques that laid the foundation for revolutionary advances in artificial intelligence
A Nobel Prize in Physics for… AI?
For science journalists such as myself, covering the Nobel Prizes can be a nerve-wracking experience. In October of each year as we dutifully await the announcement of the latest prizewinners, many of us wonder if the Nobel Committee will throw us a topical curveball. And this year’s Physics Nobel for breakthroughs in machine learning was certainly a curveball, as the research involved scarcely concerns physics at all, but rather dwells in the realm of computer science. The tech-heavy trend continued with this year’s Chemistry Nobel, which also went to machine-learning approaches—this time for predicting and designing protein structure and function.
Besides inspiring some obvious jokes (“Will next year’s Nobel Prize in Literature honor the inventors of Microsoft Word’s autocomplete function, perhaps?”), the trend does highlight a very real concern: Just as “one device to rule them all” smartphones have rendered most other general consumer electronic gadgets obsolete, are artificial intelligence and machine learning going to do the same thing for scientific research? Is this trend of tech-heavy Nobels a signal of The End of Science?!
Dear reader, I won’t pretend to really know the answer, but my guess is that the much-hyped rise of AI isn’t the existential threat to old-fashioned flesh-and-blood ingenuity and intuition that some pundits proclaim. Not yet, anyway. These new technologies are first and foremost tools for human use, much like their predecessors the integrated circuit and the optical fiber (both of which also received Nobels). In most cases, actually making them usefulwill still require having humans involved. The relationship is symbiotic. Real science demands a lot of simple-but-hard work at which humans excel.
The real imminent threat science now faces from this notional rise of the machines is the prospect of too many scientists and their sponsoring institutions prematurely buying in to the hype, favoring and funding AI-infused projects and proposals at the expense and exclusion of all others. And in this respect, at least, 2024’s tech-heavy science Nobels may be an ill portent indeed.”
Sources:
- Scientific American, 10 October 2024: Nobel Prize in Physics Awarded for Breakthroughs in Machine Learning;
- Washington Post, 11 October 2024: When AI looked at biology, the result was astounding;
- Your Genome: What is RNA?
0 Comments