Autopoiesis. A beautiful word.
And an utterly superfluous one.
You cannot do anything useful with it.
The word "living" is entirely sufficient. So forget about autopoiesis and work on living systems, making them "even more alive!" #systemsthinking#systemstheory#systems#betacodex#autopoiesis
@gimulnautti
Thanks for commenting!
I think you are mixing up things.
"A.I." is just software. To be exact: A.I. does not really exist, what exists is #machinelearning And that is complicated, dead. Just like any tech.
Only complex, living systems are autopoietic. All complex, living things are. "Living", in this context, of course does not mean "biologically alive".
@dianor We learned that lesson hard with conventional machine learning, trying to detect mentions of violence against education on Twitter a few years ago.
No matter how hard we trained and retrained the model, it still struggled to distinguish actual talk of violence (usually just repeating old news reports, so no value for early detection anyway) from kids talking about school sports, video games, strict teachers, or even "une bombe" meaning a sexy person in French.
The #AI Act is a flagship legislative proposal to regulate #ArtificialIntelligence based on its potential to cause harm. The #European Parliament is now inching toward formalising its position on the file, after #EU lawmakers reached a political agreement on Thursday (27 April). #machinelearning#llm#LLMs
For the evening crowd
Is it time for a change..? New positions advertised, full time and permanent, working right at the cutting edge of both basic climate and ice sheet research, and importantly, climate services, including drought, #Attribution + #SeaLevelRise.
I guess what I don't understand, why does AI have to look like magic omnipotence? We put in a question, and this software spits out an answer based on the data it's leeched off of other sources.
Why isn't there an expectation that an AI will cite it's sources like a wiki article?
If you were going to hand someone a single resource to get a basic, workable knowledge of #MachineLearning, neural networks, deep learning, #AI, etc. what would it be? Not looking to prime someone for a doctoral class but enough for the person to be able to talk about the concepts and play with some pre-built libraries and tools. Could be a book, a class, a video, anything.
Wait, if this scales up would this let us run these things on, say, our phones? If it replaces the transformer, could it replace other uses of the transformer, like Whisper? If it can do that and deliver equivalent or better results for those kinds of speed-ups, ML applications on edge computing will explode, again. And given the accessibility benefits of some existing tech, imagine being able to run that on something other than the cloud!
This new technology could blow away GPT-4 and everything like it https://www.zdnet.com/article/this-new-technology-could-blow-away-gpt-4-and-everything-like-it/#AI#MachineLearning
Comprehensive review on Self-Supervised Learning ("the dark matter of intelligence") with focus on vision tasks and lowering the high barrier to entry.
Content moderation and #RecommenderSystems are the most widely deployed #MachineLearning based action taking systems. By action taking, I mean an algorithm that suggests a particular decision that impacts human actions. Using this view of recommender systems, we can consider how to increase the #diversity of online content by re-ranking recommended items to encourage creation of diverse content in the long term.
"Tech companies have grown secretive about what they feed the AI. So The Washington Post set out to analyze one of these data sets to fully reveal the types of proprietary, personal, and often offensive websites that go into an AI’s training data."
The basic rationale is to use random split-half data to identify what's "true" versus sampling error. Scores are based on similarities between eigenvectors or cluster centres, rather than, e.g., the shape of the eigenvalue plot.