In addition to chatGPT (especially chatGPT-4) and the various photographically, videography and digital art AI tools making headlines and already being used in workplaces, by students, and by individuals discovering the tools to express their artistry - links to a couple of threads below, there are many many things happening in the AI and machine learning space that are exciting, worrying, and life changing.

Visionaries who act quickly are paving the way, shaking up industries, and allowing others to consider what they might be able to do for interest and/or for income.

Our financial and societal structures need to change - all this AI ‘stuff’ is going to bring a rapid change. Just as people quickly realised they could earn money as influencers on social platforms, there will be new ways of making money, shaking up the old established ways, and causing grumpy oldsters to complain as they do about bloggers liking the sounds of their own voices, etc.

chatGPT discussion:
general-chatter/chatgpt-t52680-40.html

Photography and image creation discussion:
general-chatter/playing-around-the-beac ... 61-20.html



Holly+ … this was written in 2021

https://holly.mirror.xyz/54ds2IiOnvthjG ... AYy1irHy94

“the first tool of many to allow for others to make artwork with my voice, and will distribute ownership of my digital likeness through the creation of the Holly+ DAO (Decentralised Autonomous Organization)”

An NFT of a song created using Holly+ is minted by the DAO, with 50% of sales generated going to the artist, 40% to the DAO members, and 10% going to the creator of Holly.

The beginnings of real intelligence?

Bubeck got up, went to his computer, and asked GPT-4 to draw a unicorn using TikZ, a relatively obscure programming language for generating scientific diagrams. Bubeck was using a version of GPT-4 that only worked with text, not images. But the code the model presented him with, when fed into a TikZ rendering software, produced a crude yet distinctly unicorny image cobbled together from ovals, rectangles, and a triangle. To Bubeck, such a feat surely required some abstract grasp of the elements of such a creature. “Something new is happening here,” he says. “Maybe for the first time we have something that we could call intelligence.”

And this is the thing, we don’t yet know all the possibilities and their implications (singular and cumulative)

Understanding the potential or risks of AI’s new abilities means having a clear grasp of what those abilities are—and are not. But while there’s broad agreement that ChatGPT and similar systems give computers significant new skills, researchers are only just beginning to study these behaviors and determine what’s going on behind the prompt

.

Someone will…

Tenenbaum also says it isn’t clear that future generations of GPT would gain these sorts of capabilities, unless some different techniques are employed. This might mean drawing from areas of AI research that go beyond machine learning. And he says it’s important to think carefully about whether we want to engineer systems that way, as doing so could have unforeseen consequences.

https://www.wired.com/story/chatgpt-agi ... KA7hXWQYi0

Editor sacked for running a fake AI generated interview with Michael Schumacher

https://www.abc.net.au/news/2023-04-23/ ... -A6Zeq3vNU

"Die Aktuelle editor-in-chief Anne Hoffmann, who has held journalistic responsibility for the paper since 2009, will be relieved of her duties as of today."

The latest edition of Die Aktuelle ran a front cover with a picture of a smiling Schumacher and the headline promising "Michael Schumacher, the first interview".

They basically said it was AI generated. It was its tastelessness and being misleading that resulted in the sacking

April 12th, 2023
By UNIVERSITY OF MARYLAND BALTIMORE COUNTY

AI-Descartes: A Scientific Renaissance in the World of Artificial Intelligence

AI-Descartes, a new AI scientist, has successfully reproduced Nobel Prize-winning work using logical reasoning and symbolic regression to find accurate equations.

AI-Descartes, an AI scientist developed by researchers at IBM Research, Samsung AI, and the University of Maryland, Baltimore County, has reproduced key parts of Nobel Prize-winning work, including Langmuir’s gas behavior equations and Kepler’s third law of planetary motion. Supported by the Defense Advanced Research Projects Agency (DARPA), the AI system utilizes symbolic regression to find equations fitting data, and its most distinctive feature is its logical reasoning ability. This enables AI-Descartes to determine which equations best fit with background scientific theory. The system is particularly effective with noisy, real-world data and small data sets. The team is working on creating new datasets and training computers to read scientific papers and construct background theories to refine and expand the system’s capabilities.

The system demonstrated its chops on Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s equation of gas adsorption.

AI-Descartes, a new AI scientist, has successfully reproduced Nobel Prize-winning work using logical reasoning and symbolic regression to find accurate equations. The system is effective with real-world data and small datasets, with future goals including automating the construction of background theories.

In 1918, the American chemist Irving Langmuir published a paper examining the behavior of gas molecules sticking to a solid surface. Guided by the results of careful experiments, as well as his theory that solids offer discrete sites for the gas molecules to fill, he worked out a series of equations that describe how much gas will stick, given the pressure.

