Singularity Pulse  

TransUnion To Use AI to Improve Africa’s Financial Inclusion

TransUnion, a credit reporting agency, is making use of AI to gain insights into consumer behavior and consequently, help to increase financial inclusion of South Africa. The company uses “alternative data” which includes non-credit data mined from consumers' offline and online activities to better understand a consumers' credit risk. Instead of traditional credit-related data, interpretation of alternative data is able to substantially improve consumers' correct profiling and subsequent access to financial services. They have seen an increase in local population credit score over time.


Particle Physicists Team Up with AI to Solve Toughest Science Problems

Experiments at Large Hadron Collider (LHC), world's largest particle accelerator at European particle physics lab CERN, produces about a million gigabytes of data every second. Fortunately, particle physicists don’t have to deal with it all by themselves. Researchers apply what they call "triggers" which are dedicated hardware and software, deciding in real time which data to keep for analysis and which data to toss out. A ML algorithm is developed which figure out for itself how to do various analyses, thus saving several manhours of design and analysis work. Deep learning makes use of “neural networks” which learn on their own how to perform certain analysis tasks during their training period.

  Information Technology

Google To Simplify ML Learning with Use Of SQL

Google has included ML abilities to its petabyte (PB)-scale cloud database offering. The new version is termed as “BigQuery ML” and allow users to make use of simple Structured Query Language (SQL) statements to develop and deploy ML models for predictive analytics. The addition in the application will bring ML capabilities faster compared to traditional ML models in part as now the data analytics can be performed at the source itself. The other two similar products in the market are Amazon's Relational Database Service and Microsoft's Azure SQL.


Tesla to Start Making Its Own AI Chips

Elon Musk, CEO of Tesla, has established during the recent earnings call that his company is producing its own computer chips for automated driving. Till now, Tesla used to rely on Nvidia for its hardware requirements. The new hardware update will enable Tesla cars to gain a significant competitive advantage over its rival which still rely on off-the-shelf technologies present in the market. It will further enable Tesla cars to gain AI expertise and capabilities. The older Teslas could be retrofitted with the hardware, reports Musk.

  Health Care

Google Glass and AI to Help Autistic Children Socialize Better

Google Glass is finding new applications in helping children with autism. It assists children in having a better social life. According to findings of a research done by Stanford, Google Glass combined with AI algorithms is helping children identify facial expressions. Stanford biomedical data scientist Dennis Wall, with his team, conduct a study in which they used the Google Glass instead of traditional therapist. Instead of flash cards for expressions, a camera records face of a person in front of the child and feeds the image to a connected smartphone app. Making use of AI, the application differentiates between eight core expressions. Result is provided via the Google Glass’ earpiece or via an emoticon on the tiny display.


AI Powered Cancer Screening to Be More Efficient

Diagnosing cancer is difficult as it includes telling differences between a deadly and a harmless lump, instead of just identifying it. Mindshare Medical, a Seattle startup, is developing AI capabilities that can diagnose cancer using imaging data that is even invisible to the human eye. Currently, imaging is the primary way of screening. But human analysis of images gives different answers. The new technology will make initial cancer screening more efficient. It will eliminate long delays for patients who do have cancer and costly follow-up procedures for patients who do not have it. Currently Mindshare Medical has eight employees and has raised $4.1 million to date.


AI “Painting” Recreates Blacked Out Faces on TV Screens

Steve DiPaola and Kate Hennessy from Canada's Simon Fraser University have developed an algorithm that uses AI to "paint" back peoples’ blacked out faces on TV screens. Initially a human computer operator distorts the video image of a person's face. Then, with use of AI, a second level of random distortions are added. The two layers of random distortions makes it impossible for anyone to recognize what the person originally looked like. Next, AI applies its painting process to the image. The AI technology also incorporates tone of subjects' voices while determining their facial structure.

“Quantum Computing, a revolution in technology, has shown great promise towards solving complex computing problems currently outside the capabilities of current computers. Though in its infancy, we at Decimal Point Analytics strongly believe that it is going to grow exponentially in the near future. It holds the potential not only to boost the AI revolution but also transform the way data is synthesized. The articles on Quantum computing will give an insight into the recent developments in this space.”
  Quantum Computing

“Complexity Test” To Offers New Perspective on Quantum Computers

Quantum devices aren't large enough to be called full-scale computers. Standard measure of computational difficulty is known as “sampling complexity”. This gauges how easy or hard it is for an ordinary computer to simulate outcome of the quantum experiment. If a computer takes reasonable amount of time to mimic one run of a quantum experiment, the sampling complexity is low; if it takes a long time, the sampling complexity is high. Few expect that quantum computers wielding several qubits will have lower sampling complexity. To show the utility of this method, collaborators proved that sampling complexity tracks the easy-to-hard transition of a task that small/medium sized quantum computers are expected to perform faster than ordinary computers.


Quantum Computing Progress Takes A Hit from A UT Grad

Ewin Tang, teenager from Texas, has released a paper online in which he proves that ordinary computers can solve an important computing problem with performance speed comparable to that of quantum computers. The “recommendation problem” relates to how services like Amazon/Netflix determine which products you might like to try. In a recommendation problem, one can think of this data as being arranged in a giant grid with movies listed across the top, users listed down the side, and values at points in the grid quantifying whether, or to what extent, each user likes each film. A good algorithm would generate recommendations by quickly and accurately recognizing similarities between movies and users and filling in the blanks in the matrix.

Quantum Computing  
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