AI and Machine Learning Salaries Drop
According to Dice’s numbers, competition for machine learning, natural language
processing, and AI experts softened in 2021, with average salaries dropping 2.1
percent, 7.8 percent, and 8.9 percent respectively. This comes on the heels of
repeated—and sometimes dramatic—increases in recent years. Average U.S. salaries
for software engineers with expertise in machine learning, for example, jumped
22 percent in 2019 over 2018, then went up another 3.1 percent in 2020. “There
are a variety of factors likely contributing to [these] decreases,” Dice chief
marketing officer Michelle Marian told IEEE Spectrum, “with one important
consideration being that more technologists are learning and mastering these
skill sets. The increases in the talent pool over time can result in employers
needing to pay at least slightly less, given that the skill sets are easier to
find. We have seen this occur with a range of certifications and other highly
specialized technology skills.” ... Demand seemed to be slowing for
cybersecurity analysts and data engineers, however. Up 16.3 percent in 2020 from
2019, the average cybersecurity analyst salary fell 0.8 percent in 2021 to
$102,253, and data engineers saw an average salary drop of 1.1 percent, to
$117,295, after a 4.7 percent increase in 2020.
A New Trick Lets Artificial Intelligence See in 3D
The new approach involves using a neural network to capture and generate 3D
imagery from a few 2D snapshots, a technique dubbed “neural rendering.” It arose
from the merging of ideas circulating in computer graphics and AI, but interest
exploded in April 2020 when researchers at UC Berkeley and Google showed that a
neural network could capture a scene photorealistically in 3D simply by viewing
several 2D images of it. That algorithm exploits the way light travels through
the air and performs computations that calculate the density and color of points
in 3D space. This makes it possible to convert 2D images into a photorealistic
3D representation that can be viewed from any possible point. Its core is the
same sort of neural network as the 2012 image-recognition algorithm, which
analyzes the pixels in a 2D image. The new algorithms convert 2D pixels into the
3D equivalent, known as voxels. Videos of the trick, which the researchers
called Neural Radiance Fields, or NeRF, wowed the research community. “I’ve been
doing computer vision for 20 years, but when I saw this video, I was like ‘Wow,
this is just incredible,’” says Frank Dellaert, a professor at Georgia Tech.
4 Exciting DeFi Projects Worth Watching In 2022
Parallel Finance is another promising DeFi 2.0 project that aims to add
liquidity and increase the scope of DeFi across the Polkadot blockchain. This
decentralized money market protocol offers many products, including lending,
staking, and borrowing within the Polkadot ecosystem. The core products offered
by Parallel Finance include an AMM, the first money market for Polkadot and
Kusama ecosystems, insured staking, margin staking, leverage staking, and
algorithmic staking. Parallel Finance’s unique lending design can disrupt the
DeFi 1.0 narrative, adding higher yields and increased opportunities for
participants. ... By combining three different decentralized Polkadot-powered
protocols into a unified solution, Parallel Finance unlocks innovative yield
opportunities and enables participants to lend and stake simultaneously. To
date, Parallel Finance has the highest TVL in the Polkadot ecosystem after
winning the fourth Kusama parachain slot by locking up more than $239 million
worth of KSM tokens. Besides this, Parallel Finance is backed by industry
leaders like Lightspeed, Polychain Capital, Alameda Research, and Blockchain
Capital.
How Attack Surface Management Preempts Cyberattacks
ASM is a technology that either mines Internet datasets and certificate
databases or emulates attackers running reconnaissance techniques. Both
approaches aim at performing a comprehensive analysis of your organization's
assets uncovered during the discovery process. Both approaches include scanning
your domains, sub-domains, IPs, ports, shadow IT, etc., for internet-facing
assets before analyzing them to detect vulnerabilities and security gaps.
Advanced ASM includes actionable mitigation recommendations for each uncovered
security gap, recommendations ranging from cleaning up unused and unnecessary
assets to reduce the attack surface to warning individuals that their email
address is readily available and might be leveraged for phishing attacks. ASM
includes reporting on Open-Source Intelligence (OSINT) that could be used in a
social engineering attack or a phishing campaign, such as personal information
publicly available on social media or even on material such as videos, webinars,
public speeches, and conferences.
6 reasons we need to start thinking about quantum computing now
Companies are exploring applications that could help with portfolio
optimization, secure communications, transaction settlements and ultrafast
trading platforms. ... With quantum computing, they crunched the data in less
than three minutes, as compared with 30 hours with a traditional computer. ...
Today’s customers expect high degrees of personalization, and quantum computing
can help deliver on that expectation — again through its unique power to analyze
huge numbers of potential combinations of options or solutions. “There’s clearly
a trend toward the idea of ‘bank of me,’ ” Flinter says. “Customers are looking
for highly personalized solutions, and I think quantum becomes a part of that
solution.” ... In the past few years, quantum computing has moved from the
research lab into engineering, and it can quickly solve important, complex
problems as it simultaneously considers all possible solutions. Though likely
years away, bad actors using quantum computing’s power may be able to more
easily decrypt messages sent using existing public-key cryptography and
ultimately compromise the security of key systems that are not
quantum-proofed.