Now, about a hundred years later, an “AI scientist” developed by researchers at IBM Research, Samsung AI, and the University of Maryland, Baltimore County (UMBC) has reproduced a key part of Langmuir’s Nobel Prize-winning work. The system—artificial intelligence (AI) functioning as a scientist—also rediscovered Kepler’s third law of planetary motion, which can calculate the time it takes one space object to orbit another given the distance separating them, and produced a good approximation of Einstein’s relativistic time-dilation law, which shows that time slows down for fast-moving objects.

The research was supported by the Defense Advanced Research Projects Agency (DARPA). A paper describing the results will be published today (April 12) in the journal Nature Communications.
A machine-learning tool that reasons

The new AI scientist—dubbed “AI-Descartes” by the researchers—joins the likes of AI Feynman and other recently developed computing tools that aim to speed up scientific discovery. At the core of these systems is a concept called symbolic regression, which finds equations to fit data. Given basic operators, such as addition, multiplication, and division, the systems can generate hundreds to millions of candidate equations, searching for the ones that most accurately describe the relationships in the data.

AI-Descartes offers a few advantages over other systems, but its most distinctive feature is its ability to logically reason, says Cristina Cornelio, a research scientist at Samsung AI in Cambridge, England who is first author on the paper. If there are multiple candidate equations that fit the data well, the system identifies which equations fit best with background scientific theory. The ability to reason also distinguishes the system from “generative AI” programs such as ChatGPT, whose large language model has limited logical skills and sometimes messes up basic math.

“In our work, we are merging a first-principles approach, which has been used by scientists for centuries to derive new formulas from existing background theories, with a data-driven approach that is more common in the machine learning era,” Cornelio says. “This combination allows us to take advantage of both approaches and create more accurate and meaningful models for a wide range of applications.”

The name AI-Descartes is a nod to 17th-century mathematician and philosopher René Descartes, who argued that the natural world could be described by a few fundamental physical laws and that logical deduction played a key role in scientific discovery.
Suited for real-world data

The system works particularly well on noisy, real-world data, which can trip up traditional symbolic regression programs that might overlook the real signal in an effort to find formulas that capture every errant zig and zag of the data. It also handles small data sets well, even finding reliable equations when fed as few as ten data points.

One factor that might slow down the adoption of a tool like AI-Descartes for frontier science is the need to identify and code associated background theory for open scientific questions. The team is working to create new datasets that contain both real measurement data and an associated background theory to refine their system and test it on new terrain.

They would also like to eventually train computers to read scientific papers and construct the background theory themselves.

“In this work, we needed human experts to write down, in formal, computer-readable terms, what the axioms of the background theory are, and if the human missed any or got any of those wrong, the system won’t work,” says co-author Tyler Josephson, assistant professor of Chemical, Biochemical and Environmental Engineering at UMBC. “In the future,” he says, “we’d like to automate this part of the work as well, so we can explore many more areas of science and engineering.”

This goal motivates Josephson’s research on AI tools to advance chemical engineering.

Ultimately, the team hopes their AI-Descartes, like the real person, may inspire a productive new approach to science. “One of the most exciting aspects of our work is the potential to make significant advances in scientific research,” Cornelio says.

https://scitechdaily.com/ai-descartes-a ... elligence/

violet wrote: ↑Sun Apr 23, 2023 10:40 am Editor sacked for running a fake AI generated interview with Michael Schumacher

https://www.abc.net.au/news/2023-04-23/ ... -A6Zeq3vNU

"Die Aktuelle editor-in-chief Anne Hoffmann, who has held journalistic responsibility for the paper since 2009, will be relieved of her duties as of today."

The latest edition of Die Aktuelle ran a front cover with a picture of a smiling Schumacher and the headline promising "Michael Schumacher, the first interview".

They basically said it was AI generated. It was its tastelessness and being misleading that resulted in the sacking

The AI was willing to be Schumacher?

techietraveller84 wrote: ↑Mon Apr 24, 2023 10:02 am

violet wrote: ↑Sun Apr 23, 2023 10:40 am Editor sacked for running a fake AI generated interview with Michael Schumacher

https://www.abc.net.au/news/2023-04-23/ ... -A6Zeq3vNU

"Die Aktuelle editor-in-chief Anne Hoffmann, who has held journalistic responsibility for the paper since 2009, will be relieved of her duties as of today."

The latest edition of Die Aktuelle ran a front cover with a picture of a smiling Schumacher and the headline promising "Michael Schumacher, the first interview".

They basically said it was AI generated. It was its tastelessness and being misleading that resulted in the sacking

The AI was willing to be Schumacher?

I don't understand your humour.