Asked about the potential for a Russia-Ukraine cyber conflict spreading to the UK, Edwards said: “We have picked up on that heightened threat environment and we think it’s really important to take the opportunity to remind businesses of the importance of security over the data that they hold. This is a different era from blacking out the windows and keeping the lights off. The threats are going to come in through your inbox.” Edwards said that outside the Ukraine conflict and the warnings it had brought of a heightened security threat, the Information Commissioner’s Office had seen a “steady and significant” increase in cyber-attacks against UK businesses over the past two years. Between July and December last year the ICO recorded 1,345 “cybersecurity incidents”, including ransomware attacks, where assailants demand payment in cryptocurrency to decrypt a target’s computers, and phishing attacks, where the victim is tricked, often via email, into downloading malware or handing over their login details.
After companies are successful at initial proofs of concept, they often build AI centers of excellence to operationalize the technology and build talent, expertise, and best practices. But once a company reaches a level of critical mass, then it makes sense to break up some of these centers of excellence and federate AI, moving experts directly into the business units where they are needed most. “For those companies that are less mature, there is value in having a center of excellence that is housing talent and learning across the institution,” says McKinsey’s Singla. “Without that, companies usually don’t have the ability to scale. Talented people want to be with other like-minded people. And less experienced people benefit from being in a center of excellence because they can grow or learn.” Distributing them too early would dilute their impact and reduce a company’s ability to iterate and duplicate successful projects across multiple business lines. “But as you get to a layer of maturity and scale, longer-term, the benefit of technologists having both a deep AI expertise and domain expertise is a real home run,” he says.
If and when AI reaches the point where it can continually improve itself, the fate of our species could depend on the actions of this superintelligent machine, warns Nick Bostrom, a University of Oxford philosopher, in his book Superintelligence: Paths, Dangers, Strategies. Yet that fate might not necessarily be a dismal one. The experts also point out that superintelligent AI could offer a solution to many of our problems. If we can’t figure out how to tackle climate change, eradicate poverty and ensure world peace, perhaps AI can. “This remarkable technology has the potential to help everybody live healthy, wealthy lives so humanity can flourish like never before,” says Tegmark, who is also the founder of the Future of Life Institute, an organization that aims to ensure these positive outcomes. Yet, he adds, it “might wipe out humanity if its goals aren’t aligned with ours.” Or as Bostrom put it in Superintelligence, when it comes to confronting an intelligence explosion, “We humans are like small children playing with a bomb.”
The attack technique that the researchers at NC State developed involves a vulnerability in a Microsoft implementation of fully homomorphic encryption called Microsoft Simple Encrypted Arithmetic Library (SEAL). Microsoft SEAL is a collection of encryption libraries for performing computing operations on encrypted data. The vulnerability, which the researchers have described as a "power-based side-channel leakage" is present in the SEAL homomorphic encryption library through version 3.6 of the technology, according to the researchers. It enables attackers to use a single power measurement from the device doing the encryption operations to extract data in plaintext while the data is being homomorphically encrypted. The vulnerability allows attackers to listen to the machine doing the encryption and infer if a 0 bit is being processed or a 1 bit, Aysu says. "It's a few lines in the software code that give out the data being executed on the device," he says. "This information allows us to use some fancy equations and figure out the secret messages being encrypted in a homomorphic encryption scheme."
Big, centralized application backends just could not provide the flexibility required to scale from thousands to millions of requests per second. Most of us probably can remember at least a couple of cases when “monolithic” web applications were experiencing severe performance issues after going viral. The solution to this problem came from adapting an approach where organizations split these monoliths into smaller “micro” services running on docker containers that can be horizontally scaled both independently of each other and much quicker than monoliths. With each microservice adding to the demand on development operations, this strategy, however, wouldn’t be so successful without container orchestration frameworks like Kubernetes. Introduced publicly in 2014, Kubernetes, formerly known inside Google as Borg, quickly proved itself as a top choice for automating deployment workflows and today is one of the industry standards for modern development operations. Also, being an open source, cloud native component, Kubernetes continues to evolve and improve.
The rise in creative energy has inspired the developer community as well. New niche streaming platforms have grown up, helped by the emergence of low-cost decentralized infrastructure that allows application builders to encode video, store data and handle identity without having to pay expensive centralized cloud providers for such services. These centralized providers will increasingly find themselves on the defensive. Two attention-grabbing incidents in 2021 are illustrative: Hackers attacked Twitch and released private information about its code and its users to the world. And, Facebook suffered colossal reputational damage from a lengthy outage and whistleblower claims that its management has repeatedly chosen to prioritize profit over safety. Big Tech’s woes and pandemic-related restrictions have sped up fundamental changes already underway in how the world produces, consumes and uses video content — changes likely to propel growth in the creator economy well into the future.
One project with interoperability at its heart is Spherium. Not only has the startup developed a cross-chain bridge, but its incubation program HyperLaunch facilitates the seamless entry of innovative blockchain projects into the cross-chain ecosystem. Spherium also has its own cross-chain DEX, which supports trading among tokens between EVM and Non-EVM compatible chains. To date, Spherium has partnered with leading NFT, DeFi, P2E, and general blockchain projects. The alliance seeks to “expand the multi-chain experience for creators and buyers to bridge major blockchains and add certain defi functionalities into their platform.” Through HyperLaunch, Spherium offers projects the opportunity to integrate a bridge solution into their core functionality and enable the deployment of their native tokens on different networks. With the audited Spherium bridge, token swaps can take less than one minute currently and is free to use for projects in the HyperLaunch program. Geared towards defi, NFT and meta-world platforms, the incubation program offers more than just bridge access; staking and dual-farming solutions are also provided, along with extensive technical support.
In light of the "Great Resignation" and unprecedented job mobility in part sparked by the pandemic, such data about job happiness is "top of mind for investors today," Lopata said. Another timely use for alternative data is tracking how inflation in the U.S. is disrupting markets. Thinknum is following used car sales on CarMax and Carvana, two of the big auto sales apps. "We're tracking all that data in real time down to a VIN number, so that allows you to understand whether prices are peaking," Lopata said. "Beyond just tracking the peaks … we're tracking when the peak ends." "We're able to identify that in January '22, we finally started to see some decrease in pricing," she added. Other current market trends for which Thinknum is digging up alternative data include changes in the food delivery services business and cryptocurrency price fluctuations, where the vendor has discovered that GitHub, the provider of internet hosting for software development, is a prime source of data. "We've been looking at where we can find a signal before it hits the market," Lopata said.
Technology that allows companies to analyze and deliver data where it’s needed and at the right time is crucial to producing a better customer experience. To achieve this, companies need a data architecture that provides a highly granular view of their customers. The architecture must be flexible and adaptable, so new data can be incorporated and changes can be made without causing major technological upheavals. The problems we face chasing omniscience about customers are constantly evolving. The tools and solutions evolve to keep pace. The data architecture we implement must handle these changes in a forgiving manner. Additionally, the architecture must make data available to developers, analysts, and other staff to use whenever they need it in a way that protects the integrity and security of the individual data event. A data fabric brings together data of all forms — from the edge to the cloud — and provides services for discovery, governance, quality, and transformation. This architecture truly puts data to use at scale to improve customer experiences.
Quote for the day:
"Don't let a bad day make you feel like you have a bad life." -- Joubert Botha