(Reuters) — Rain Neuromorphics Inc., a startup designing chips that mimic the way the brain works and aims to serve companies using artificial intelligence (AI) algorithms, said on Wednesday it raised $25 million.
Gordon Wilson, CEO and co-founder of Rain, said that while most AI chips on the market today are digital, his company’s technology is analogue. Digital chips read 1s and 0s while analogue chips can decipher incremental information such as sound waves.
Omuterema AkhahendaAdmin.
🤔 if it is Optimus, can I buy it with Amazon Prime.
Wojtek TekOmuterema Akhahenda free delivery.
Alan LightAdmin.
More than just free delivery: self-delivery.
We should really come up with a new term for an autonomous robot that delivers itself this way. Probably some combination of the terms “auto” (for “self”) and “bot”.… See more.
Ron FriedmanJust when I thought I have enough Tesla stocks, it looks like I’ll buy more.
Denoising an image is a classical problem that researchers are trying to solve for decades. In earlier times, researchers used filters to reduce the noise in the images. They used to work fairly well for images with a reasonable level of noise. However, applying those filters would add a blur to the image. And if the image is too noisy, then the resultant image would be so blurry that most of the critical details in the image are lost.
There has to be a better way to solve this problem. As a result, I have implemented several deep learning architectures that far surpass the traditional denoising filters. In this blog, I will explain my approach step-by-step as a case study, starting from the problem formulation to implementing the state-of-the-art deep learning models, and then finally see the results.
Might there be a better way? Perhaps.
A new paper published on the preprint server arXiv describes how a type of algorithm called a “hypernetwork” could make the training process much more efficient. The hypernetwork in the study learned the internal connections (or parameters) of a million example algorithms so it could pre-configure the parameters of new, untrained algorithms.
The AI, called GHN-2, can predict and set the parameters of an untrained neural network in a fraction of a second. And in most cases, the algorithms using GHN-2’s parameters performed as well as algorithms that had cycled through thousands of rounds of training.
Hibernating astronauts could be the best way to save mission costs, reduce the size of spacecraft by a third and keep crew healthy on their way to Mars. An ESA-led investigation suggests that human hibernation goes beyond the realm of science-fiction and may become a game-changing technique for space travel.
When packing for a return flight to the Red Planet, space engineers account for around two years’ worth of food and water for the crew.
“We are talking about 30 kg per astronaut per day, and on top of that we need to consider radiation as well as mental and physiological challenges,” explains Jennifer Ngo-Anh, ESA research and payload coordinator of Human and Robotic Exploration and one of the authors of the paper that links biology to engineering.
Elon Musk has always said that Neuralink, the company he created in 2016 to build brain-computer interfaces, would do amazing things: Eventually, he says, it aims to allow humans to interact seamlessly with advanced artificial intelligence through thought alone. Along the way, it would help to cure people with spinal cord injuries and brain disorders ranging from Parkinson’s to schizophrenia.
Now the company is approaching a key test: a human clinical trial of its brain-computer interface (BCI). In December, Musk told a conference audience that “we hope to have this in our first humans” in 2022. In January, the company posted a job listing for a clinical trial director, an indication that it may be on track to meet Musk’s suggested timeline.
Musk has put the startup under unrelenting pressure to meet unrealistic timelines, these former employees say. “There was this top-down dissatisfaction with the pace of progress even though we were moving at unprecedented speeds,” says one former member of Neuralink’s technical staff, who worked at the company in 2019. “Still Elon was not satisfied.” Multiple staffers say company policy, dictated by Musk, forbade employees from faulting outside suppliers or vendors for a delay; the person who managed that relationship had to take responsibility for missed deadlines, even those outside their control.
Posted in robotics/AI
The machine-learning model could help scientists speed the development of new medicines.
This technique could help scientists better understand some biological processes that involve protein interactions, like DNA replication and repair; it could also speed up the process of developing new medicines.
“Deep learning is very good at capturing interactions between different proteins that are otherwise difficult for chemists or biologists to write experimentally. Some of these interactions are very complicated, and people haven’t found good ways to express them. This deep-learning model can learn these types of interactions from data,” says Octavian-Eugen Ganea, a postdoc in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and co-lead author of the paper.
Ganea’s co-lead author is Xinyuan Huang, a graduate student at ETH Zurich. MIT co-authors include Regina Barzilay, the School of Engineering Distinguished Professor for AI and Health in CSAIL, and Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering in CSAIL and a member of the Institute for Data, Systems, and Society. The research will be presented at the International Conference on Learning Representations.
Machine-learning model could help scientists speed the development of new medicines.
The AI nanny is here! In a new feat for science, robots and AI can now be paired to optimise the creation of human life. In a Matrix-esque reality, robotics and artificial intelligence can now help to develop babies with algorithms and artificial wombs.
Reported by South China Morning Post, Chinese scientists in Suzhou have developed the new technology. However, there are worries surrounding the ethics of actually artificially growing human babies.
This video covers the world in 2080 and its future technologies. Watch this next video about the world in 2070: https://bit.ly/3nYXvjf.
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SOURCES:
• https://www.futuretimeline.net.
• The Future of Humanity (Michio Kaku): https://amzn.to/3Gz8ffA
• The Singularity Is Near: When Humans Transcend Biology (Ray Kurzweil): https://amzn.to/3ftOhXI
• Physics of the Future (Michio Kaku): https://amzn.to/33NP7f7
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