Singularity Pulse  

AI Outperforms Lawyers in Detecting Risks in Legal Contracts

Tel Aviv based LawGeex, which makes artificial intelligence (AI) software for contract review and approval, in spotting issues in everyday contracts. The AI software was compared with 20 experienced US-trained corporate lawyers. Both the lawyers and the LawGeex AI analyzed five previously unseen non-disclosure agreement contracts, containing 153 paragraphs of technical legal language under controlled conditions. LawGeex software achieved a 94% accuracy rate at identifying risks in the NDAs while the average accuracy rate was 85% for the lawyers. The challenge took the LawGeex AI 26 seconds to complete, compared to an average of 92 minutes for the lawyers. The longest time taken by a lawyer to complete the test was 156 minutes, and the shortest time was 51 minutes.


AI is Making Day Trading Obsolete

Research has shown that digital currencies have become a source of high marginal returns. However, monitoring trends to make the trade involves deep analysis of market trends, fundamentals etc. Here, AI takes advantage over humans as it trades with zero emotional breakdowns. OpenBlock has developed an automated trading bot “Obi”. It trades multiple currency pairs simultaneously along with scanning market reports, analyzing charts and performing fundamental analysis. OBi has the ability to trade up to 1200 round trips in a single 24-hour period. Obi posts the results daily of individual trades and daily profits earned. This ensures that staking participants are always informed.

  Space Research

Artificial Intelligence Identified 6,000 New Craters on The Moon

Researchers at University of Toronto Scarborough developed a technique from artificial intelligence that can automate process of manually looking at an image, locating and counting the craters, and then calculating how large they are based off the size of the image. The method utilized a convolutional neural network. Data was used from elevation maps, collected by orbiting satellites, to train the algorithm on an area that covers two-thirds of the Moon’s surface. Algorithm was able to map the unseen terrain with great accuracy and detail. It identified twice as many craters as manual methods, with about 6,000 new lunar craters being discovered.


AI Helping Diabetic Patients to Identify Retinal Damage

At Dubai Diabetes Centre, routine eye scans are being performed by AI programmed algorithm. The AI programme will identify retinal damage from the thousands of eye scans fed into it, thereby aiding doctors in diagnosing and treating patients who are suffering from retinal damage effectively and quickly. Usually, seven pictures of each eye are needed to diagnose retinal damage. Program makes that process faster. A successful trial could lead to permanent adoption at the Dubai Diabetes Centre. Currently, the accuracy of the programme’s diagnosis of retinal damage is at 96%.


The Mind-Reading Robot to Respond to Social Cues

Researchers at Cambridge University have built ‘Charles’, to mimic all human expressions as part of a ground-breaking project. Charles is made up of a system of computer programmes linked up to a camera - which can read people's faces. Top scientists at Cambridge University have been working with Charles to find out if machines can respond to social cues as part of a ground-breaking project. The computer reads the positions of the face, including the eyebrows, jaw and mouth, then sends the information over to Charles who mimics the expression in just two to three seconds.


Machine-learning Tool Helps to Detect and Combat Illegal Deforestation

Rainforest Connection, a San Francisco nonprofit, has developed a cheap, rigorous acoustic monitoring system made from modified cell phones and solar panels. An app on the so-called Guardian devices, which can be hidden in trees throughout forests, continuously listens for the telltale signs of illegal logging and animal poaching. The Company will be using Google’s TensorFlow, a free tool that makes it simpler for other companies and groups to develop machine-learning software. Currently, Rainforest Connection is only monitoring an area of 64-acre, but it plans on expanding that in the future.


AI Can Create Convincing Fictional Lifelike Photographs

Artificial intelligence is poised to lend photographic fakery a new level of sophistication. The artificial neural networks algorithms can analyze millions of pictures of real people and places—and use them to create convincing fictional ones. These networks consist of interconnected computers arranged in a system loosely based on the human brain's structure. Google, Facebook and others have been using such arrays for years to help their software identify people in images. A newer approach involves so-called generative adversarial networks, or GANs, which consist of a “generator” network that creates images and a “discriminator” network that evaluates their authenticity. Highly realistic AI-generated images and video hold great promise for filmmakers and video-game creators needing relatively inexpensive content.


AI Models Can Help Unravel Mystery of Human Brain

Cognitive neuroscientists are using AI networks to enhance the understanding of human brain. At 25th annual meeting of the Cognitive Neuroscience Society (CNS), Aude Oliva of Massachusetts Institute of Technology (MIT) presented her work on role of contextual clues in human image recognition. Using "artificial neurons" and software, researchers can now find out the parts of human brain that are responsible for recognizing a specific place or object. An artificial network was taught to recognize 350 different places, such as a kitchen, bedroom, park, living room, etc. AI programs learn very quickly when given lots of data. Artificial neural networks serve as "mini-brains that can be studied, changed, evaluated and compared against responses given by human neural networks, so the cognitive neuroscientists have some sort of sketch of how a real brain may function.

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