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Current issue

ELEKTRO 10/2016 was released on September 27th 2016. Its digital version will be available on October 27th 2016.


Topic: 22nd International trade fair ELO SYS 2016; Electrical Power Engineering; RES; Emergency Power Units


Main Article

Power system management under utilization of Smart Grid system

Printed edition of SVĚTLO (Light) 5/2016 was released on September 19th 2016. Its digital version will be available immediately.


Standards, regulations and recommendations

Regulation No 10/2016 (Prague building code) from the view of building lighting technology


Lighting installations

PROLICHT CZECH – supplier of lighting for new SAP offices

Hold up the light to see in work your work

Modern and saving LED lifting of swimming pool hall

First self-driving cognitive vehicle uses IBM Watson

08.07.2016 | Kurzweil | www.kurzweilai.net

Local Motors, creator of the world’s first 3D-printed cars, has developed the first self-driving “cognitive” vehicle, using IBM Watson Internet of Things (IoT) for Automotive.

The vehicle, dubbed “Olli,” can carry up to 12 people. It uses IBM Watson and other systems to improve the passenger experience and allow natural interaction with the vehicle. Olli will be used on public roads locally in Washington DC and later this year in Miami-Dade County.

FIrst cognitive self-driving vehicle

Olli is the first vehicle to use the cloud-based cognitive computing capability of IBM Watson IoT to analyze and learn from high volumes of transportation data, produced by more than 30 sensors embedded throughout the vehicle. Sensors will be added and adjusted continually as passenger needs and local preferences are identified.

Four Watson developer APIs — Speech to Text, Natural Language Classifier, Entity Extraction and Text to Speech — will enable passengers to interact conversationally with Olli while traveling from point A to point B, discussing topics about how the vehicle works, where they are going, and why Olli is making specific driving decisions. Passengers can also ask for recommendations on local destinations such as popular restaurants or historical sites based on analysis of personal preferences.

Read more at Kurzweil

Image Credit: Local Motors