Via
Wired magazine:
The U.S. National Security Agency (NSA) has chosen to open source the
cybersecurity tool Ghidra, a reverse-engineering platform that takes
"compiled," deployed software and "decompiles" it. Reverse engineering
allows malware analysts and threat intelligence researchers to work
backward from software discovered in the wild to understand how it
works, what its capabilities are, and who wrote it. Said NSA
cybersecurity advisor Rob Joyce, Ghidra was "built for our internal use
at NSA" and "helped us address some things in our work flow." Joyce
noted that the NSA views the release of Ghidra as a recruiting strategy,
allowing new hires to enter the agency at a higher level or contractors
to provide expertise without having to first come up to speed on the
tool. Added Dave Aitel, a former NSA researcher who is now chief
security technology officer at Cyxtera, "Malware authors already know
how to make it annoying to reverse their code. There's really no
downside [to releasing Ghidra]."
Via the
Washington Times:
Researchers at the Georgia Institute of Technology (Georgia Tech) have
found that state-of-the-art object-detection systems, such as the
sensors and cameras used in self-driving cars, are better at detecting
people with lighter skin tones, meaning they are less likely to identify
black people and to stop before crashing into them. The researchers
examined eight image recognition systems and found the bias in each one,
with accuracy 5% lower on average for people with darker skin. The team
proved the hypothesis by dividing a large pool of pedestrian images
into groups of lighter and darker skin using the Fitzpatrick scale—a
scientific way of classifying skin color. “This behavior suggests that
future errors made by autonomous vehicles may not be evenly distributed
across different demographic groups,” the researchers wrote.
Via
the Los Angeles Times:
The New York Police Department (NYPD) is using pattern-recognition
software so analysts can compare robberies, larcenies, and thefts to
hundreds of thousands of crimes logged in the department's database,
finding matches faster than they would manually. The Patternizr
algorithm was launched in December 2016, and NYPD assistant commissioner
of data analytics Evan Levine said, "The more easily that we can
identify patterns in...crimes, the more quickly we can identify and
apprehend perpetrators." Levine and co-developer Alex Chohlas-Wood
trained Patternizr on 10 years of patterns that the department had
manually identified. Patternizr accurately reproduced old crime patterns
a third of the time, and matched parts of patterns 80% of the time. The
software compares factors like method of entry, type of goods stolen,
and distance between crimes, and reduces possible racial bias by not
counting the race of suspects when looking for patterns.
Via
the Wall Street Journal:
Employers across a spectrum of industries are welcoming applicants with
experience in making or playing videogames, believing such backgrounds
can help workers with online collaboration, problem-solving, and other
key workplace skills. For example, General Electric (GE) is hiring
people with game development expertise to train robots to inspect
hazardous areas via virtual reality technology, a role that GE's
Ratnadeep Paul said "came out of the gaming industry." Although some
people still regard gamers as socially maladroit, in recent years that
assumption has been dispelled, partly due to increasingly popular online
multiplayer games that encourage players to form teams and strategize
via online text or voice communication. Said the Rochester Institute of
Technology's Andrew Phelps, "What we used to stereotypically think of as
a weird thing some folks did in their basement is now part of everyday
life. Gaming has become a common touch point for people."
Via
New York Times.com:
The Aravind Eye Hospital in Madurai, India, is working with Google
artificial intelligence (AI) scientists to automate the identification
of diabetic retinopathy. The hospital is using the new AI system to
screen patients, with plans to deploy the technology in surrounding
villages where eye doctors are scarce. The system is based on a neural
network analyzing millions of retinal scans indicating diabetic
blindness so it can learn to identify the disease on its own. The
Aravind installation employs wall-mounted computer screens in waiting
rooms to translate information into the various languages spoken by
patients; the system's performance reportedly equals that of trained
ophthalmologists. However, Luke Oakden-Rayner, director of medical
imaging research at the Royal Adelaide Hospital in Australia, warned,
“On paper, the Google system performs very well, but when you roll it
out to a huge population, there can be problems that do not show up for
years.”
Via
UW Medicine:
International researchers have computer-designed a nanoparticle vaccine
candidate for respiratory syncytial virus (RSV), an infection caught by
nearly all children under three, which is the leading cause of pneumonia
in babies under a year old in the U.S. Computationally-designed protein
nanoparticles enable significantly greater control over key vaccine
properties, including overall size, stability, and the number of
antigens presented to the immune system. University of Washington (UW)
researchers said the vaccine based on the DS-Cav1 protein yielded 10
times more potency than DS-Cav1 alone. UW's Neil King said, "We believe
that computationally-designed nanoparticle vaccines will ultimately be
simpler to manufacture and more effective than traditional vaccines. We
will continue to develop this technology so that we and others can make
new vaccines better, cheaper, and faster."
