Tag Archives: Artificial Intelligence

This Person Does Not exist

With the help of artificial intelligence, you can manipulate video of public figures to say whatever you like — or now, create images of people’s faces that don’t even exist. You can see this in action on a website called thispersondoesnotexist.com. It uses an algorithm to spit out a single image of a person’s face, and for the most part, they look frighteningly realHit refresh in your browser, and the algorithm will generate a new face. Again, these people do not exist.

The website is the creation of software engineer Phillip Wang, and uses a new AI algorithm called StyleGAN, which was developed by researchers at NvidiaGAN, or Generative Adversarial Networks, is a concept within machine learning which aims to generate images that are indistinguishable from real ones. You can train GANs to remember human faces, as well bedrooms, cars, and cats, and of course, generate images of them.

Wang explained that he created the site to create awareness for the algorithm, and chose facesbecause our brains are sensitive to that kind of image.”  He added that it costs $150 a month to hire out the server, as he needs a good amount of graphical power to run the website.

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It also started off as a personal agenda mainly because none of my friends seem to believe this AI phenomenon, and I wanted to convince them,” Wang said. “This was the most shocking presentation I could send them. I then posted it on Facebook and it went viral from there.

I think eventually, given enough data, a big enough neural [network] can be teased into dreaming up many different kinds of scenarios,” Wang added.

Source: https://thispersondoesnotexist.com/
AND
https://mashable.com/

Ai-Da The Artist Robot

A British arts engineering company says it has created the world’s first AI robot capable of drawing people who pose for it. The humanoid called Ai-Da can sketch subjects using a microchip in her eye and a pencil in her robotic hand – coordinated by AI processes and algorithmsAi-Da‘s ability as a life-like robot to draw and paint ultra-realistic portraits from sight has never been achieved before, according to the designers in Cornwall. It is the brainchild of art impresario and galleries Aidan Meller.

Named after Ada Lovelace , the first female computer programmer in the world, Ai-Da the robot has been designed and built by Cornish robotics company Engineered Arts who make robots for communication and entertainment.

In April 2018, Engineered Arts created an ultra-realistic robot to promote the Westworld TV show.

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Pioneering a new AI art movement, we are excited to present Ai-Da, the first professional humanoid artist, who creates her own art, as well as being a performance artist. “As an AI robot, her artwork uses AI processes and algorithms. “The work engages us to think about AI and technological uses and abuses in the world today.” explains Aidan Meller.

Professors and post-Phd students at Oxford University and Goldsmiths are providing Ai-Da with the programming and creative design for her art work. While students at Leeds University are custom designing and programming a bionic arm to create her art work.

Ai-Da has a “RoboThespian” body , featuring an expressive range of movements and she has the ability to talk and respond to questions. The robot also has a “Mesmer” head, featuring realistic silicone skin, 3D printed teeth and gums, integrated eye cameras, as well as hair.

Source: http://fortune.com/
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https://www.mirror.co.uk/

Facial Recognition And AI Identify 90% Of Rare Genetic Disorders

A facial recognition scan could become part of a standard medical checkup in the not-too-distant future. Researchers have shown how algorithms can help identify facial characteristics linked to genetic disorders, potentially speeding up clinical diagnoses.

In a study published this month in the journal Nature Medicine, US company FDNA published new tests of their software, DeepGestalt. Just like regular facial recognition software, the company trained their algorithms by analyzing a dataset of faces. FDNA collected more than 17,000 images covering 200 different syndromes using a smartphone app it developed named Face2Gene.

Rare genetic disorders are collectively common, affecting 8 percent of the population

In two first tests, DeepGestalt was used to look for specific disorders: Cornelia de Lange syndrome and Angelman syndrome. Both of these are complex conditions that affect intellectual development and mobility. They also have distinct facial traits, like arched eyebrows that meet in the middle for Cornelia de Lange syndrome, and unusually fair skin and hair for Angelman syndrome.

When tasked with distinguishing between pictures of patients with one syndrome or another, random syndrome, DeepGestalt was more than 90 percent accurate, beating expert clinicians, who were around 70 percent accurate on similar tests. When tested on 502 images showing individuals with 92 different syndromes, DeepGestalt identified the target condition in its guess of 10 possible diagnoses more than 90 percent of the time.

Source: https://www.theverge.com

Artificial Synapses Made from Nanowires

Scientists from Jülich together with colleagues from Aachen and Turin have produced a memristive element made from nanowires that functions in much the same way as a biological nerve cell. The component is able to both save and process information, as well as receive numerous signals in parallel. The resistive switching cell made from oxide crystal nanowires is thus proving to be the ideal candidate for use in building bioinspired “neuromorphic” processors, able to take over the diverse functions of biological synapses and neurons.

Image captured by an electron microscope of a single nanowire memristor (highlighted in colour to distinguish it from other nanowires in the background image). Blue: silver electrode, orange: nanowire, yellow: platinum electrode. Blue bubbles are dispersed over the nanowire. They are made up of silver ions and form a bridge between the electrodes which increases the resistance.

Computers have learned a lot in recent years. Thanks to rapid progress in artificial intelligence they are now able to drive cars, translate texts, defeat world champions at chess, and much more besides. In doing so, one of the greatest challenges lies in the attempt to artificially reproduce the signal processing in the human brain. In neural networks, data are stored and processed to a high degree in parallel. Traditional computers on the other hand rapidly work through tasks in succession and clearly distinguish between the storing and processing of information. As a rule, neural networks can only be simulated in a very cumbersome and inefficient way using conventional hardware.

