New AI Can Detect Emotion With Radio Waves

THERE ARE NATIONAL SECURITY AND PRIVACY IMPLICATIONS TO AN EXPERIMENTAL UK NEURAL NETWORK THAT DECIPHERS HOW PEOPLE RESPOND TO EMOTIONAL STIMULI.

By PATRICK TUCKER 

Picture: military interrogators are talking to a local man they suspect of helping to emplace roadside bombs. The man denies it, even as they show him photos of his purported accomplices. But an antenna in the interrogation room is detecting the man’s heartbeat as he looks at the pictures. The data is fed to an AI, which concludes that his emotions do not match his words…

A UK research team is using radio waves to pick up subtle changes in heart rhythm and then, using an advanced AI called a neural network, understand what those signals mean — in other words, what the subject is feeling. It’s a breakthrough that one day might help, say, human-intelligence analysts in Afghanistan figure out who represents an insider threat.

The paper from a team out of Queen Mary University of London and published in the online journal PLOS ONE, demonstrates how to apply a neural network to decipher emotions gathered with transmitting radio antenna. A neural network functions in a manner somewhat similar to a human brain, with cells creating links to other cells in patterns that create memory, as opposed to more conventional methods such as machine learning, which employ straightforward statistical methods on data sets. 

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Using AI to measure the demand for parking space

by Fraunhofer-Gesellschaft

The growth in the number of cars parked in urban areas has a major impact on public space. One key consequence of this is that parking availability is less predictable, both in downtown and in quieter, residential areas, where people are having to spend more and more time looking for a free space. One remedy is to create a residential parking zone. To justify this measure, however, a municipality must first commission reports and carry out a survey of parking availability, both of which take time and cost money. To reduce this effort, the Fraunhofer Institute for Industrial Engineering IAO is now exploring the use of AI to analyze the demand for parking space. This pilot project is running in partnership with the City of Karlsruhe and is being conducted by the Research and Innovation Center for Cognitive Service Systems (KODIS), a branch of Fraunhofer IAO.

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RESEARCHERS: IT WOULD BE IMPOSSIBLE TO CONTROL SUPER AI

But is superintelligent AI really possible? Some experts are skeptical   

From the media release for a recent paper:

The idea of artificial intelligence overthrowing humankind has been talked about for many decades, and scientists have just delivered their verdict on whether we’d be able to control a high-level computer super-intelligence. The answer? Almost definitely not.

The catch is that controlling a super-intelligence far beyond human comprehension would require a simulation of that super-intelligence which we can analyse. But if we’re unable to comprehend it, it’s impossible to create such a simulation. 

DAVID NIELD, “CALCULATIONS SHOW IT’LL BE IMPOSSIBLE TO CONTROL A SUPER-INTELLIGENT AI” AT SCIENCE ALERT THE OPEN ACCESS RESEARCH STUDY IS HERE.

First, the idea that machines can design smarter machines should be treated with skepticism: maybe we are looking at a Robogeddon that can’t happen and a crowd of experts who need it to.

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AI plastering robot developed for construction sites

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Amid the ever-increasing use of artificial intelligence (AI) robots at construction sites, a new robot that can perform concrete plastering work on its own has been developed.

 Hyundai Engineering Co., a plant engineering affiliate of Hyundai Motor Group, announced on Wednesday that it had developed the nation’s first AI plastering robot that can flatten concrete floors by itself, adding that it has applied for related patents.

The AI plastering robot, which was developed in collaboration with Robo Block Systems, is a device that rotates two motors with four micro blades to flatten a floor infilled with concrete.

Compared to existing floor plastering machines, the newly-developed AI robot features a lighter design and a greater usability. By making use of an electric motor, the AI robot generates less noise compared to existing machines that use gasoline motors.

The patented ‘AI plastering robot floor flattening technology’ precisely measures the concrete-infilled floor space with a 3D scanner.

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What can AI learn from Human intelligence?

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At HAI’s fall conference, scholars discussed novel ways AI can learn from human intelligence – and vice versa.

Can we teach robots to generalize their learning? How can algorithms become more commonsensical? Can a child’s learning style influence AI?

Stanford Institute for Human-Centered Artificial Intelligence’s fall conference considered those and other questions to understand how to mutually improve and better understand artificial and human intelligence. The event featured the theme of “triangulating intelligence” among the fields of AI, neuroscience, and psychology to develop research and applications for large-scale impact.

HAI faculty associate directors Christopher Manning, a Stanford professor of machine learning, linguistics, and computer science, and Surya Ganguli, a Stanford associate professor of neurobiology, served as hosts and panel moderators for the conference, which was co-sponsored by Stanford’s Wu-Tsai Neurosciences Institute, Department of Psychology, and Symbolic Systems program.

Speakers described cutting-edge approaches—some established, some new—to create a two-way flow of insights between research on human and machine-based intelligence, for powerful application. Here are some of their key takeaways.

