A Carnegie Mellon team used an automated system and machine-learning software to develop fast-charging electrolytes that outperformed a standard one.
face_with_colon_three circa 2021.
Think about where our energy comes from: drilling rigs and smokestacks, windmills and solar panels. Lithium-ion battery packs might even come to mind.
We probably don’t think about the farms that comprise over one-third of Earth’s total land area. But farms can also be an energy source. Barcelona-based battery company Bioo is generating electricity from the organic matter in soil and creating biological batteries that can power agricultural sensors, a growing 1.36 billion dollar global market.
Continue reading “How biological batteries can generate renewable energy from soil” »
face_with_colon_three circa 2021.
Microsoft has developed an AI program called BugLab, which can help you find and fix bugs in your code. Here’s how it works!
It took scientists 375 years to discover the eighth continent of the world, which had been hiding in plain sight all along. But mysteries still remain.
Improving the efficiency of algorithms for fundamental computations is a crucial task nowadays as it influences the overall pace of a large number of computations that might have a significant impact. One such simple task is matrix multiplication, which can be found in systems like neural networks and scientific computing routines. Machine learning has the potential to go beyond human intuition and beat the most exemplary human-designed algorithms currently available. However, due to the vast number of possible algorithms, this process of automated algorithm discovery is complicated. DeepMind recently made a breakthrough discovery by developing AplhaTensor, the first-ever artificial intelligence (AI) system for developing new, effective, and indubitably correct algorithms for essential operations like matrix multiplication. Their approach answers a mathematical puzzle that has been open for over 50 years: how to multiply two matrices as quickly as possible.
AlphaZero, an agent that showed superhuman performance in board games like chess, go, and shogi, is the foundation upon which AlphaTensor is built. The system expands on AlphaZero’s progression from playing traditional games to solving complex mathematical problems for the first time. The team believes this study represents an important milestone in DeepMind’s objective to improve science and use AI to solve the most fundamental problems. The research has also been published in the established Nature journal.
Matrix multiplication has numerous real-world applications despite being one of the most simple algorithms taught to students in high school. This method is utilized for many things, including processing images on smartphones, identifying verbal commands, creating graphics for video games, and much more. Developing computing hardware that multiplies matrices effectively consumes many resources; therefore, even small gains in matrix multiplication efficiency can have a significant impact. The study investigates how the automatic development of new matrix multiplication algorithms could be advanced by using contemporary AI approaches. In order to find algorithms that are more effective than the state-of-the-art for many matrix sizes, AlphaTensor further leans on human intuition. Its AI-designed algorithms outperform those created by humans, which represents a significant advancement in algorithmic discovery.
New to nerfstudio? Here we walk you through a step-by-step process on how to turn your favorite capture into a trendy 3D video in minutes.
Github: github.com/nerfstudio-project/nerfstudio.
Discord: discord.gg/uMbNqcraFc.
Twitter: @nerfstudioteam.
❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers.
📝 My paper “The flow from simulation to reality” with clickable citations is available here:
https://www.nature.com/articles/s41567-022-01788-5
📝 Read it for free here! https://rdcu.be/cWPfD
Continue reading “Wow, A Simulation That Looks Like Reality! 🤯” »
Science-fiction author Neal Stephenson predicted cryptocurrencies and virtual worlds — even coining the term metaverse — in his 1992 novel Snow Crash. Now, 30 years later, he is combining the two ideas by launching a blockchain-powered open metaverse. It is a move that sets him against big tech firms with their own metaverse plans, so why is he doing it and what even is an open metaverse?
Developers have pushed various versions of the metaverse for decades, but nothing has stuck.
Lamina1 was contacted for comment.
Continue reading “Sci-fi author Neal Stephenson wants to build a metaverse open to all” »
Circa 2015 face_with_colon_three
From driving water wheels to turning turbines, waterhas been used as the prime mover of machinery and the powerhouse of industry for many centuries. In ancient times, the forces of flowing water were even harnessed to power the first rudimentaryclocks. Now, engineers at Stanford University have created the world’s first water-operated computer. Using magnetized particles flowing through a micro-miniature network ofchannels, the machine runs like clockwork and is claimed to be capable ofperforming complex logical operations.
Continue reading “Engineers create a computer with a water droplet processor” »
Circa 2014 face_with_colon_three
A liquid hard drive containing a suspension of nanoparticles could be used to store impressive amounts of data: 1 terabyte per tablespoon.
Researchers from the University of Michigan and New York University have been simulating wet information storage techniques which uses clusters of nanoparticles suspended in liquid. These clusters of particles can store more data than conventional computer bits which have just two storage states: 0 and 1. The clusters of particles work a bit like Rubik’s Cubes to reconfigure in different ways to represent different storage states. A 12-particle memory cluster connected to a central sphere can have almost eight million unique states, which is equivalent to 2.86 bytes of data.
Continue reading “Liquid hard drive could store 1TB data in a tablespoon” »