Via
Reuters:
U.S. regulators have approved Google's deployment of a radar-based
motion sensor, granting it a waiver to use the device at higher power
levels than currently permitted. The U.S. Federal Communications
Commission (FCC) said the Project Soli device "will serve the public
interest by providing for innovative device control features using
touchless hand gesture technology." According to the FCC, the sensor
captures motion in a three-dimensional space using a radar beam to
facilitate touchless control of functions or features that can benefit
users with mobility or speech impediments. Google said the sensor
enables users to press an invisible button between the thumb and index
fingers, or a virtual dial that turns by rubbing the thumb against the
index finger. Said Google, "Even though these controls are virtual, the
interactions feel physical and responsive" as feedback is produced by
the haptic sensation of fingers touching.
And now, news from
Germany.
A new parallel-computing approach can solve combinatorial problems,
according to a study published in Proceedings of the National Academy of
Sciences. Researchers from the Max Planck Institute of Molecular Cell
Biology and Genetics and the Dresden University of Technology
collaborated with an international team on the technology. The
researchers note significant advances have been made in conventional
electronic computers in the past decades, but their sequential nature
prevents them from solving problems of a combinatorial nature. The
number of calculations required to solve such problems grows with the
size of the problem, making them intractable for sequential computing.
The new approach addresses these issues by combining well-established
nanofabrication technology with molecular motors that are very
energy-efficient and inherently work in parallel. The researchers
demonstrated the parallel-computing approach on a benchmark
combinatorial problem that is very difficult to solve with sequential
computers. The team says the approach is scalable, error-tolerant, and
dramatically improves the time to solve combinatorial problems of size
N. The problem to be solved is "encoded" within a network of nanoscale
channels by both mathematically designing a geometrical network that is
capable of representing the problem, and by fabricating a physical
network based on this design using lithography. The network is then
explored in parallel by many protein filaments self-propelled by a
molecular layer of motor proteins covering the bottom of the channels.
Meanwhile at
Stanford:
Researchers at Stanford University are using 600,000 fictional
stories to inform their new knowledge base called Augur. The team
considers the approach to be an easier, more affordable, and more
effective way to train computers to understand and anticipate human
behavior. Augur is designed to power vector machines in making
predictions about what an individual user might be about to do, or want
to do next. The system's current success rate is 71 percent for
unsupervised predictions of what a user will do next, and 96 percent for
recall, or identification of human events. The researchers report
dramatic stories can introduce comical errors into a machine-based
prediction system. "While we tend to think about stories in terms of the
dramatic and unusual events that shape their plots, stories are also
filled with prosaic information about how we navigate and react to our
everyday surroundings," they say. The researchers note artificial
intelligence will need to put scenes and objects into an appropriate
context. They say crowdsourcing or similar user-feedback systems will
likely be needed to amend some of the more dramatic associations certain
objects or situations might inspire.
Via
HPCwire.com:
Water scarcity has been surfacing as an extremely critical issue
worth addressing in the U.S. as well as around the globe nowadays. A
McKinsey-led report shows that, by 2030, the global water demand is
expected to exceed the supply by 40%. According to another recent report
by The Congressional Research Service (CRS), more than 70% of the land
area in the U.S. underwent drought condition during August, 2012.
When it comes to 2014, the condition has become even
worse in some of the states: following a three-year dry period,
California declared state-wide drought emergency. A report by NBC News
on this drought quotes California Gov. Jerry Brown as saying, “perhaps
the worst drought California has ever seen since records began being
kept about 100 years ago”. Many such evidences of extended droughts and
water scarcity have undoubtedly necessitated concerted approaches to
tackling the global crisis and ensuring water sustainability.
Supercomputers are notorious for consuming a
significant amount of electricity, but a less-known fact is that
supercomputers are also extremely “thirsty” and consume a huge amount of
water to cool down servers through cooling towers that are typically
located on the roof of supercomputer facilities. While high-density
servers packed in a supercomputer center can save space and/or costs,
they also generate a large amount of heat which, if not properly
removed, could damage the equipment and result in huge economic losses.
The high heat capacity makes water an ideal and
energy-efficient medium to reject server heat into the environment
through evaporation, an old yet effective cooling mechanism. According
to Amazon’s James Hamilton, a 15MW data center could guzzle up to
360,000 gallons of water per day. The U.S. National Security Agency’s
data center in Utah would require up to 1.7 million gallons of water per
day, enough to satiate over 10,000 households’ water needs.
Although water consumption is related to energy
consumption, they also differ from each other: due to time-varying water
efficiency resulting from volatile outside temperatures, the same
amount of server energy but consumed at different times may also result
in different amount of water evaporation in cooling towers. In addition
to onsite cooling towers, the enormous appetite for electricity also
holds supercomputers accountable for offsite water consumption embedded
in electricity production. As a matter of fact, electricity production
accounts for the largest water withdrawal among all sectors in the U.S.
While not all the water withdrawal is consumed or “lost” via
evaporation, the national average water consumption for just one kWh
electricity still reaches 1.8L/kWh, even excluding hydropower which
itself is a huge water consumer.