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How artificial intelligence may be making you buy things

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If you are getting told off for spending too much on wine, maybe you can blame it on artificial intelligence

The shopping lists we used to scribble on the back of an envelope are increasingly already known by the supermarkets we frequent.

Firstly via the loyalty cards we scan at checkouts, and more and more so from our online baskets, our shopping habits are no longer a secret.

But now more retailers are using AI (artificial intelligence) – software systems that can learn for themselves – to try to automatically predict and encourage our very specific preferences and purchases like never before.

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Satellites are mapping out every tree on earth using artificial intelligence

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Scientists have mapped 1.8 billion individual tree canopies across millions of kilometres of the Sahel and Sahara regions of West Africa. It is the first time ever that trees have been mapped in detail over such a large area.

So how was it possible? Researchers analysed a huge database of satellite images using artificial intelligence. They employed neural networks which are able to recognise objects, like trees, based on their shapes and colours.

To train it, the AI system was shown satellite images where trees had been manually traced. This involved lead author Martin Brandt going through the arduous process of identifying and labelling nearly 90,000 trees himself, beforehand.

From these images, the computer learnt what a tree looked like and could pick out individual canopies from the thousands of images in the database. Brandt says it would have taken millions of people years to identify the trees without the AI system.

In a review of the research, commissioned by Nature, scientists at New Mexico State University wrote that “it will soon be possible, with certain limitations, to map the location and size of every tree worldwide”

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The next generation of Artificial Intelligence

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AI legend Yann LeCun, one of the godfathers of AI

 The field of artificial intelligence moves fast. It has only been 8 years since the modern era of deep learning began at the 2012 ImageNet competition. Progress in the field since then has been breathtaking and relentless.

If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.

What will the next generation of artificial intelligence look like? Which novel AI approaches will unlock currently unimaginable possibilities in technology and business? This article highlights three emerging areas within AI that are poised to redefine the field—and society—in the years ahead. Study up now.

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This AI lyrics generator strings your random words into songs

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The system provides a new cure for songwriter’s block

 Could keyword lyrics provide a new cure for songwriter’s block?

Songwriter‘s block can be a problem for even the world’s most successful musicians. They can sometimes overcome it by taking breaks, seeking new forms of inspiration, or simply pushing through. And if none of that works, they could try out a new AI lyrics generator called keyword2lyrics.

The system was created by Mathi Gatti, a data scientist from Argentina, who told TNW he got the idea from his own songwriting struggles:

Sometimes I have a few ideas that I want to turn into a song, but I’m too lazy for that, so I thought it would be cool to make a program that generates lyrics from isolated keywords or phrases.

Gatti developed the tool by training OpenAI‘s GPT-2 language model on songs that Google lists when you search for “top artists 20th century” and “top artists 21st century,” and extracted keywords from them using a tool called yake.

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Biochip innovation combines AI and nanoparticles to analyze tumors

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Electrical engineers, computer scientists and biomedical engineers at the University of California, Irvine have created a new lab-on-a-chip that can help study tumor heterogeneity to reduce resistance to cancer therapies.

In a paper published today in Advanced Biosystems, the researchers describe how they combined artificial intelligence, microfluidics and nanoparticle inkjet printing in a device that enables the examination and differentiation of cancers and healthy tissues at the single-cell level.

“Cancer cell and tumor heterogeneity can lead to increased therapeutic resistance and inconsistent outcomes for different patients,” said lead author Kushal Joshi, a former UCI graduate student in biomedical engineering. The team’s novel biochip addresses this problem by allowing precise characterization of a variety of cancer cells from a sample.

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Robot reapers and AI: Just another day on the farm

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Pressures on agriculture have forced a technological revolution that are driving a new age of farming.

The agriculture industry has hit a turning point. Faced with a massive labor crunch and environmental instability, aggressive technology deployments are no longer an option for outliers in the sector, but a necessary and critical element in the success of the farm.

Enabling the transformation are a host of new developers, but also legacy companies with deep roots in agriculture. Smart technology from companies like John Deere, for example, is helping farmers to produce more with less and create more successful crops, all while having a smaller impact on the land and environment. In contrast to prevailing wisdom that you can’t teach an old dog new tricks, John Deere is employing AI and machine learning in its equipment to identify and enable needed actions at a scope and speed beyond human capacity, automating farming actions through smart robotics to enable consistent and precise actions at large scale, and providing precise, geospatial intelligence generated with machine technology and coupled with cloud-stored data to enable sustainable farming.

In other words, it’s like farming with technologies that might be more commonly associated with NASA than a tractor company. I caught up with Dr. Cristian Dima, Lead of Advanced Algorithms, John Deere Intelligent Solutions Group, to discuss the changes underway in the farming sector and what we can expect going forward.

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