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Singapore will pilot autonomous buses and real-time monitoring of rail system

The Singaporean Land Transport Authority in partnership with the Nanyang Technology University will test the use of two driverless buses within the Jurong Innovation District to improve road safety, reduce vehicle congestion and pollution, and address manpower challenges. The autonomous buses will be driving along a pre-determined route and will be recharged at bus stops. Heavy focus is being placed by LTA on road safety as the project announcement came a day after a crash incident involving nuTonomy, which was testing its autonomous cars in the One North Business District. The two parties will also develop a real-time monitoring system for its national rail network to identify potential defects without disrupting operations.

Key Takeaway: 

The transport regulator of Singapore in partnership with the NTU will pilot the use of autonomous buses in the Jurong Innovation District to address transportation-related issues.

Publication: 
Publication Date: 
October 19, 2016

Wal-Mart adopts blockchain for first time to track pork supplies

Wal-Mart has partnered with IBM to use the latter's blockchain technology to track its pork supplies in China. This is the first time that Wal-Mart, the largest retailer in the world, is adopting blockchain technology. Tracking pork is just a start for the company. If the project is successful, it could also expand to include other commodities. Wal-Mart wants to be able to monitor where the meat goes in its supply chain using serial numbers and record systems. The retailer giant is also partnering with Tsinghua University for academic research on the project. The news is reported as a significant development for the growing blockchain as a service (BaaS) industry.

Key Takeaway: 

Retail giant Wal-Mart is adopting blockchain technology through a partnership with IBM to monitor the pork supply chain in China, which could be the beginning of a new solution for tracking commodities and food supply chains.

Transforming Business Models: 
Publication: 
Publication Date: 
October 19, 2016

Microsoft’s neural network at par with humans in recognizing speech

Microsoft's artificial intelligence program has reached the accuracy level of a professional human transcriber in recognizing speech, achieving the same error rate of 5.9%, an improvement from its record of 6.3% just a month ago. The overall score is a measurement of how the AI and the human transcriptionists did on three indicators - how many times both wrongly substituted sounds, omitted a word, or inserted the wrong word. According to Microsoft's chief speech scientist Xuedong Huang, achieving parity with a human is a historic achievement. The company used 2,000 hours of data to train its neural network. Improved automated speech recognition systems can enhance current speech-to-text services as well as Cortana, adding features that could allow the deaf to understand spoken words.

Key Takeaway: 

Microsoft’s neural network performed as accurately as a professional human transcriptionist at recognizing speech with an error rate of 5.9%; the improvement can introduce better speech-to-text systems and artificial intelligence assistants that can aid the deaf to hear.

Publication: 
Publication Date: 
October 19, 2016

Rise in EV adoption will drive new opportunities for utilities

A new report from Bloomberg New Energy Finance states that the electrification of transportation will present opportunities for utilities faced with stagnant load growth as well as increasing pressure to innovate with new business models that incorporate distributed and clean energy as a resource. It is estimated that electric vehicle adoption will have greater impact on utilities by 2030 as they will make up 3% of global energy demand. However, electric cars are not expected to be competitive to internal combustion engine vehicles until the mid-2020s. Utilities can provide specific rate plans designed for EV charging to cater to this new market, as well as new vehicle leases that take account negotiated electricity rates. They can also participate in the build-out of public and semi-public charging infrastructure. Autonomous cars and car sharing models can speed the integration of electric vehicles as demand response assets. Much opportunity is also in used batteries which is expected to hit the market in large quantities by mid-2020s. They will be used for grid storage, enabling more clean energy to be integrated to the grid, as well as introduce lower peak demand prices for public charging.

Key Takeaway: 

Rise in electric vehicle adoption driven by declining battery prices as well as autonomous and ride sharing models, will present opportunities for utilities to increase their bottomline as loads are expected to grow and enable them to venture into new business models such as new rate plans and vehicle lease structures.

Publication: 
Publication Date: 
October 19, 2016

DeepMind’s new hybrid AI learns from memory on its own

Google's DeepMind built a new hybrid artificial intelligence that can learn on its own from the memory it already has. The system, called Differential Neural Computer (DNC), is hybrid because it has both a neural network and the data storage of conventional computers. This allows it to learn from examples as well as store vast amounts of data like traditional computers. From demonstrations, it was able to infer family connections on its own with just a few inputs about certain relationships. It also determined complex relationships and possible routes for a public transit system after learning the basics. This gives it capabilities much like the human brain where it solves new information based on data from its memory, leading to a future where computers can answer questions on new topics based on prior data or artificial intelligence systems that can reason independently.

Key Takeaway: 

A new hybrid AI called Differential Neural Computer, developed by DeepMind, is both a neural network and a powerful memory computer, able to learn and figure out new information from existing data in its memory independently.

Transforming Business Models: 
Publication: 
Publication Date: 
October 17, 2016

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