June 18, 2023
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | GRC Consulting | Independent Director | Enterprise & Solution Architecture | Former Sr. VP & CTO of MF Utilities | BU Soft Tech | itTrident
Penetration testing has evolved significantly over the past few years, with a growing emphasis on mimicking real-life cyberattack scenarios for greater accuracy and relevance. By adopting more realistic simulation strategies, pen testers aim to emulate threats that an organization might realistically face in their operational environment, thereby providing valuable insights into susceptibilities and vulnerabilities. This approach entails examining an organization’s infrastructure from multiple angles, encompassing technological weaknesses as well as human factors such as employee behavior and resistance to social engineering attacks. ... With cyber threats constantly scaling and tech landscapes evolving at a rapid pace, automation enables organizations to efficiently identify potential weaknesses without sacrificing accuracy or thoroughness. Automated tools can expedite vulnerability assessment processes by scanning networks for known flaws or misconfigurations while continuously staying up-to-date with emerging threat information, significantly reducing manual workloads for security teams.?
In general, the microservice-based approach requires that architects and developers determine exactly which microservices to build, which is not an easy task. Software teams must carefully assess how to achieve the best balance between application complexity and modularity when designing a microservices application. There are also few standards or guidelines that dictate the exact number of individual microservice modules an application should embody. While including too many microservices can add unnecessary development and operations overhead as well as compromise the architecture's flexibility, a headless architecture is much easier to design since there is still a clear definition between the front and the backend. Division of responsibilities will remain much clearer, and the relationship between components is less likely to get lost in translation. A single microservice-based application can easily represent dozens of individual services running across a complex cluster of servers. Each service must be deployed and monitored separately because each one could impact the performance of other microservices.?
Bringing our unconscious mind into alignment and reconciliation with our conscious mind requires a level of self-awareness that many people are unable to achieve independently. Individuals who are struggling with achieving goals and don’t know why may find it helpful to work with an objective outside observer, such as a therapist or a professional coach, who can help them identify thought and behavior patterns that may be holding them back from advancing in work or life. Ultimately, to break out of these self-limiting beliefs, it’s important to change one’s thinking, particularly in areas when self-abnegating thoughts have been dominating our lives for far too long. When I’m working with clients, I try to help them develop what’s called a “growth mindset”—that is, an inherent belief in one’s own ability to constantly learn new skills, gain new capabilities and improve. People who have a growth mindset do not see failures as the end of the road, or as confirmation of the self-limiting, critical beliefs they’ve internalized throughout their lives.
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AI is one of the significant tools left in the fight against climate change. AI has turned its hand to risk prediction, the prevention of damaging weather events, such as wildfires and carbon offsets. It has been described as vital to ensuring that companies meet their ESG targets. Yet, it’s also an accelerant. AI requires vast computing power, which churns through energy when designing algorithms and training models. And just as software ate the world, AI is set to follow. AI will contribute as much as $15.7 trillion to the global economy by 2030, which is greater than the GDP of Japan, Germany, India and the UK. That’s a lot of people using AI as ubiquitously as the internet, from using ChatGPT to craft emails and write code to using text-to-image platforms to make art. The power that AI uses has been increasing for years now. For example, the power required to train the largest AI models doubled roughly every 3.4 months, increasing 300,000 times between 2012 and 2018. This expansion brings opportunities to solve major real-world problems in everything from security and medicine to hunger and farming.
When the Denodo Platform and Tableau GPT are integrated, Tableau customers can unlock several key benefits, including: Data Unification: The Denodo Platform’s logical data management capabilities provide Tableau GPT with a unified view of data from diverse sources. By integrating data silos and disparate systems, organizations can access a comprehensive, holistic data landscape within Tableau. The elimination of manual data consolidation simplifies the process of accessing and analyzing data, accelerating insights and decision-making. This significantly reduces the need for manual effort and enhances efficiency in data management. Expanded Data Access: The Denodo Platform’s ability to connect to a wide range of data sources means Tableau GPT can leverage an extensive array of structured and unstructured data. With connections to over 200 data sources, the Denodo Platform lets organizations tap into a comprehensive, distributed data ecosystem as easily and simply as connecting to a single data source.
Quantum computers have been an exciting tech development in recent times. They are exponentially faster than classical computers which makes them suitable for several applications in a wide variety of areas. However, they are still in their nascent stage of development, and even the most sophisticated machines are limited to a few hundred qubits. There is also the inherent problem of random fluctuations or noise—the loss of information held by qubits. This is one of the chief obstacles in the practical implementation of quantum computers. As a result, it takes more time for these noisy intermediate-scale quantum computers to perform complex calculations. Even the most basic reaction of CO2 with the simplest amine, ammonia, turns out to be too complex for these NISQs. VQE utilises a quantum computer to estimate the energy of a quantum system, while using a classical computer to optimise and suggest improvements to the calculation. One possible remedy to this problem is to combine quantum and classical computers, to overcome the problem of noise in quantum algorithms.?
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1 年Jagan Chennaiyan
Next Trend Realty LLC./wwwHar.com/Chester-Swanson/agent_cbswan
1 年Thanks for posting.