Tag Archives: AI

New Material For New Processor

Computers used to take up entire rooms. Today, a two-pound laptop can slide effortlessly into a backpack. But that wouldn’t have been possible without the creation of new, smaller processors — which are only possible with the innovation of new materials. But how do materials scientists actually invent new materials? Through experimentation, explains Sanket Deshmukh, an assistant professor in the chemical engineering department of Virginia Tech whose team’s recently published computational research might vastly improve the efficiency and costs savings of the material design process.

Deshmukh’s lab, the Computational Design of Hybrid Materials lab, is devoted to understanding and simulating the ways molecules move and interact — crucial to creating a new material. In recent years, materials scientists have employed machine learning, a powerful subset of artificial intelligence, to accelerate the discovery of new materials through computer simulations. Deshmukh and his team have recently published research in the Journal of Physical Chemistry Letters demonstrating a novel machine learning framework that trainson the fly,” meaning it instantaneously processes data and learns from it to accelerate the development of computational models. Traditionally the development of computational models are “carried out manually via trial-and-error approach, which is very expensive and inefficient, and is a labor-intensive task,” Deshmukh explained.

This novel framework not only uses the machine learning in a unique fashion for the first time,” Deshmukh said, “but it also dramatically accelerates the development of accurate computational models of materials.” “We train the machine learning model in a ‘reverse’ fashion by using the properties of a model obtained from molecular dynamics simulations as an input for the machine learning model, and using the input parameters used in molecular dynamics simulations as an output for the machine learning model,” said Karteek Bejagam, a post-doctoral researcher in Deshmukh’s lab and one of the lead authors of the study.

This new framework allows researchers to perform optimization of computational models, at unusually faster speed, until they reach the desired properties of a new material.

Source: https://vtnews.vt.edu/

Amazon to datamine the stars

Amazon.com is in talks with Chile to house and mine massive amounts of data generated by the country’s giant telescopes, which could prove fertile ground for the company to develop new artificial intelligence tools. The talks are aimed at fuelling growth in Amazon.com Inc’s cloud computing business in Latin America and boosting its data processing capabilities.

President Sebastian Pinera’s center-right government, which is seeking to wean Chile’s $325 billion economy from reliance on copper mining, announced last week it plans to pool data from all its telescopes onto a virtual observatory stored in the cloud, without giving a timeframe. The government talked of the potential for astrodata innovation, but did not give details.

Amazon executives have been holding discussions with the Chilean government for two years about a possible data center to provide infrastructure for local firms and the government to store information on the cloud. The talks have included discussion about the possibility of Amazon Web Services (AWS), hosting astrodata.

Jeffrey Kratz, AWS’s General Manager for Public Sector for Latin American, has confirmed the company’s interest in astrodata but said Amazon had no announcements to make at present. “Chile is a very important country for AWS,” he said in an email to Reuters. “We kept being amazed about the incredible work on astronomy and the telescopes, as real proof points on innovation and technology working together.” “The Chilean telescopes can benefit from the cloud by eliminating the heavy lifting of managing IT,” Kratz added.

Source: https://www.reuters.com/

AI creates 3D ‘digital heart’ to aid patient diagnoses

Armed with a mouse and computer screen instead of a scalpel and operating theater, cardiologist Benjamin Meder carefully places the electrodes of a pacemaker in a beating, digital heart.  Using this “digital twin” that mimics the electrical and physical properties of the cells in patient 7497’s heart, Meder runs simulations to see if the pacemaker can keep the congestive heart failure sufferer alivebefore he has inserted a knife.

A three-dimensional printout of a human heart is seen at the Heidelberg University Hospital (Universitaetsklinikum Heidelberg)

The digital heart twin developed by Siemens Healthineers, a German company is one example of how medical device makers are using artificial intelligence (AI) to help doctors make more precise diagnoses as medicine enters an increasingly personalized age.

The challenge for Siemens Healthineers and rivals such as Philips and GE Healthcare is to keep an edge over tech giants from Alphabet’s Google to Alibaba that hope to use big data to grab a slice of healthcare spending.

