October 17, 2022
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | GRC Consulting | Independent Director | Enterprise & Solution Architecture | Former Sr. VP & CTO of MF Utilities | BU Soft Tech | itTrident
“The metaverse presents an opportunity to more fully transcend our physical limitations,” says Anand Srivatsa, CEO of Tobii. “Technologies like eye tracking will play a critical role in helping reduce the need for compute and networking power, which are required to deliver lifelike, immersive virtual environments. Eye tracking will also help users express their attention and intent in more realistic ways when they’re in the digital universe.” ... If human-digital devices enable the experience, and infrastructure supports metaverse-scale interactivity, then it’s how real the experience feels to users that will be the primary innovation and differentiator. To start, organizations will need strong dataops capabilities, and machine learning models will likely require synthetic data generation. Zuk continues, “Businesses looking to make waves in the metaverse usually begin by establishing a robust data pipeline—with synthetic data as the primary resource driving the development life cycle.” Bart Schouw, chief evangelist at Software AG, agrees.
Phishing-as-a-service is a fairly new phenomenon, this trend is where the cybercriminal actually takes the role of a service provider, carrying out attacks for others instead of just for themselves in exchange for a sum of money. PaaS only serves to show how hackers are becoming better organized and looking for greater monetisation from ransomware. Instead of threat actors being required to have technical knowledge of building or taking over infrastructure to host a phishing kit (login page emulating known login interfaces like Facebook/Amazon/Netflix/OWA), the barrier to entry is significantly lowered with the introduction of PaaS. ... Phishing-as-a-service can be very advanced, with capabilities spanning from detecting sandbox environments, to fingerprinting user agents in order to determine whether you might be a researchers bot. That being said, Web Content Filters can often limit the exposure of users.
Automation plays a significant role in transforming the world. It has stimulated various transformations in business, resulting in sustained proficiency. In the past few years, the best automation capabilities have been provided by the industrialisation of big data analytics. The process of Analytic Process Automation (APA) encourages growth by providing prescriptive and predictive abilities along with other insights to businesses. Through this, businesses have been able to receive excellence with efficient results and low costs. Analytic Process Automation mainly enhances computing power to make good right decisions. Data analytics automation can be considered a perfect disruptive force. Big data analysis helps substantially with stimulating valuable data usage and productivity. ... Data Governance handles data access all over the world. General Data Protection Regulation (GDPR) compliance has various organizations and businesses that prioritize data governance and handles the data of consumers.
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The main problem with technical debt is that code lacks visibility. Code is an abstract concept that isn’t accessible to all members of your organization. Hence, it’s easy to ignore technical debt even if we are aware of the general problem. Quantifying and visualizing the situation in your codebase is key, both for the engineering teams as well as for product and management. Visualisations are wonderful as they let us tap into the most powerful pattern detector that we have in the known universe: the human brain. I explored the concept at depth in Your Code as a Crime Scene, and founded CodeScene back in 2015 to make the techniques available to a general audience. ... With code health and hotspots covered, we have everything we need for taking it full circle. Without a quantifiable business impact, it’s hard to make the case for investing in technical debt paydowns. Any measures we use risk being dismissed as vanity metrics while the code continues to deteriorate. We don’t want that to happen.
Those at the cutting edge of ML are increasingly turning to synthetic data to circumvent the numerous constraints of original or real-world data. For instance, company Synthesis AI offers a cloud-based generation platform that delivers millions of perfectly labeled and diverse images of artificial people. Synthesis AI has been able to accomplish many challenges that come with the messy reality of original data. For a start, the company makes the data cheaper. ... The challenges of real-world data don’t end there. In some fields, huge historical bias pollutes data sets. This is how we end up with global tech behemoths running into hot water because their algorithms don’t recognize black faces properly. Even now, with ML technology experts acutely aware of the bias issue, it can be challenging to collate a real-world dataset entirely free of bias. Even if a real-world dataset can account for all of the above challenges, which in reality is hard to imagine, data models need to be improved and tweaked constantly to stay unbiased and avoid degradation over time. That means a constant need for fresh data.
It’s obvious that a poor developer experience creates a negative impact throughout an entire company. If developers aren’t producing good work due to unhappiness, illness or burnout, it’s likely that organizations aren’t staying at the cutting edge or offering competitive products in the market. A demoralized team can have a really negative business impact, and it can even change the way that people outside the company feel about it. An unhappy team isn’t going to lead to much creativity or productivity. As a way to combat this growing trend, companies are looking left and right for solutions. Some companies are reaching for things like extra PTO days, a full month off, better benefits, pay raises, and more fun work culture or relaxed dress codes. Those things are nice to have, and we’re certainly not speaking ill of any organization trying something new to help their employees. But at the end of the day, if the overwork and unrealistic expectations remain, the developer burnout will remain too.