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.
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.
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.
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.
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.
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.
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.”
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.
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