Daily Tech Digest - February 18, 2023

Oracle outages serve as warning for companies relying on cloud technology

“Oracle engineers identified a performance issue within the back-end infrastructure supporting the OCI Public DNS API, which prevented some incoming service requests from being processed as expected during the impact window,” the company said on its cloud infrastructure website. In an update, the company said it implemented "an adaptive mitigation approach using real-time backend optimizations and fine-tuning of DNS Load Management to handle current requests." Oracle said that the outage caused a variety of problems for customers. OCI customers using OCI Vault, API Gateway, Oracle Digital Assistant, and OCI Search with OpenSearch, for example, may have received 5xx-type error or failures (which are associated with server problems), Oracle said. Identity customers may have experienced issues when creating and modifying new domains. In addition, Oracle Management Cloud customers may have been unable to create new instances or delete existing instances, Oracle said. Oracle Analytics Cloud, Oracle Integration Cloud, Oracle Visual Builder Studio, and Oracle Content Management customers may have encountered failures when creating new instances.

EU parliamentary committee says 'no' to EU-US data privacy framework

In particular, the committee noted, the executive order is too vague, and leaves US courts — who would be the sole interpreters of the policy — wiggle room to approve the bulk collection of data for signals intelligence, and doesn’t apply to data accessed under US laws like the Cloud Act and the Patriot Act. The parliamentary committee's major points echoed those of many critics of the deal in the EU, as well as the criticsm of the American Civil Liberties Union (ACLU), which has said that the US has failed to enact meaningful surveillance reform. ... In short, the committee said that US domestic law is simply incompatible with the GDPR framework, and that no agreement should be reached until those laws are more in alignment. The committee’s negative response this week to the proposed data privacy framework, however, was a nonbinding draft resolution and though it is a sticking point, does not put a formal halt to the adoption process, as its approval was not required to move the agreement along.

How edge devices and infrastructure will shape the metaverse experience

Cloud-native edge infrastructure can address these shortcomings and provide optimized service chaining. It can handle a tremendous amount of data processing while delivering cost-effective, terabit-scale performance and reduced power consumption. In doing so, edge computing can move past closed networking models to meet the demanding data processing requirements of the metaverse. “Edge computing allows data to be processed at or near the data source, implying that commands and processes will occur promptly. As the metaverse will require massive data simultaneously, processing data quickly and seamlessly depends on proximity,” Prasad Joshi, SVP and head of emerging technology solutions at Infosys, told VentureBeat. “Edge computing offers the ability to process such information on a headset or on the device, thereby making that immersive experience much more effective.” ... The power, space and cooling limitations of legacy architecture further exacerbate this data surge. While these challenges impact consumer-based metaverse applications, the stakes are much higher for enterprise use cases.

The New AI-Powered Bing Is Threatening Users. That’s No Laughing Matter

It’s not a Skynet-level supercomputer that can manipulate the real world. ... Those feats are impressive. But combined with what appears to be an unstable personality, a capacity to threaten individuals, and an ability to brush off the safety features Microsoft has attempted to constrain it with, that power could also be incredibly dangerous. Von Hagen says he hopes that his experience being threatened by Bing makes the world wake up to the risk of artificial intelligence systems that are powerful but not benevolent—and forces more attention on the urgent task of “aligning” AI to human values. “I’m scared in the long term,” he says. “I think when we get to the stage where AI could potentially harm me, I think not only I have a problem, but humanity has a problem.” Ever since OpenAI’s chatbot ChatGPT displayed the power of recent AI innovations to the general public late last year, Big Tech companies have been rushing to market with AI technologies that, until recently, they had kept behind closed doors as they worked to make them safer.

Machines Are Dreaming Instead of Learning

The question is—how much of the ‘data problem’ is about the quantity versus the quality of data? To deal with this data scarcity or quantity, people are moving away from accessing and using real data towards using synthetic data. In a nutshell, synthetic data is artificially generated data, either mathematically or statistically, which appears close to real-world data. This also increases the amount of data which, in turn, increases the accuracy of each model and removes all the existing flaws in the data. There are many positive reasons to be attracted towards synthetic data such as data privacy. ... One of the reasons that synthetic data is on the rise is to tackle the bias that is present in smaller datasets. Even though larger datasets can have poor quality data—which would require higher fine-tuning and heavier workloads—synthetic data does not represent the quality and the amount of variability that is present within real-world data. Synthetic data is generated using algorithms that model the statistical properties of real data.

