​With 5G, carriers hope  to deliver data to smartphone users at speeds 10 times as fast as on  today’s 4G networks, and with only 1 millisecond of delay.

Both Verizon and AT&T say their 2017 fixed wireless networks will rely on millimeter waves, which are arguably the hottest new 5G technology. Millimeter waves are officially defined as waves transmitted at frequencies between 30 and 300 gigahertz, and they are between 1 and 10 millimeters in length.

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Tensor processing unit
Tensor processing units (or TPUs) are application-specific integrated circuits (ASIC) developed specifically for machine learning. Compared to graphics processing units (which as of 2016 are frequently used for the same tasks), they are designed explicitly for a higher volume of reduced precision computation with higher IOPS per watt (e.g. as little as 8-bit precision[1]), and lack hardware for rasterisation/texture mapping.[2] The chip has been specifically designed for Google’s TensorFlow framework, however Google still uses CPUs and GPUs for other machine learning.[3] Other AI accelerator designs are appearing from other vendors also and are aimed at embedded and robotics markets.

Google has stated that its proprietary tensor processing units were used in the AlphaGo versus Lee Sedol series of man-machine Go games.[2] Google has also used TPUs for Google Street View text processing, and was able to find all the text in the Street View database in less than five days. In Google Photos, an individual TPU can process over 100 million photos a day. It is also used in RankBrain which Google uses to provide search results.[4] The tensor processing unit was announced in 2016 at Google I/O, although the company stated that the TPU had been used inside their datacenter for over a year prior.[3][2]

The chip size can fit in a hard drive slot within a data center rack according to Google Distinguished Hardware Engineer Norm Jouppi.[3]

See also Edit

Vision processing unit a similar device specialised for vision processing.
TrueNorth a similar device simulating spiking neurons instead of low precision tensors.
Neural processing unit
References Edit

^ Armasu, Lucian (2016-05-19). “Google’s Big Chip Unveil For Machine Learning: Tensor Processing Unit With 10x Better Efficiency (Updated)”. Tom’s Hardware. Retrieved 2016-06-26.
^ a b c Jouppi, Norm (May 18, 2016). “Google supercharges machine learning tasks with TPU custom chip”. Google Cloud Platform Blog. Google. Retrieved 2017-01-22.
^ a b c “Google’s Tensor Processing Unit explained: this is what the future of computing looks like”. TechRadar. Retrieved 2017-01-19.
^ “Google’s Tensor Processing Unit could advance Moore’s Law 7 years into the future”. PCWorld. Retrieved 2017-01-19.

Last edited 12 days ago by PirateImpulse

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Mary Winston Jackson (April 9, 1921 – February 11, 2005) was an African American mathematician and aerospace engineer at the National Advisory Committee for Aeronautics (NACA), which in 1958 was succeeded by theNational Aeronautics and Space Administration (NASA). She worked atLangley Research Center in Hampton, Virginia, for most of her career. She started as a computer at the segregated West Area Computing division. She took advanced engineering classes and in 1958 became NASA’s first black female engineer.

After 34 years at NASA, Jackson had earned the most senior engineering title available. She realized she could not earn further promotions without becoming a supervisor. She accepted a demotion to become a manager of both the Federal Women’s Program, in the NASA Office of Equal Opportunity Programs, and of the Affirmative Action Program. In this role, she worked to influence both the hiring and promotion of women in NASA’s science, engineering, and mathematics careers.

Jackson’s story features in the non-fiction book Hidden Figures: The Story of the African-American Women Who Helped Win the Space Race (2016). She is one of the three protagonists in Hidden Figures, the film adaptation released the same year.

https://en.m.wikipedia.org/wiki/Mary_Jackson_(engineer)

Dorothy Johnson Vaughan (September 20, 1910 – November 10, 2008) was an African American mathematician who worked for the National Advisory Committee for Aeronautics (NACA), and NASA, at Langley Research Center inHampton, Virginia. In 1949, she became acting supervisor of the West Area Computers, the first African-American woman to supervise a staff at the center.

She later was promoted officially to this position. During her 28-year career, Vaughan prepared for the introduction of machine computers in the early 1960s by teaching herself and her staff the programming language of FORTRAN; she later headed the programming section of the Analysis and Computation Division (ACD) at Langley.

Vaughan is one of the women featured in Margot Lee Shetterly‘s history Hidden Figures: The Story of the African-American Women Who Helped Win the Space Race(2016). It was adapted as a biographical film of the same name, also released in 2016.

https://en.m.wikipedia.org/wiki/Dorothy_Vaughan

Katherine Coleman Goble Johnson (born August 26, 1918) is an African American physicist and mathematician who made contributions to the United States’ aeronautics and space programs with the early application of digital electronic computers at NASA. Known for accuracy in computerized celestial navigation, she conducted technical work at NASA that spanned decades. During this time, she calculated the trajectories,launch windows, and emergency back-up return paths for many flights from Project Mercury, including the early NASA missions of John Glennand Alan Shepard, and the 1969 Apollo 11 flight to the Moon, through theSpace Shuttle program.^[1][2] Her calculations were critical to the success of these missions.^[1] Johnson also did calculations for plans for a mission to Mars.
https://en.m.wikipedia.org/wiki/Katherine_Johnson

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