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Social roboticist, Heather Knight, sees robots and entertainment a research-rich coupling. So she programmed a charming humanoid robot named DATA with jokes, and equipped it with sensors and algorithmic capabilities to help with timing and gauging a crowd. Then Knight and DATA hit the road on an international robot stand-up comedy tour. Their act landed stage time at a TED conference and Knight was profiled in Forbes 30 Under 30. Watching Data perform is much like watching an amateur stand-up comedian cutting her/his chops at an open mic night doing light comedy with a sweet but wooden delivery.

Knight’s goal is specific:

In satellite photos of the Earth, clouds of bright green bloom across the surface of lakes and oceans as algae populations explode in nutrient-rich water. From the air, the algae appear to be the primary players in the ecological drama unfolding below.

But those we credit for influencing the aquatic environment at the base of the food chain may be under the influence of something else: whose can reconfigure their hosts’ metabolism.

In a new study published in Nature Communications, a research team from Virginia Tech reported that they had found a substantial collection of genes for metabolic cycles—a defining characteristic of cellular life—in a wide range of “.”

“It’s good to hear your voice, you know it’s been so long If I don’t get your calls, then everything goes wrong… Your voice across the line gives me a strange sensation” — Blondie, “Hanging on the Telephone”

In 1978, Debbie Harry propelled her new wave band Blondie to the top of the charts with a plaintive tale of yearning to hear her boyfriend’s from afar and insisting he not leave her “hanging on the telephone.”

But the questions arises: What if it were 2020 and she was speaking over VOIP with intermittent packet losses, audio jitter, network delays and out-of-sequence packet transmissions?

Researchers have designed a machine learning method that can predict battery health with 10x higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics.

The researchers, from Cambridge and Newcastle Universities, have designed a new way to monitor batteries by sending electrical pulses into them and measuring the response. The measurements are then processed by a to predict the ’s health and useful lifespan. Their method is non-invasive and is a simple add-on to any existing battery system. The results are reported in the journal Nature Communications.

Predicting the state of health and the remaining useful lifespan of lithium-ion batteries is one of the big problems limiting widespread adoption of : it’s also a familiar annoyance to mobile phone users. Over time, battery performance degrades via a complex network of subtle chemical processes. Individually, each of these processes doesn’t have much of an effect on battery performance, but collectively they can severely shorten a battery’s performance and lifespan.

In order to better solve complex challenges at the dawn of the third decade of the 21st century, Alphabet Inc. has tapped into relics dating to the 1980s: video games.

The parent company of Google reported this week that its DeepMind Technologies Artificial Intelligence unit has successfully learned how to play 57 Atari video games. And the plays better than any human.

Atari, creator of Pong, one of the first successful video games of the 1970s, went on to popularize many of the great early classic video games into the 1990s. Video games are commonly used with AI projects because they algorithms to navigate increasingly complex paths and options, all while encountering changing scenarios, threats and rewards.

As of right now, Cortical’s mini-brains have less processing power than a dragonfly brain. The company is looking to get its mouse-neuron-powered chips to be capable of playing a game of “Pong,” as CEO Hon Weng Chong told Fortune, following the footsteps of AI company DeepMind, which used the game to test the power of its AI algorithms back in 2013.

“What we are trying to do is show we can shape the behavior of these neurons,” Chong told Fortune.

READ MORE: A startup is building computer chips using human neurons [Fortune].

Satellites come in all sizes and shapes. A small satellite or SmallSat is commonly considered to be a satellite that weighs less than 500 kg.

As a basic application of various satellite sizes by mass, the common distinction:

Lower LimitUpper Limit(kg)ClassificationExamples
1000Large satellitesHubble Space Telescope / Inmarsat-4A F4
5001000Medium satellitesO3b
0500Small satellitesSpaceX StarLink
Short Summary of Satellite sizes

CubeSats are smaller yet.

Under DARPA’s Photonics in the Package for Extreme Scalability (PIPES) program, researchers from Intel and Ayar Labs have demonstrated early progress towards improving chip connectivity with photons – or light. Signaling over optical fibers enables the internet today and optical transceivers are ubiquitous in data centers, yet digital systems still rely upon the movement of electrons over metal wires to push data between integrated circuits (ICs) on a board. Increasingly, the limitations of electrical signaling from the chip package restrict overall bandwidth and signaling efficiency, throttling the performance of advanced systems. The PIPES program is exploring ways to expand the use of optical components to address these constraints and enable digital microelectronics with new levels of performance.

Researchers from Intel and Ayar Labs working on PIPES have successfully replaced the traditional electrical input/output (I/O) of a state-of-the-art field programmable gate array (FPGA) with efficient optical signaling interfaces. The demonstration leverages an optical interface developed by Ayar Labs called TeraPHY, an optical I/O chiplet that replaces electrical serializer/deserializer (SERDES) chiplets. These SERDES chiplets traditionally compensate for limited I/O when there is a need for fast data movement, enabling high-speed communications and other capabilities. Using Intel’s advanced packaging and interconnect technology, the team integrated TeraPHY and the Intel FPGA core within a single package, creating a multi-chip module (MCM) with in-package optics. The integrated solution substantially improves interconnect reach, efficiency, and latency – enabling high-speed data links with single mode optical fibers coming directly from the FPGA.