This is Harnham’s weekly news digest,
the place to come for a quick breakdown of the week’s top news stories from the
world of Data & Analytics.
Tech Xplore: New deep learning techniques
lead to materials imaging breakthrough
Most of the time, supercomputers are
being used by researchers to study the cause and effect of complex phenomena.
But sometimes scientists need to deduce the origins of phenomena, using
observable results – known as ‘inverse problems’.
A team from the US Department of
Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL), NVIDIA, and Uber
Technologies have developed and demonstrated two new techniques within a
commonly used communication library called Horovod – to try to better understand
The Horovod platform trains deep neural
networks (DNNs) that use algorithms to imitate and harness the decision-making
power of the human brain for scientific applications. It relies on a single
coordinator to provide instructions to many different workers which can result
in lengthy and repetitive training processes and significant slowdowns for
large-scale deep-learning applications.
This new technique removed repetitive
steps from the traditional process to increase the speed and outperform
existing approaches, which has led to the discovery of the first-ever
approximate solution to an age-old inverse problem in the field of materials
Scientist Nouamane Laanait said;
“We don’t know what the ceiling is for these improvements, so the only way
to find out is by continuing to experiment.”
Karat: Serena Williams teams up with Karat to
double the number of Black Software Engineers in the U.S.
Karat, the world’s largest interviewing
company, recently announced a strategic
investment from Serena Williams to significantly scale Brilliant Black Minds, a
program that improves access and inclusion across the technology industry.
Karat has long been calling for the
industry to help add more than 100,000 new Black engineers to tech in the next
decade. Serena is planning to support this vision, by serving as Karat’s
‘Champion of Brilliance’ and by opening the program to all current and aspiring
Black software engineers.
Just 5 percent of all software engineers in the U.S. are Black, with
many Black software engineers facing multiple barriers to entering the tech
industry, from structural inequities that delay early exposure to computer
science to fewer connections in their professional networks, and less
opportunities to practice technical interviews.
As part of Serena’s involvement, she
will mentor on the importance of practice and building a championship mindset
to help participants land their dream job in tech.
Read more about this incredible
AI Business: Mark Zuckerberg: ‘Meaningful’
metaverse monetization not until 2030s
Despite the buzz around the endless
possibilities that the new metaverse will bring, Mark Zuckerburg has revealed
that he does not expect any ‘meaningful’ monetisation from it until the 2030s.
As a result, there appears to be a
consorted effort to pivot towards more short-term goals such as targeting the
VR community. There are plans in motion to grow the metaverse community through
its Horizon Worlds, a VR game and social environment accessed through Meta’s
Oculus VR headset. Something which Zuckerberg claims will eventually replace
Earlier this year, Meta reported that
in the fourth quarter of 2021, daily active users (DAU) declined from the third
quarter – the first-ever drop for Facebook – resulting in Meta losing more than
$230 billion in market value in one day.
This combined with the swirling
regulation currently being rethought and rewritten could cause some significant
challenges for the industry and will make it an interesting and telling year
for the success of the metaverse.
Read more here.
Tech Xplore: The new algorithm that has
opinions about your face
When people meet in person for the
first time, they make instant judgments, whether consciously or unconsciously
about that person – from the way they look to their intelligence and
everything in between. These first impressions tend to shape how we act toward
that person but are powerful enough to influence all sorts of decisions,
such as hiring.
Researchers at Stevens Institute of
Technology, in collaboration with Princeton University and University of
Chicago, have taught an AI algorithm to model these first impressions and
accurately predict how people will be perceived based on a photograph of their
The model was developed by asking
thousands of people to give their first impressions of over 1,000
computer-generated photos of faces and then ranking them using criteria such as
how intelligent, electable, religious, trustworthy, or outgoing the subject
appeared to be. These responses were then used to train a neural network.
The real-life implications of this
research could be both positive and negative, however, cognitive scientist and
AI expert, Jordon Suchow, reminds us that: ‘It’s important to remember that the
judgments we’re modeling don’t reveal anything about a person’s actual
personality or competencies’” He goes on to say: “What we’re doing here is
studying people’s stereotypes, and that’s something we should all strive to
Read more about the work here.
We’ve loved seeing
all the news from Data & Analytics in the past week, it’s a
market full of exciting and dynamic opportunities. To learn more about our work
in this space, get in touch with us at firstname.lastname@example.org.