Making Microservices Just the Right Size

By attempting to make smaller and simpler services, applications have become more complex. The smaller service size is a great benefit to the individual development team that owns that service, but the complex interconnection between services has made the overall system architecture more involved. We’ve essentially moved the complexity uphill. Rather than individual developers dealing with complexity at the code level, system architects deal with the complexity at the system level. Thus, services that are too large are difficult to build and understand at scale. Services that are too small simply move the complexity up to the system level. The goal, therefore, is to find the right size. It’s like the story of Goldilocks and the Three Bears; finding the right size for your services is challenging, and often involves trial and error. It’s easy to build them too big or too small. Finding the Goldilocks size can be challenging. How do you find the Goldilocks size for your microservices? The answer depends a lot on your organization and your application.

4 Ways To Be A Learning Leader

Constant curiosity makes learning simply part of you and your way of being. If you're motivated and hungry to improve your skills and knowledge, you'll learn more successfully. Professor and researcher Francesca Gino wrote, “When our curiosity is triggered, we think more deeply and rationally about decisions and come up with more-creative solutions.” Additionally, developing and demonstrating a genuine interest in people and their perspectives and interests enriches all your relationships. Start by asking yourself what you're curious about, then think about all the topics that extend from that. If this still feels hard, set an intention to ask one other-oriented question per meeting or interaction. We all consume and digest information and learning differently. Think about how you prefer to learn in given contexts. For example, do you like to just go for it? Do you like talking to other leaders, coaches or mentors? Maybe you like podcasts or reading books and articles. Discover what works best for your learning.

Malware authors leverage more attack techniques that enable lateral movement

"An increase in the prevalence of techniques being performed to conduct lateral movement highlights the importance of enhancing threat prevention and detection both at the security perimeter as well as inside networks," researchers from cybersecurity firm Picus, said in their report. Many years ago lateral movement used to be associated primarily with advanced persistent threats (APTs). These sophisticated groups of attackers are often associated with intelligence agencies and governments, whose primary goals are cyberespionage or sabotage. To achieve these goals these groups typically take a long time to understand the network environments they infiltrate, establish deep persistence by installing implants on multiple systems, they identify critical servers and sensitive data stores and try to extract credentials that gives them extensive access and privilege escalation. APTs also used to operate in a targeted manner, going to specific companies from specific industries that might have the secrets their handlers are looking for.

The cost and sustainability of generative AI

More demand for AI means more demand for the resources these AI systems use, such as public clouds and the services they provide. This demand will most likely be met with more data centers housing power-hungry servers and networking equipment. Public cloud providers are like any other utility resource provider and will increase prices as demand rises, much like we see household power bills go up seasonally (also based on demand). As a result, we normally curtail usage, running the air conditioning at 74 degrees rather than 68 in the summer. However, higher cloud computing costs may not have the same effect on enterprises. Businesses may find that these AI systems are not optional and are needed to drive certain critical business processes. In many cases, they may try to save money within the business, perhaps by reducing the number of employees in order to offset the cost of AI systems. It’s no secret that generative AI systems will displace many information workers soon.

6 quantum computing questions IT needs to ask

The challenge is the older systems' data format and fields may not be compatible with newer systems. In addition, the fields and tables might not contain what you'd expect. There is also the complexity of free text fields that store keywords. Do not underestimate the challenge of making existing data available for quantum application to work with. ... The important question in developing quantum applications is finding tools that can provide a 10-year lifespan with guaranteed software support. There are many open source tools for quantum-based application development. A company could take on one (or more) open source projects, but this can be a challenge and a costly commitment. The issue is not only keeping your software up to date (and retaining staff to develop it) but also to develop quantum software that's compatible with the rest of your IT environment. When considering lifespan, consider abandoned open source projects for quantum software applications.

Quote for the day:

"Leadership is an opportunity to serve. It is not a trumpet call to self-importance." -- J. Donald Walters

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