AI – Page 55 – Impact Lab

AI, Artificial Intelligence, Machine Learning, Science & Technology News

The fourth generation of AI is here, and it’s called ‘Artificial Intuition’

September 16, 2020

Artificial Intelligence (AI) is one of the most powerful technologies ever developed, but it’s not nearly as new as you might think. In fact, it’s undergone several evolutions since its inception in the 1950s. The first generation of AI was ‘descriptive analytics,’ which answers the question, “What happened?” The second, ‘diagnostic analytics,’ addresses, “Why did it happen?” The third and current generation is ‘predictive analytics,’ which answers the question, “Based on what has already happened, what could happen in the future?”

While predictive analytics can be very helpful and save time for data scientists, it is still fully dependent on historic data. Data scientists are therefore left helpless when faced with new, unknown scenarios. In order to have true “artificial intelligence,” we need machines that can “think” on their own, especially when faced with an unfamiliar situation. We need AI that can not just analyze the data it is shown, but express a “gut feeling” when something doesn’t add up. In short, we need AI that can mimic human intuition. Thankfully, we have it.

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AI, Artificial Intelligence, Microsoft, Science & Technology News, Video

AI researchers use heartbeat detection to identify deepfake videos

September 12, 2020

Facebook and Twitter earlier this week took down social media accounts associated with the Internet Research Agency, the Russian troll farm that interfered in the U.S. presidential election four years ago, that had been spreading misinformation to up to 126 million Facebook users. Today, Facebook rolled out measures aimed at curbing disinformation ahead of Election Day in November. Deepfakes can make epic memes or put Nicholas Cage in every movie, but they can also undermine elections. As threats of election interference mount, two teams of AI researchers have recently introduced novel approaches to identifying deepfakes by watching for evidence of heartbeats.

Existing deepfake detection models focus on traditional media forensics methods, like tracking unnatural eyelid movements or distortions at the edge of the face. The first study for detection of unique GAN fingerprints was introduced in 2018. But photoplethysmography (PPG) translates visual cues such as how blood flow causes slight changes in skin color into a human heartbeat. Remote PPG applications are being explored in areas like health care, but PPG is also being used to identify deepfakes because generative models are not currently known to be able to mimic human blood movements.

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AI, brain hacking, Energy, Engineering, Science & Technology News

Brain-inspired electronic system could vastly reduce AI’s carbon footprint

September 4, 2020

A wafer filled with memristors.

Extremely energy-efficient artificial intelligence is now closer to reality after a study by UCL researchers found a way to improve the accuracy of a brain-inspired computing system.

The system, which uses memristors to create artificial neural networks, is at least 1,000 times more energy efficient than conventional transistor-based AI hardware, but has until now been more prone to error.

Existing AI is extremely energy-intensive—training one AI model can generate 284 tons of carbon dioxide, equivalent to the lifetime emissions of five cars. Replacing the transistors that make up all digital devices with memristors, a novel electronic device first built in 2008, could reduce this to a fraction of a ton of carbon dioxide—equivalent to emissions generated in an afternoon’s drive.

Since memristors are so much more energy-efficient than existing computing systems, they can potentially pack huge amounts of computing power into hand-held devices, removing the need to be connected to the Internet.

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AI, Automation, Employment, Robots, Science & Technology News

Are robots eating our jobs? Not according to AI

September 4, 2020

Automation has been gradually transforming the workplace for years (think Excel spreadsheets or chatbots). As artificial intelligence (AI), machine learning and deep learning systems that can learn from each other become more prevalent and smarter (think Alexa or IBM Watson), they continue to replace more manual, repetitive job tasks. Consequently, automation and robots are changing more jobs globally at breakneck speed.

A McKinsey Global Institute report suggests that between 400 million to 800 million jobs worldwide will be lost due to automation by 2030. The report claims that the U.S. could lose between 16 to 54 million jobs by 2030. The pace at which robots are entering our workforce is staggering. Oxford Economics expects robots and automation to replace 20 million (8.5%) global manufacturing jobs by 2030.

Keep in mind that these predictions came before anyone predicted the Covid-19 pandemic or its impact on our workforce. The pandemic has made the need for digital transformation and automation more urgent as the critical need to work from home, physical distancing and contactless become the new normal.

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AI, cutting edge, Google, Internet, Science & Technology News

Physna aims to be Google of 3D search with geometry-based AI

August 30, 2020

Physna, a midwestern U.S. startup founded in 2015, is trying to do for physical object (3D model) search what Google did for text and image search. Using geometric deep-learning technology and proprietary algorithms, Physna is able to understand, map and compare 3D models and index them based on their geometry. While it has been possible to search for 3D models using text, images, tags and more, this is the first time that searching for physical objects based on their fundamental geometry, their physical ‘DNA’ (hence the name PHYSNA according to its founder Paul Powers), has been made possible and available, with the launch of Thangs.com.

“We live in a 3D world, but digital technology is two-dimensional,” said Paul Powers, CEO of Physna. “Over 70% of the economy is centered around physical goods, but less than 1% of software is capable of handling 3D data. Physna was founded on the principle that computers should be taught to “think” in 3D, and accurately describe the real, 3D world around us. By enabling 3D models to be treated and analyzed like other code, Physna’s technology bridges the gap between the physical world and digital world of software. By democratizing the ability to design, interact with and analyze 3D models of the world around them, more people will have the ability to create and drive innovation in product design, 3D printing, augmented and virtual reality, gaming, healthcare and beyond.”

By identifying specific geometry ‘clusters’, the proprietary algorithms characterize and categorize 3D models in a unique way – and directly use this to search for other models that may be similar, different, or exact matches. With this approach of decomposing and linking 3D models by their geometry, Physna is able to capture 10,000 times more data points than a traditional scanned model, by codifying 3D model data for use in software applications. It essentially provides a platform for 3D designers and engineers similar to what software engineers have.

