The Artificial Intelligence Thread

[publiusr]

No-no...having something that can do prints of all the art out there would be great.

Now we have chatterbots of the dead
https://www.inverse.com/innovation/amazon-alex-ai-dead-relatives-chat-bot

Misc:
https://techxplore.com/news/2022-09-aids-lips-masks.html
https://techxplore.com/news/2022-09-device-paves-technology-ease-daily.html
https://techxplore.com/news/2022-09-ai-enables-autonomous-vehicles-weather.html
https://techxplore.com/news/2022-09-low-cost-viable-solution-self-driving-cars.html

 

[rahullak]

Giant, free index to world’s research papers released online

In a project that could unlock the world’s research papers for easier computerized analysis, an American technologist has released online a gigantic index of the words and short phrases contained in more than 100 million journal articles — including many paywalled papers.

The catalogue, which was released on 7 October and is free to use, holds tables of more than 355 billion words and sentence fragments listed next to the articles in which they appear. It is an effort to help scientists use software to glean insights from published work even if they have no legal access to the underlying papers, says its creator, Carl Malamud. He released the files under the auspices of Public Resource, a non-profit corporation in Sebastopol, California, that he founded.

Some researchers who have had early access to the index say it’s a major development in helping them to search the literature with software — a procedure known as text mining. Gitanjali Yadav, a computational biologist at the University of Cambridge, UK, who studies volatile organic compounds emitted by plants, says she aims to comb through Malamud’s index to produce analyses of the plant chemicals described in the world’s research papers. “There is no way for me — or anyone else — to experimentally analyse or measure the chemical fingerprint of each and every plant species on Earth. Much of the information we seek already exists, in published literature,” she says. But researchers are restricted by lack of access to many papers, Yadav adds.

 

[think]

Living robots made in a lab have found a new way to self-replicate, researchers say:
https://www.npr.org/2021/12/01/1060027395/robots-xenobots-living-self-replicating-copy
this is xenobots made by an AI system I guess something is to be said of AI making organic life forms and such ?
and of course the video is on youtube of them self replicating

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yeah. and it makes me happy to have an AI thread discussion here in this section so I did not have to put up some kind of tread just for this topic-

 

[think]

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AlphaGo - The Movie | Full award-winning documentary
this is the documentary of the AI that wins at Go playing the best the best of the best number one Go player in the world --- Go is seriously big in the orient --- I mean really big-- yeah- I am posting this as it is an AI topic that --- deepmind is AI named in this video here --

Spoiler: spoiler for movie

AI is the best player and wins world wide

 

[Asbo Zaprudder]

An interesting technology for long-term storage:

Scientists claim big advance in using DNA to store data - BBC News

I don't envisage it ever replacing hard drives or SSDs but who knows? The same goes for DNA computing.

DNA computing - Wikipedia

Now building neutral networks out of real neurons that can reorganise - that would also be interesting, especially if it could be combined with evolutionary algorithms to optimise the network through plasticity. The novel of Contact by Carl Sagan described the aliens instructing us how to build such a device. That bit didn't make it into the movie.

 

[rahullak]

Advancing mathematics by guiding human intuition with AI

Abstract:
The practice of mathematics involves discovering patterns and using these to formulate and prove conjectures, resulting in theorems. Since the 1960s, mathematicians have used computers to assist in the discovery of patterns and formulation of conjectures1, most famously in the Birch and Swinnerton-Dyer conjecture2, a Millennium Prize Problem3. Here we provide examples of new fundamental results in pure mathematics that have been discovered with the assistance of machine learning—demonstrating a method by which machine learning can aid mathematicians in discovering new conjectures and theorems. We propose a process of using machine learning to discover potential patterns and relations between mathematical objects, understanding them with attribution techniques and using these observations to guide intuition and propose conjectures. We outline this machine-learning-guided framework and demonstrate its successful application to current research questions in distinct areas of pure mathematics, in each case showing how it led to meaningful mathematical contributions on important open problems: a new connection between the algebraic and geometric structure of knots, and a candidate algorithm predicted by the combinatorial invariance conjecture for symmetric groups4. Our work may serve as a model for collaboration between the fields of mathematics and artificial intelligence (AI) that can achieve surprising results by leveraging the respective strengths of mathematicians and machine learning.

@CorporalCaptain Right in your wheelhouse!

I got the gist. It's intriguing in how it could be used to further human-machine collaboration not just in science but also in other fields.

 

[Asbo Zaprudder]

Perhaps an AI could help someone deduce whether Category Theory and Constructor Theory are fundamentally linked.

 

[rahullak]

Asking for a friend?

 

[Gingerbread Demon]

Interesting and would genetic memory chips outlast their silicon cousins in terms of durability?

 

[Asbo Zaprudder]

Interesting and would genetic memory chips outlast their silicon cousins in terms of durability?