With healthcare budgets under increasing pressure, AI tools such as the digital heart twin could save tens of thousands of dollars by predicting outcomes and avoiding unnecessary surgery.

Source: https://www.healthcare.siemens.com/
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https://www.reuters.com/

Teaching a car how to drive itself in 20 minutes

Researchers from Wayve, a company founded by a team from the Cambridge University engineering department, have developed a neural network sophisticated enough to learn how to drive a car in 15 to 20 minutes using nothing but a computer and a single camera. The company showed off its robust deep learning methods last week in a company blog post showcasing the no-frills approach to driverless car development. Where companies like Waymo and Uber are relying on a variety of sensors and custom-built hardware, Wayve is creating the world’s first autonomous vehicles based entirely on reinforcement learning.

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The AI powering Wayve’s self-driving system is remarkable for its simplicity. It’s a four layer convolutional neural network (learn about neural networks here) that performs all of its processing on a GPU inside the car. It doesn’t require any cloud connectivity or use pre-loaded mapsWayve’s vehicles are early-stage level five autonomous. There’s a lot of work to be done before Wayve’s AI can drive any car under any circumstances. But the idea that driverless cars will require tens of thousands of dollars worth of extraneous hardware is taking a serious blow in the wake of the company’s amazing deep learning techniques. According to Wayve, these algorithms are only going to get smarter.

Source: https://wayve.ai/
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https://thenextweb.com/

Brain function partly replicated by nanomaterials

The brain requires surprisingly little energy to adapt to the environment to learn, make ambiguous recognitions, have high recognition ability and intelligence, and perform complex information processing.

The two key features of neural circuits are “learning ability of synapses” and “nerve impulses or spikes.” As brain science progresses, brain structure has been gradually clarified, but it is too complicated to completely emulate. Scientists have tried to replicate brain function by using simplified neuromorphic circuits and devices that emulate a part of the brain’s mechanisms.

Spontaneous spikes being similar to nerve impulses of neurons was generated from a POM/CNT complexed network

In developing neuromorphic chips to artificially replicate the circuits that mimic brain structure and function, the functions of generation and transmission of spontaneous spikes that mimic nerve impulses (spikes) have not yet been fully utilized.

A joint group of researchers from Kyushu Institute of Technology and Osaka University studied current rectification control in junctions of various molecules and particles absorbed on single-walled carbon nanotube (SWNT), using conductive atomic force microscopy (C -AFM), and discovered that a negative differential resistance was produced in polyoxometalate (POM) molecules absorbed on SWNT. This suggests that an unstable dynamic non-equilibrium state occurs in molecular junctions.

In addition, the researchers created extremely dense, random SWNT/POM network molecular neuromorphic devices, generating spontaneous spikes similar to nerve impulses of neurons.

POM consists of metal atoms and oxygen atoms to form a 3-dimensional framework. Unlike ordinary organic molecules, POM can store charges in a single molecule. In this study, it was thought that negative differential resistance and spike generation from the network were caused by nonequilibrium charge dynamics in molecular junctions in the network.

Thus, the joint research group led by Megumi Akai-Kasaya conducted simulation calculations of the random molecular network model complexed with POM molecules, which are able to store electric charges, replicating spikes generated from the random molecular network.  They also demonstrated that this molecular model would very likely become a component of reservoir computing devices. Reservoir computing is anticipated as next-generation artificial intelligence (AI). Their research results were published in Nature Communications.

The significance of our study is that a portion of brain function was replicated by nano-molecular materials. We demonstrated the possibility that the random molecular network itself can become neuromorphic AI,” says lead author Hirofumi Tanaka.

Source: http://resou.osaka-u.ac.jp/

Carlos Ghosn: “Driverless Cars Similar To Antibiotics”

Carlos Ghosn, CEO of the Renault-Nissan-Mitsubishi Alliance car maker (ranked 1 in the world),  has detailed the impact of the driverless car on human daily lives (Interview at the French TV BFM). There are between 1,3 million and 1,4 million death on roads every year in the world. The driverless car will eliminate 90% of the fatal accidents.

