slate.com The Leak That Has Big Tech and Regulators Panicked
The open-source revolution has come to A.I.
In the only loaf like picture I have it didn’t find my cat because it’s only her butt :(
Interesting experiment! Made me think of the book “how we learn: the new science of education and the brain”
Never used it :).
Keep me updated on your progress, I barely have any time to do it as thoroughly as you and so I’ll be glad to learn from your experiment also
It’s not so theory heavy but I’ve enjoyed the paper titled “what uncertainty do we need in Bayesian deep learning for computer vision?” By Kendall and Gal of Cambridge.
If you find some nice introductory/theory paper please share them also :)!
Bayesian neural networks are a thing ;)
Before selling the 5, they should make it so one can buy the 4 x)
Thanks for sharing! I’ll have a look later it sounds great!
Big Tech Isn’t Prepared for A.I.’s Next Chapter
Any way to bypass the paywall for this article :)?
Sparse Networks Come to the Aid of Big Physics
www.quantamagazine.org Sparse Neural Networks Point Physicists to Useful Data | Quanta Magazine
A novel type of neural network is helping physicists with the daunting challenge of data analysis.
That’s a fairly terrifying scenario. Like putting open doors into our brains
I’m sorry my answer triggered something; it wasn’t meant to. In my experience people here are nice and friendly, so I hope you manage to feel safe and welcomed.
To Move Fast, Quantum Maze Solvers Must Forget the Past
www.quantamagazine.org To Move Fast, Quantum Maze Solvers Must Forget the Past | Quanta Magazine
Quantum algorithms can find their way out of mazes exponentially faster than classical ones, at the cost of forgetting the path they took. A new result suggests that the trade-off may be inevitable.
What 😅? Ok I guess 😅
I was just saying it’s hard to make a company spend more “just” for the environment, but it’s still important to do.
I’m trying at mine and it goes exactly as you would think…
Introducing Keras Core: Keras for TensorFlow, JAX, and PyTorch.
In the study, physicians found more inaccuracies and irrelevant information in answers provided by Google’s Med-PaLM and Med-PalM 2 than those of other doctors.
It’s a bit like every other use of AI IMO: the challenge is to make people understand that it’s a fancy information retrieval system and thus it is flowed and not to be blindly trusted. There was study on the use of professional settings that showed that model such as ChatGPT helped low performers much more than high performers (which had barely any improvement thanks to the model). If this model is used to help less competent doctors (without judgement, they could be beginning their careers) while maintaining a certain degree of doubt, then that could be very good.
However, the ramification of a wrong diagnosis from the AI is quite scary, especially considering that AI tend to repeat the biais of their training dataset, and even curated data is not exempt from biais
I would advise not training your own model but instead use tools like langchain and chroma, in combination with a open model like gpt4all or falcon :).
So in general explore langchain!
merci j’avais pas réaliser ça!
wyss.harvard.edu Team builds first living robots—that can reproduce
AI-designed Xenobots reveal entirely new form of biological self-replication—promising for regenerative medicine
distill.pub A Gentle Introduction to Graph Neural Networks
What components are needed for building learning algorithms that leverage the structure and properties of graphs?
'Organoid Intelligence' — how mini-brains could replace AI for supercomputing
I ended up making the robotics_and_ai community. Let's see how it goes :)
The Curse of Recursion: Training on Generated Data Makes Models Forget
Synthetic data is often used to trian model because data is hard to collect. But, now that we have a lot data generated by AI, we are realizing it may not be as valuable
Robotics and AI
A community about the latest advances in robotics and AI. Focused on the science and state-of-the-art.
or mander.xyz/c/robotics_and_ai
interestingengineering.com Necrobiotics: Researchers are turning dead spiders' legs into robotic grippers
Mechanical engineers Daniel Preston and Faye Yap of Rice University have devised a method of using dead spiders to delicately grasp small object and other tiny animals.
I'm not sure if I shouldn't mark this one as NSFW X).
I don't often feel like science went too far, but necrobiotics might be a step too far... I tend to agree with this take against it.
A New Approach to Computation Reimagines Artificial Intelligence
www.quantamagazine.org A New Approach to Computation Reimagines Artificial Intelligence | Quanta Magazine
By imbuing enormous vectors with semantic meaning, we can get machines to reason more abstractly — and efficiently — than before.
Interesting article! I wholeheartedly agree with every other topic but I partly disagree on the AI front. AI has a topic is much wider than crypto and nfts, and better defined than the meta verse. It has concrete uses from document extraction, to protein prediction, and data analysis. However, where I agree with the author is that, on platform like LinkedIn, you find so many quacks who are suddenly experts, telling how AI is the game changer that you didn’t know for something completely unrelated. There is a va lot of pseudo science and false (but seemingly logic) conclusions thrown around. And that’s where the gift is: not in the technology, but in the marketing by scammers.
E.g. they keep on pushing that, as an expert, AI will replace you unless you adapt and that only those who use ai will survive. However, early research shows the opposite and that using AI actually help low performers and has little impact for experts. Here is an interesting podcast on it
I think you are absolutely correct for the interpretation of the photon count :)
Hi all, I’m Camille Mellom here I guess
Hi everyone! Guess I’ll make an intro post to try to find some cool people and cool communities. In the real world I’m the head of research lab for a company in a university (hopefully the best of both world instead of the worse of both), and my research focuses on machine learning and robotics. Otherwise I like math, the environment, nature. I saw quite some communities in mander on nature but not so much math, machine learning, and robotics?
Outside of work nothing better than a good hike, a nice climbing session, or an evening playing video games :).