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AI, Crime Prevention, government, privacy, Science & Technology News

Artificial intelligence will surveil and study released prisoners to “reduce recidivism”

August 29, 2020

A group of researchers is launching a new artificial intelligence led study that will collect data from recently released prisoners.

Artificial intelligence applications are popping up everywhere these days, from our Internet browsing to smart homes and self-driving cars. Now a group of researchers is launching a new AI-led study that will collect data from recently released prisoners. The ultimate goal of the project is to identify – and, ostensibly, one day eliminate – the psychological and physiological triggers that cause recidivism among parolees.

Researchers at Purdue University Polytechnic Institute plan to monitor volunteer parolees using a panoply of AI-powered tools and methods, including smartphones and biometric wearable bracelets. These gadgets will record and analyze a variety of data, such as the ex-prisoners’ biological information (heart rate), photos, and location meta-data.

According to project-leads Marcus Rogers and Umit Karabiyik, the resulting data will assist them in conducting a forensic psychological analysis. While the monitoring will be gauged in intervals – not real-time – they believe it will help build a profile of the risky behaviors and stressful triggers that recent parolees face when returning to the outside world.

Citing a Department of Justice study, the researchers say over 80 percent of prisoners released from state prisons get arrested in their first 9 years and a plurality of those prisoners get arrested in less than a year.

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AI, Automation, Coronavirus, Employment, Science & Technology News

How robotics and automation could create new jobs in the new normal

August 25, 2020

Depending on who you ask, AI and automation will either destroy jobs or create new ones. In reality, a greater push toward automation will probably both kill and create jobs — human workers will become redundant in certain spheres, sure, but many new roles will likely crop up. A report last year from PA Consulting, titled “People and machines: From hype to reality,” supports this assertion, predicting that AI and automation will lead to a net gain in job numbers. This is pretty much in line with findings from the Organization for Economic Co-operation and Development (OECD), a pan-governmental economic body spanning 36 member countries, which noted that “employment in total may continue to rise” even if automation disrupts specific industries.

Automation has gained increased attention amid the great social distancing experiment sparked by COVID-19. But it’s too early to say whether the pandemic will expedite automation across all industries. Recent LinkedIn data suggests AI hiring slowed during the crisis, but there are plenty of cases where automation could help people adhere to social distancing protocols — from robot baristas and cleaners to commercial drones.

Of course, any discussion about automation invariably raises the question of what it means for jobs.

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AI, Automation, Driverless vehicles, Machine Learning, Science & Technology News

Helm.ai pioneers breakthrough…. “Deep Teaching” of neural networks

August 12, 2020

Helm.ai today announced a breakthrough in unsupervised learning technology. This new methodology, called Deep Teaching, enables Helm.ai to train neural networks without human annotation or simulation for the purpose of advancing AI systems. Deep Teaching offers far-reaching implications for the future of computer vision and autonomous driving, as well as industries including aviation, robotics, manufacturing and even retail.

Artificial intelligence, or AI, is commonly understood as the science of simulating human intelligence processed by machines. Supervised learning refers to the process of training neural networks to perform certain tasks using training examples, typically provided by a human annotator or synthetic simulator to machines to perform certain tasks, while unsupervised learning is the process of enabling AI systems to learn from unlabelled information, infer inputs and produce solutions without the assistance of pre-established input and output patterns.

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AI, Automobiles, Driverless vehicles, Science & Technology News

Exploring the three elephants in the autonomous vehicle room

August 10, 2020

The expression “elephant in the room” refers to an important question that everyone knows about but no one wants to discuss because it makes them uncomfortable.

Today, in the area of Autonomous Vehicles (AVs), there are three elephants in the room which are worth exploring.

Let’s get started.

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AI, Artificial Intelligence, Future, Machine Learning, New Viewpoints, Science & Technology News

The 6 unholy AI systems thou shalt not develop

August 6, 2020

TLDR; don’t pretend a Magic 8 Ball is a useful tool for grownups and don’t build hate machines

Artificial intelligence may be the most powerful tool humans have. When applied properly to a problem suited for it, AI allows humans to do amazing things. We can diagnose cancer at a glance or give a voice to those who cannot speak by simply applying the right algorithm in the correct way.

But AI isn’t a panacea or cure-all. In fact, when improperly applied, it’s a dangerous snake oil that should be avoided at all costs. To that end, I present six types of AI that I believe ethical developers should avoid.

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AI, brain-computer interfaces, Elon Musk, Futurist, Machine Learning, Science & Technology News

Elon Musk claims AI will overtake humans in ‘less than five years’

August 5, 2020

Chatbots powered by artificial intelligence are already capable of passing some Turing tests. ( AFP via Getty Images )

Existential threat posed by artificial intelligence is much closer than previously predicted, billionaire warns.

Elon Musk has warned that humans risk being overtaken by artificial intelligence within the next five years.

The prediction marks a significant revision of previous estimations of the so-called technological singularity, when machine intelligence surpasses human intelligence and accelerates at an incomprehensible rate.

Noted futurist Ray Kurzweil previously pegged this superintelligence tipping point at around 2045, citing exponential advances in technologies like robotics, computers and AI.

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AI, Banking, Bitcoin, Money Talk, Science & Technology News

Bank of Korea launches a department devoted to blockchain and AI

August 4, 2020

Bank of Korea is launching a digital innovation department that will leverage blockchain and AI to improve business efficiency.

The Bank of Korea has reportedly chosen to establish a “Digital Innovation department” through organizational reform in the second half of this year, according to the local news on July 22.

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