 “We are five years from safe, driverless cars for all“, adds Ghosn. “Driverless cars impact will be similar to the discovery of antibiotics“.

Famously given the moniker “Le Cost Killer” for his work transforming two ailing brands into one profit-making success story, Carlos Ghosn has achieved celebrity status in the car industry — and was once even portrayed as a superhero in a Japanese comic book.

Today the auto industry is experiencing a paradigm shift with the growth of the global electric vehicle (EV) market, as well as the vast potential offered by disruptive new areas like the autonomously-driven vehicle, using massively Artificial Intelligence. Despite the challenge of staying competitive and profitable in this changing environment, the Brazilian-born 64-year old believes the brands under his watch are already in pole position — and plan to stay there. But he has to stay vigilant and is aware of the dangers, acknowledging that businesses are pushing hard for driverless vehicles. “Amazon, Alibaba, Uberwhy are they interested in this? It’s very simple. The driver is the biggest cost they have — you make a quick calculation about a car running 24-7 for a month: the electricity bill is about $250 a month; the lease of the car is $300; plus three drivers, since you’re running for 24 hours a day, are going to cost you $15,000 per month.  So getting rid of the driver is a 90% reduction in costs.

That’s why Uber, DiDi all want to be the first to have this … because if my competitor gets this before me, I’m dead.”

https://www.forbes.com/

Driverless Taxi Service in US and France By The End Of The Year

The City of Lyon in France, will operate a regular cab service by the end of this year, using driverless electric vehicles from the french company Navya. As a pioneer and specialist in the autonomous vehicle market, Navya has conceived, developed and produced the Autonom Cab, the very first autonomous, personalized and shared mobility solution. The cab was designed from the outset to be autonomous, just like all the vehicles in the Autonom range, meaning that there is no cockpit, steering wheel nor pedals.

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At the heart of the smart city, Autonom Cab provides an intelligent transport service for individual trips in urban centers. Able to carry 1 to 6 passengers, The driverless taxi is a fluid, continuous and effective solution that answers user expectations in terms of service before, during and after their trip. Available as either a private or shared service, Autonom Cab places an emphasis on conviviality and comfort. On board, passengers can for example choose to work, benefiting from fully connected technology, or partake in an interactive cultural visit of the city. They can also choose a playlist, or buy their cinema or museum tickets.

As well,  the american company Waymo says that their self-driving car service will begin operations by the end of the year in Phoenix, Arizona. Waymo is a subsidiary of Alphabet, the parent company of Google, and the CEO John Krafcik said engineers at both companies were hard at work on the AI backing their self-driving cars.

People will be able to download a Waymo app and secure rides on autonomous vehicles through it, with no driver present, Krafcik said. Waymo has been operating autonomous vehicles on the roads of Phoenix since October, and is one of the first companies to do so in the US. Originally, Waymo was a part of Google before it was spun off into its own company under the Alphabet umbrella. Despite the separation, members of Google‘s Brain team have helped Waymo engineers by beefing up the neural networks underpinning the AI operating the vehicles.

Source: http://navya.tech/
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https://www.techrepublic.com/

Artificial Intelligence System Detects Guns On Videos

Scientists from the University of Granada (UGR) in Spain designed a computer system, based on new artificial intelligence techniques, that automatically detects in real time when a subject in a video draws a gun.

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Their work, pioneering on a global scale, has numerous practical applications, from improving security in airports and malls, for example, toautomatically controlling violent content in which handguns appear in videos uploaded on social networks such as Facebook, Youtube or Twitter, or classifying public videos on the internet that have handguns. The researchers tested their system with movies like Pulp Fiction, Mission Impossibleand James Bond

Francisco Herrera Triguero, Roberto Olmos and Siham Tabik, researchers in the Department of Computational and Artificial Intelligence Sciences at the UGR, developed this work. Its relevance was reflected when the MIT Technology Review, an e-journal of the renowned technology-oriented university, selected it as one of the five most stimulating articles of the week worldwide.

Source: https://canal.ugr.es/