November 03, 2023

Embracing the co-evolution: AI's role in enriching the workforce

AI's capabilities in data processing and predictive analytics are undeniably impressive, yet it falls short in embodying human experience–empathy, contextual comprehension, and emotional intelligence. This raises the question: what can AI achieve without human involvement? For example, several automotive companies are adopting LLMs into their vehicles and systems. They use it to conduct routine checks and assist with on-road safety and predictive maintenance. But in this case, AI cannot fix any of the problems that it detects. To ensure that the challenges detected by AI are addressed, businesses will always need skilled human workers. ... If things with AI aren’t that bad, why is the popular narrative suggesting otherwise? The simple answer is, timing. The economic conditions coupled with the aftermath of the pandemic has left people bracing themselves for the next big disruption. Add the popularity of LLMs into the mix, and you have what seems like the next catastrophe. But that’s far from the truth.

Burnout: An IT epidemic in the making

Even among those who report low or moderate levels of burnout, 25% express a desire to leave their company in the near future. And burnout is also impacting skills acquisition, as 43% of Yerbo survey respondents said they had to stop studying for a certification exam because they were unable to find time due to their workloads. Further, burned-out employees who do leave are highly likely to negatively impact your company’s reputation by sharing their frustrations online and on review sites, where other potential candidates can see them. With tech talent markets always tight, increased burnout within your organization can quickly become not only a retention issue, but a recruitment problem as well. ... Burnout can’t be fixed overnight. Turning around burnout in your organization will require consistency and dedication to improving the employee experience. You’ll need to consider increases in resources, mentoring, opportunities for advancement, as well as evaluating boundaries around work-life balance and ensuring that a healthy balance is reflected and modeled all the way to the top.

Edge and beyond: How to meet the increasing demand for memory

What is needed is a way to improve direct access to offboard memory by providing on-demand access to memory across servers. The industry has recognized this and has been working on a software-defined memory solution for many years in the form of CXL. However, CXL 3.0, which provides complete caching capability, is still several years away, will require new server architecture, and will only be available in forthcoming generations of hardware. Concerns about latency compromises are surfacing, too. Even CXL 3.0 is still piggybacking on the PCI Express (PCIe) physical layer and relying on physical memory paired with PCIe, so one would ordinarily incur a penalty on a key critical metric—latency. Generally, the farther the memory is from the CPU, the higher the latency and the poorer the performance. Workloads at the heart of everything from HPC to AI have significant memory requirements. But designers struggle to make use of the additional cores available in modern CPUs. The leap forward in the number of CPU cores is mismatched with a lack of memory bandwidth.

The False Dichotomy of Monolith vs. Microservices

Sure, microservices are more difficult to work with than a monolith -- I’ll give you that. But that argument doesn’t pan out once you’ve seen a microservices architecture with good automation. Some of the most seamless and easy-to-work-with systems I have ever used were microservices with good automation. On the other hand, one of the most difficult projects I have worked on was a large old monolith with little to no automation. We can’t assume we will have a good time just because we choose monolith over microservices. Is the fear of microservices a backlash to the hype? Yes, microservices have been overhyped. No, microservices are not a silver bullet. Like all potential solutions, they can’t be applied to every situation. When you apply any architecture to the wrong problem (or worse, were forced to apply the wrong architecture by management), then I can understand why you might passionately hate that architecture. Is some of the fear from earlier days when microservices were genuinely much more difficult??

The Software Testing Odyssey That You Need to Take

Let’s illustrate a practical scenario where a financial services company is adding new transactional functionalities to its application. Its team uses AI-powered test creation to transform its user stories and requirements into functional test scripts. The AI uses natural language processing to analyze descriptions of test requirements and convert them into executable scripts that simulate user interactions within the banking application. During testing, which is automated and runs at predefined times, a minor application layout UI change occurs. This results in a number of tests failing as the pre-existing automated tests cannot locate the update element. This is where AI-powered self-healing comes in. The AI algorithm, powered by classification AI techniques, will inspect the failed tests meticulously and compare them with previous test versions. Through this analysis, the AI identifies the UI element change that caused the failures and autonomously updates the test scripts with new locators for the UI element changes.

3 Ways of Protecting Your Public Cloud Against DDoS Attacks

While basic DDoS protection offered by CSPs is free, more advanced, or comprehensive protection options come with additional costs. This becomes quite expensive because you will need to pay a monthly fee for each account or resource, and if you need more visibility into the traffic, you must turn on and pay for an additional service. All the additional charges add up quick and turn out to be quite expensive. Best for: All in all, the native DDoS protection offered by cloud service providers offers basic protection which provides good coverage for most network-layer attacks. This will be good for those looking for cheap, no hassle, integrated protection with low latency. ... Third-party DDoS mitigation services are best for organizations looking for dedicated, advanced DDoS protection, particularly of missions-critical applications. It is also suitable for organizations which are frequently attacked, and need constant, high-grade protection. In summary, DDoS protection is a fundamental component of cybersecurity in public cloud environments.?

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