Blog

Archive for the ‘information science’ category: Page 102

Dec 30, 2022

Michael Levin: Anatomical decision-making

Posted by in categories: biotech/medical, evolution, information science, life extension, neuroscience

Anatomical decision-making by cellular collectives: Bioelectrical pattern memories, regeneration, and synthetic living organisms.

A key question for basic biology and regenerative medicine concerns the way in which evolution exploits physics toward adaptive form and function. While genomes specify the molecular hardware of cells, what algorithms enable cellular collectives to reliably build specific, complex, target morphologies? Our lab studies the way in which all cells, not just neurons, communicate as electrical networks that enable scaling of single-cell properties into collective intelligences that solve problems in anatomical feature space. By learning to read, interpret, and write bioelectrical information in vivo, we have identified some novel controls of growth and form that enable incredible plasticity and robustness in anatomical homeostasis. In this talk, I will describe the fundamental knowledge gaps with respect to anatomical plasticity and pattern control beyond emergence, and discuss our efforts to understand large-scale morphological control circuits. I will show examples in embryogenesis, regeneration, cancer, and synthetic living machines. I will also discuss the implications of this work for not only regenerative medicine, but also for fundamental understanding of the origin of bodyplans and the relationship between genomes and functional anatomy.

Dec 29, 2022

Big Data, Machine Learning, and AI in Portfolio Management

Posted by in categories: information science, robotics/AI

https://www.youtube.com/watch?v=03IE2f8giBw

BlackRock’s Kevin Franklin explains how investors get comfortable with applying these tools to money management.

For all Morningstar videos: http://www.morningstar.com/articles/archive/467/us-videos.html

Dec 28, 2022

“A Big Deal” — Physicists Solve 20-Year Mystery of Stable Chiral Nanostructures

Posted by in categories: computing, information science, nanotechnology, physics

Researchers have finally succeeded in building a long-sought nanoparticle structure, opening the door to new materials with special properties.

Alex Travesset does not have a sparkling research lab stocked with the most cutting-edge instruments for probing new nanomaterials and measuring their unique properties.

Instead of using traditional laboratory instruments, Alex Travesset, a professor of physics and astronomy at Iowa State University and an affiliate of the U.S. Department of Energy’s Ames National Laboratory, relies on computer models, equations, and figures to understand the behavior of new nanomaterials.

Dec 26, 2022

Is AI Translation the Future of Video Games?

Posted by in categories: cybercrime/malcode, education, Elon Musk, information science, mobile phones, robotics/AI, space

In the midst of the Anti AI Art movement and the ever evolving complexity of the algorithms they are rallying against, this video essay discusses current flaws and future potential of AI Translation technology within Retro Game Emulation. Through rigorous testing of 3 games that never got localizations or fan translations (Tokimeki Memorial 2, Sakura Wars 2 & Boku No Natsuyasami 2), we will see how well Retroarch and ZTranslate’s AI Translator works for the average player. We will also discuss the ways in which this technology could one day be used in more formal localisations by professional teams, and wel will come to understand the nuances of the AI debate.

#AI #FanTranslation #Emulation.

Continue reading “Is AI Translation the Future of Video Games?” »

Dec 25, 2022

The Universe May Be More Unstable Than You Think

Posted by in categories: information science, particle physics

In particle physics, particles are constantly interacting and interfering with all the other kinds of particles, but the strength of those interactions depend on the particle masses. So, when we try to evaluate anything involving the Higgs boson – like, say, its ability to maintain the separation between the electromagnetic and weak nuclear forces – we also need to pay attention to how the other particles will interfere with that effort. And since the top quark is handily the biggest of the bunch (the next largest, the bottom quark, weighs a mere 5 GeV) it’s essentially the only other particle we need to care about.

When physicists first calculated the stability of the universe, as determined by the Higgs boson’s ability to maintain the separation of the electroweak force, they didn’t know the mass of either the Higgs itself or the top quark. Now we do: The top quark weighs around 175 GeV, and the Higgs around 125 GeV.

Plugging those two numbers into the stability equations reveals that the universe is… metastable. This is different than stable, which would mean that there’s no chance of the universe splitting apart instantly, but also different than unstable, which would mean it already happened.

Dec 23, 2022

OpenAI ChatGPT: The Future Is Here!

Posted by in categories: habitats, information science, physics, robotics/AI

❤️ Check out Weights & Biases and sign up for a free demo here: https://wandb.com/papers.
❤️ Their mentioned post is available here: http://wandb.me/RLHF-OpenAI

Try #ChatGPT!
https://chat.openai.com/
https://openai.com/blog/chatgpt/

Continue reading “OpenAI ChatGPT: The Future Is Here!” »

Dec 21, 2022

Study shows how machine learning could predict rare disastrous events, like earthquakes or pandemics

Posted by in categories: biotech/medical, information science, robotics/AI

PROVIDENCE, R.I. [Brown University] — When it comes to predicting disasters brought on by extreme events (think earthquakes, pandemics or “rogue waves” that could destroy coastal structures), computational modeling faces an almost insurmountable challenge: Statistically speaking, these events are so rare that there’s just not enough data on them to use predictive models to accurately forecast when they’ll happen next.

But a team of researchers from Brown University and Massachusetts Institute of Technology say it doesn’t have to be that way.

In a new study in Nature Computational Science, the scientists describe how they combined statistical algorithms — which need less data to make accurate, efficient predictions — with a powerful machine learning technique developed at Brown and trained it to predict scenarios, probabilities and sometimes even the timeline of rare events despite the lack of historical record on them.

Dec 20, 2022

AI Art is NOT Theft

Posted by in categories: information science, robotics/AI

The term AI Art refers to artwork created by computers and algorithms. AI Art is not theft as it does not involve taking or copying someone else’s work without permission. AI Art is an entirely new form of creativity that involves the use of artificial intelligence to create unique and original works of art.

▼ Link(s) From Today’s Video:

Continue reading “AI Art is NOT Theft” »

Dec 20, 2022

Signal processing algorithms improve turbulence in free-space optic tests

Posted by in categories: information science, internet

New signal-processing algorithms have been shown to mitigate the impact of turbulence in free-space optical experiments, potentially bringing “free space” internet a step closer to reality.

The team of researchers, from Aston University’s Aston Institute of Photonic Technologies and Glasgow University, used commercially available photonic lanterns, a commercial transponder, and a to emulate turbulence. By applying a successive interference cancelation algorithm, they achieved record results.

The findings are published in the Journal of Lightwave Technology.

Dec 19, 2022

Autonomous Estimation of High-Dimensional Coulomb Diamonds from Sparse Measurements

Posted by in categories: information science, mapping, quantum physics, robotics/AI

In spin-based quantum processors, each quantum dot of a qubit is populated by exactly one electron, which requires careful tuning of each gate voltage such that it lies inside the charge-stability region (the “Coulomb diamond’‘) associated with the dot array. However, mapping the boundary of a multidimensional Coulomb diamond by traditional dense raster scanning would take years, so the authors develop a sparse acquisition technique that autonomously learns Coulomb-diamond boundaries from a small number of measurements. Here we have hardware-triggered line searches in the gate-voltage space of a silicon quadruple dot, with smart search directions proposed by an active-learning algorithm.