Systems with neuromorphic chips that imitate the way the human brain works offer significant advantages. Experts in the field describe this type of bioinspired computer as being able to work in a decentralised way, having at its disposal a multitude of processors, which, like neurons in the brain, are connected to each other by networks. If a processor breaks down, another can take over its function. What is more, just like in the brain, where practice leads to improved signal transfer, a bioinspired processor should have the capacity to learn.

With today’s semiconductor technology, these functions are to some extent already achievable. These systems are however suitable for particular applications and require a lot of space and energy,” says Dr. Ilia Valov from Forschungszentrum Jülich. “Our nanowire devices made from zinc oxide crystals can inherently process and even store information, as well as being extremely small and energy efficient,” explains the researcher from Jülich’s Peter Grünberg Institute.

Source: http://www.fz-juelich.de/

AI and Big Data To Fight Eye Diseases

In future, it will be possible to diagnose diabetes from the eye using automatic digital retinal screening, without the assistance of an ophthalmologist‘: these were the words used by Ursula Schmidt-Erfurth, Head of MedUni Vienna‘s Department of Ophthalmology and Optometrics. The scientist has opened the press conference about the ART-2018 Specialist Meeting on new developments in retinal therapy. The automatic diabetes screening, has been recently implemented at MedUni Vienna.
Patients flock to the Department to undergo this retinal examination to detect any diabetic changes. It takes just a few minutes and is completely non-invasive

Essentially this technique can detect all stages of diabetic retinal diseasehigh-resolution digital retinal images with two million pixels are taken and analyzed within seconds – but Big Data offers even more potential: nowadays it is already possible to diagnose an additional 50 other diseases in this way. Diabetes is just the start. And MedUni Vienna is among the global leaders in this digital revolution.

The Division of Cardiology led by Christian Hengstenberg within the Department of Medicine II is working on how digital retinal analysis can also be used in future for the early diagnosis of cardiovascular diseases.

This AI medicine is ‘super human’,” emphasizes Schmidt-Erfurth. “The algorithms are quicker and more accurate. They can analyze things that an expert cannot detect with the naked eye.” And yet the commitment to Big Data and Artificial Intelligence is not a plea for medicine without doctors, which some experts predict for the not-to-distant future. “What we want are ‘super doctors’, who are able to use the high-tech findings to make the correct, individualized therapeutic decision for their patients, in the spirit of precision medicine, rather than leaving patients on their own.”

However, it is not only in the diagnosis of diseases that Artificial Intelligence and Big Data, plus virtual reality, provide better results. “We are already performing digitized operations with support from Artificial Intelligence. This involves projecting a virtual and precise image of the area of the eye being operated on onto a huge screen – and the surgeon then performs the operation with a perfect viewon screen” as it were, while actually operating on the patient with a scalpel.”

Source: https://www.news-medical.net/

AI Robot Presents TV News In China

China’s state news agency Xinhua this week introduced the newest members of its newsroom: AI anchors who will reporttirelessly” all day every day, from anywhere in the country. Chinese viewers were greeted with a digital version of a regular Xinhua news anchor named Qiu Hao. The anchor, wearing a red tie and pin-striped suit, nods his head in emphasis, blinking and raising his eyebrows slightly.

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Not only can I accompany you 24 hours a day, 365 days a year. I can be endlessly copied and present at different scenes to bring you the news,” he says. Xinhua also presented an English-speaking AI, based on another presenter, who adds: “The development of the media industry calls for continuous innovation and deep integration with the international advanced technologies … I look forward to bringing you brand new news experiences.”

Developed by Xinhua and the Chinese search engine, Sogou, the anchors were developed through machine learning to simulate the voice, facial movements, and gestures of real-life broadcasters, to present a “a lifelike image instead of a cold robot,” according to Xinhua.

Source: https://www.theguardian.com/

AI Lie Detectors Could Reach 85% Accuracy

It’s already nerve-wracking answering questions at the border, and some ports in the European Union are taking it to another, kinda worrying level. They’re installing an artificial intelligence-powered system called iBorderCtrl, which aims to speed up the processing of travellers, but also to determine if they’re lying. A six-month trial will take place at four border crossing points in Hungary, Greece and Latvia.

During pre-screening, users will upload their passport, visa, and proof of funds, then answer questions asked by a computer-generated border guard to a webcam. The system will analyse the user’s microexpressions to determine if they’re lying, and they’ll be flagged as either low or high risk. People will be asked questions like “What’s in your suitcase?” and “If you open the suitcase and show me what is inside, will it confirm that your answers were true?” For those who pass the test, they’ll receive a QR code that will let them pass through. If there’s additional concern, their biometric data will be taken, and be handed off to a human agent who will assess the case.

We’re employing existing and proven — as well as novel ones — to empower border agents to increase the accuracy and efficiency of border checks,” project coordinator George Boultadakis told the European Commission.  “iBorderCtrl’s system will collect data that will move beyond biometrics and on to biomarkers of deceit.

Of course, there’s the question of how accurate a system like this could be. iBorderCtrl is still in its early stages, and a team member told that early testing provided a 76 percent success rate, but believe this could be raised to 85 percent.

Source: https://mashable.com/

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/