In long-term cryonic storage with appropriate error detection and correction when reading was necessary, potentially thousands of years. Lose the cooling, however, and it would quickly degrade. The problem as I see it is the assumption that civilisation is stable enough to maintain the support systems and the knowledge required to access the data. For SSDs and hard drives, you're talking about tens of years at most in a redundant RAID configuration.

 

[Gingerbread Demon]

What would a genetic SSD be like and would you need external systems to put it in a PC?

 

[Asbo Zaprudder]

No idea really - you're the person suggesting it. SSDs don't have the required degree of plasticity, I suspect. They are data storage devices, not computing devices. Real brains can rewire themselves; simulated neural networks have to, well, simulate this.

Eventually, someone will integrate neural network computation more fully into memory systems to improve efficiency of that sort of AI. How plasticity and genetic algorithm optimisation will be implemented, I don't know but nature already did the job in wetware.

 

[Gingerbread Demon]

No idea really - you're the person suggesting it. SSDs don't have the required degree of plasticity, I suspect. They are data storage devices, not computing devices. Real brains can rewire themselves; simulated neural networks have to, well, simulate this.

Eventually, someone will integrate neural network computation more fully into memory systems to improve efficiency of that sort of AI. How plasticity and genetic algorithm optimisation will be implemented, I don't know but nature already did the job in wetware.

No I meant if we get to the point where we can have genetic memory chips would they need anything to keep the material "fresh" or could they be self contained? If the answer to that is yes and you don't need any kind of external support to keep the chip's fresh could you then have a genetic SSD?

 

[Asbo Zaprudder]

At the moment, what is being developed is more like long-term offline backup storage. It has much longer write and read times than SSDs and hard drives. It also requires cryogenics. I don't know if it can be made workable in non-controlled environments but ordinary DNA and RNA usually degrade very rapidly after an organism dies. I expect there might be more robust atomic-scale substrates that could be used - all they have to do is encode 0s and 1s. A scanning tunnelling microscope could in principle be used to perform both reading and writing. This was being researches nearly 30 years ago - I don't know whether it still is.

Scanning Tunneling Microscopes (STM) - Functionality and Applications (azonano.com)

 

[Asbo Zaprudder]

Asking for a friend?

It sounds like a valid area of research - I'm sure there is at least one PhD's worth there.

 

[think]

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The danger of AI is weirder than you think | Janelle Shane

AI problems (stupid AI). like it doesn't know what a human is --- or the meaning of words or things like that you know communication ---

 

[Gingerbread Demon]

Let AI run government, can't be worse then the meatbags

 

[rahullak]

DeepMind’s AI helps untangle the mathematics of knots

Because machine learning requires lots of data to train on, one requirement was to be able to calculate properties for large numbers of objects: in the case of knots, the team calculated several properties, called invariants, for millions of different knots.

The researchers then moved on to working out which AI technique would be most helpful for finding a pattern that linked two properties. One technique in particular, called saliency maps, turned out to be especially helpful. It is often used in computer vision to identify which parts of an image carry the most-relevant information. Saliency maps pointed to knot properties that were likely to be linked to each other, and generated a formula that seemed to be correct in all cases that could be tested. Lackenby and Juhász then provided a rigorous proof that the formula applied to a very large class of knots.

Williamson focused on a separate problem, regarding symmetries. Symmetries that switch around finite sets of objects have an important role in several branches of maths, and mathematicians have long studied them using various tools, including graphs — large abstract networks linking thousands of nodes — and algebraic expressions called polynomials. For decades, researchers have suspected that it would be possible to calculate the polynomials from the networks, but guessing how to do it seemed like a hopeless task, Williamson says. “Very quickly, the graph becomes beyond human comprehension.”

With the computer’s help, he and the rest of the team noticed that it should be possible to break down the graph into smaller, more-manageable parts, one of which has the structure of a higher-dimensional cube. This gave Williamson a solid conjecture to work on for the first time.

These are two examples of how AI/ML can be used to "narrow the field" when dealing large amounts of data or highly complex data, so that patterns that are actually relevant can be highlighted and then further explored/proved/theorised.

@Christmas Corps What are your thoughts on these techniques and application?

 

[CorporalCaptain]

DeepMind’s AI helps untangle the mathematics of knots




These are two examples of how AI/ML can be used to "narrow the field" when dealing large amounts of data or highly complex data, so that patterns that are actually relevant can be highlighted and then further explored/proved/theorised.

@Christmas Corps What are your thoughts on these techniques and application?

It's starting to look like a tentative step along the way to cyborg intelligence, specifically as it pertains to applying computers to recognize patterns in data that is beyond human ability to perceive.

 

[Asbo Zaprudder]

Neural networks should be able to recognise patterns in multidimensional spaces so I'm wondering if they could be used to help determine the likely configuration of the six-dimensional Calabi-Yau manifold or seven-dimensional Joyce manifold on which strings vibrate to give rise to the properties of what we identify as fundamental particles.

Dimensions, Wound Strings, Branes, and Calabi Yau Spaces (archive.org)