Quantum Complexity Tamed by Machine Learning
A major goal of DFT research is to find more accurate approximations of that
universal functional. John Perdew, a physicist at Temple University and a
leading functional developer, has long spearheaded this work. He describes the
path toward the universal functional as like climbing the rungs on a ladder. On
each rung, physicists add new ingredients to the functional. The simplest
ingredient is just the thickness of the electron stew in each location. On the
next rung, the functional also considers how quickly the thickness changes from
place to place, giving researchers a broader view and making the functional more
precise. A key part of Perdew’s strategy is to use physical reasoning to
identify certain mathematical properties that good approximations must obey,
known as “exact constraints.” Higher rungs satisfy more of these constraints,
and researchers have to search harder to find equations that obey them all.
Perdew’s group started tackling third-rung functionals, which blend six
ingredients, in 1999, and in 2015, he released a state-of-the-art functional
called SCAN. It was his eighth attempt, and the first to obey all 17 known
constraints relevant on the third rung.
To save independent journalism, media must embrace web3 innovation
There’s been a lot of talk about journalism and artificial intelligence (AI).
Importantly, news organizations have been concretely working on a wide variety
of AI solutions, from content recommendation and moderation to advanced
analytics, deep-fake detection and optimizing subscription pipelines. But have
we seen anything truly disruptive and transformative yet? Something that will
really move the needle for news organizations in the longer run, giving them a
business advantage in the digital information ecosystem? Adoption of AI
technologies is still slow in the field partly due to the high cost of
development. Additionally, news media needs more use cases and business cases
for AI that have been born out of pure journalistic thinking and need. What
about web3 and metaverse, and their combination? So far, news organizations
haven’t actively explored or developed solutions for these emerging digital
ecosystems. Yes, there is a lot of hype and misconception related to both, but
it doesn’t mean that web3 and metaverse won’t become “the next big thing.”
Detect active network reconnaissance with Microsoft Defender for Endpoint
Spending quality time on reconnaissance is guaranteed to pay dividends at
subsequent stages of the cybersecurity kill chain and is a crucial indicator
from which to detect malicious activity at the earliest possible stages of an
attack. Unfortunately, it is also a focus area that is overlooked by security
professionals in favor of exotic phases of an attack such as weaponization,
delivery, and exploitation. This is because it can be notoriously difficult to
detect reconnaissance attacks—as they are often passive—executed in the public
domain and external to the victim’s network. Job postings, domain registrars,
and financial reporting are great resources to gain context on a target, but due
to their nature, it can be a challenge to even seasoned security operations
teams to detect and investigate this type of attack. Fortunately, there is a
certain point where passive activities can have diminishing returns as the data
points produced can be too broad to act upon. This can drive an attacker to
consider the use of active reconnaissance which has dependencies on the endpoint
or human interaction.
5 Reasons You Don’t Always Need a JavaScript Framework
With the release of JavaScript ES6, the necessity for frameworks isn’t nearly as
great as it once was. And with the inclusion of modules and classes with ES6,
most of the popular frameworks could be thought of as obsolete. Remember,
frameworks are used to abstract some of the more complex aspects of development.
With the release of ES6, a number of new features (such as default parameters,
template literals, multi-line strings, destructuring assignment, enhanced object
literals, and arrow functions — along with modules and classes), reduces the
need to even bother with frameworks for many use cases. Prior to ES6, working
with things like classes was a major challenge, even though previous iterations
were designed to specifically support classes. These new features of JavaScript
go a long way towards making frameworks a thing of the past, because they bring
certain functionalities to the language that were previously unavailable.
Instead of having to employ those third-party tools, most everything will be
pre-packaged within the language itself.
Web3: Empty Buzzword Or The Next Evolution Of The Web?
Web3 is the vision to flip this paradigm on its head. The end goal is a
re-architecture of the internet enabling users to own their data in
decentralized environments through the use of open source protocols and
applications. This model may eliminate the need for centralized gatekeepers, or
at least reduce reliance on individual companies. If this vision is properly
manifested, data would be ownable and easily transferable by users, and users
would be compensated directly for contributing to the network. Web3 aims to make
users “uncancellable” as it strips power away from centralized service providers
that can unilaterally deplatform users and disconnect them from their audiences.
This empowers users to more freely express themselves, produce content and have
interactions without fear of personal or monetary consequences, increasing value
for all participants within a network. This can even have political
ramifications as it may encourage activists and dissidents to pursue their goals
more openly and vigorously.
Quote for the day:
"When you expect the best from people,
you will often see more in them than they see in themselves." --
Mark Miller
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