Lifeboat Foundation

If you are interested in artificial general intelligence (AGI), then I have a panel discussion to recommend. My friend, David Wood, has done a masterful job of selecting three panelists with deep insight into possible regulation of AGI. One of the panelists was my friend, Dan Faggella, who was eloquent and informative as usual. For this session of the London Futurists, David Wood selected two other panelists with significantly different opinions on how to properly restrain AGI.

An artificial general intelligence (AGI), by one definition, is an agent that requires less information than any other to make an accurate prediction. It is arguable that the general reinforcement learning agent AIXI not only met this definition, but was the only mathematical formalism to do so. Though a significant result, AIXI was incomputable and its performance subjective. This paper proposes an alternative formalism of AGI which overcomes both problems. Formal proof of its performance is given, along with a simple implementation and experimental results that support these claims.

Here are some things I would expect any AGI to be able to do:…

Epistemic status: trying to feel out the shape of a concept and give it an appropriate name. Trying to make explicit some things that I think exist implicitly in many people’s minds. This post makes truth claims, but its main goal is to not to convince you that they are true.

One of the biggest challenges in a World Building competition that asked teams to imagine a positive future with superintelligent AI: Make it plausible.

Today we’re going to shine some light on Lumen, the fully dynamic global illumination and reflections system featured in Unreal Engine 5.

Our latest tech blog… See more.

Continue reading “Unreal Engine 5 goes all-in on dynamic global illumination with Lumen” »

The mainstream approach to driverless cars is slow and difficult. These startups think going all-in on AI will get there faster.

Company expects its robots to be doing your household chores in a decade.

Researchers at Meta’s Artificial Intelligence Research Lab (Facebook) in the U.S. and at the University of Twente’s Neuromechanical Modelling and Engineering Lab in the Netherlands (led by Prof.dr.ir Massimo Sartori), have co-developed the open-source framework MyoSuite, which combines advanced musculoskeletal models with advanced artificial intelligence (AI). The AI-powered digital models in MyoSuite can learn to execute complex movements and interactions with assistive robots, that would otherwise require long experimentations on real human subjects.

Modeling and simulation are now as important to human health technologies as they have been for the advancement of modern automotive industry. Prof. Massimo Sartori: “If we could predict the outcome of a robotic therapy beforehand, then we could optimize it for a patient and deliver a truly personalized and cost-effective treatment.”

MyoSuite supports the co-simulation of AI-powered musculoskeletal systems physically interacting with assistive robots such as exoskeletons. With MyoSuite you can simulate biological phenomena, e.g., muscle fatigue, muscle sarcopenia, tendon tear and tendon reaffirmation. Moreover, you can simulate how assistive robots could be designed and controlled to restore movement following impairment.

Predicting it now. 2030s there will be Tons of this, and not just chat bots of dead people, but making them seem alive, 24/7 in VR world meta whatever. There will probably be shops that cater to this and try and make it as close and realistic as possible, will probably mostly be underground.

The recent case of a man making a chatbot based on his deceased fiancée raises ethical questions: Is this something we want? property= description.

Research by Dr. Silvia de Santis and Dr. Santiago Canals, both from the Institute of Neurosciences UMH-CSIC (Alicante, Spain), has made it possible to visualize for the first time and in great detail brain inflammation using diffusion-weighted Magnetic Resonance Imaging. This detailed “X-ray” of inflammation cannot be obtained with conventional MRI, but requires data acquisition sequences and special mathematical models. Once the method was developed, the researchers were able to quantify the alterations in the morphology of the different cell populations involved in the inflammatory process in the brain.

An innovative strategy developed by the researchers has made possible this important breakthrough, which is published today in the journal Science Advances and which may be crucial to change the course of the study and treatment of neurodegenerative diseases.

The research demonstrates that diffusion-weighted MRI can noninvasively and differentially detect the activation of microglia and astrocytes, two types of brain cells that are at the basis of neuroinflammation and its progression.