Daily Tech Digest - August 07, 2024

Should You Buy or Build an AI Solution?

Training an AI model is not cheap; ChatGPT cost $10 million to train in its current form, while the cost to develop the next generation of AI systems is expected to be closer to $1 billion. Traditional AI tends to cost less than generative AI because it runs on fewer GPUs, yet even the smallest scale of AI projects can quickly reach a $100,000 price tag. Building an AI model should only be done if it’s expected that you will recoup building costs within a reasonable time horizon. ... The right partner will help integrate new AI applications into the existing IT environment and, as mentioned, provide the talent required for maintenance. Choosing an existing model tends to be cheaper and faster than building a new one. Still, the partner or vendor must be vetted carefully. Vendors with an established history of developing AI will likely have better data governance frameworks in place. Ask them about policies and practices directly to see how transparent they are. Are they flexible enough to make said policies align with yours? Will they demonstrate proof of their compliance with your organization’s policies? The right partner will be prepared to offer data encryption, firewalls, and hosting facilities to ensure regulatory requirements are met, and to protect company data as if it were their own.


Business Data Privacy Standards and the Impact of Artificial Intelligence on Data Governance

Artificial intelligence technologies, including machine learning and natural language processing, have revolutionized how businesses analyze and utilize data. AI systems can process vast amounts of information at unprecedented speeds, uncovering patterns and generating insights that drive strategic decisions and operational efficiencies. However, the use of AI introduces complexities to data governance. Traditional data governance practices focused on managing structured data within defined schemas. AI, on the other hand, thrives on vast swaths of information and can generate entirely new data. ... As AI continues to evolve, so too must data governance frameworks. Future advancements in AI technologies, such as federated learning and differential privacy, hold promise for enhancing data privacy while preserving the utility of AI applications. Collaborative efforts between businesses, policymakers, and technology experts are essential to navigate these complexities and ensure that AI-driven innovation benefits society responsibly. 


Foundations of Forensic Data Analysis

Forensic data analysis faces a variety of technical, legal, and administrative challenges. Technical factors that affect forensic data analysis include encryption issues, need for large amounts of disk storage space for data collection and analysis, and anti-forensics methods. Legal challenges can arise in forensic data analysis and can confuse or derail an investigation, such as attribution issues stemming from a malicious program capable of executing malicious activities without the user’s knowledge. These applications can make it difficult to identify whether cybercrimes were deliberately committed by a user or if they were executed by malware. The complexities of cyber threats and attacks can create significant difficulties in accurately attributing malicious activity. Administratively, the main challenge facing data forensics involves accepted standards and management of data forensic practices. Although many accepted standards for data forensics exist, there is a lack of standardization across and within organizations. Currently, there is no regulatory body that overlooks data forensic professionals to ensure they are competent and qualified and are following accepted standards of practice.


Closing the DevSecOps Gap: A Blueprint for Success

Businesses need to start at the top and ensure all DevSecOps team members accept a continuous security focus: Security isn't a one-time event; it's an ongoing process. Leaders must encourage open communication between development, security, and operation teams, which can be achieved with regular meetings and shared communication platforms that facilitate constant collaboration. Developers must learn secure coding practices when building their models, while security and operations teams need to better understand development workflows to create practical security measures. Peer-to-peer communication and training are about partnership, not conflict, and effective DevSecOps thrives on collaboration, not finger-pointing. Only once these personnel changes are implemented can a DevSecOps team successfully execute a shift left security approach and leverage the benefits of technology automation and efficiency. Once internal harmony is achieved, DevSecOps teams can begin consolidating automation and efficiency into their workflows by integrating security testing tools within the CI/CD pipelines. 


How micro-credentials can impact the world of digital upskilling in a big way

Micro-credentials, when correctly implemented, can complement traditional degree programmes in a number of ways. Take for example the Advance Centre, in partnership with University College Dublin, Technological University Dublin and ATU Sligo, which offers accredited programmes and modules with the intent of addressing Ireland’s future digital skill needs. “They enable students to gain additional skills and knowledge that supplement their professional field. For example, a mechanical engineer might pursue a micro-credential in cybersecurity or data analytics to enhance their expertise and employability,” said O’Gorman. By bridging very specific skills gaps, micro-credentials can cover materials that may otherwise not be addressed in more traditional degree programmes. “This is particularly valuable in fast-evolving fields where specific up-to-date skills are in high demand.” Furthermore, it is fair to say that balancing work, education and your personal life is no easy feat, but this shouldn’t mean that you have to compromise on your career aspirations. 


Eedge Data Center Supports Emerging Trends

Adopting AI technologies requires a lot of computational power, storage space and low-latency networking to be able to train and run models. These technologies prefer hosting environments, which makes them highly compatible with data centres, therefore, as the demand for AI grows, so will the demand for data centres. However, the challenge remains on limiting new data centres to connect to the grid, which will impact data centre build out. This highlights edge data centres as the solution to the data centre capacity problem.  ... With this pressure, cloud computing has emerged as a cornerstone for these modernisation efforts, with companies choosing to move their workloads and applications onto the cloud. This shift has brought challenges for companies relating to them managing costs and ensuring data privacy. As a result, organisations are considering cloud repatriation as a strategic option. Cloud repatriation is essentially the migration of applications, data and workloads from the public cloud environment back to on-premises or a colocated centre infrastructure.


How To Get Rid of Technical Debt for Good

“To get rid of it or minimize it, you should treat this problem as a regular task -- systematically. All technical debt should be precisely defined and fixed with a maximum description of the current state and expected results after the problem is solved,” says Zaporozhets. “As the next step, [plan] the activities related to technical debt -- namely, who, when, and how should deal with these problems. And, of course, regular time should be allocated for this, which means that dealing with technical debt should become a regular activity, like attending daily meetings.” ... Regularly addressing technical debt requires discipline, motivation and systematic behavior from all team members. “When the team stops being afraid of technical debt and starts treating it as a regular task, the pressure will lessen, and there will be a sense of control,” says Zaporozhets, “It's important not to put technical debt on hold. I teach my teammates that each team member must remember to take a systematic approach to technical debt and take initiative. When the whole team works together on this, they will realize that technical debt is not so scary, and controlling the backlog will become a routine task.”


New Orleans CIO Kimberly LaGrue Discusses Cyber Resilience

Cities are engrossed in the business of delivering services to constituents. But appreciating that a cyber interruption could knock down a city makes everyone think about that differently. In our cyberattack, we had the support of the mayor, the chief administrative officer and the homeland security office. The problem was elevated to those levels, and we were grateful that they appreciated the importance of the challenges. The most integral part of a good resilience strategy for government, especially for city government, is for city leaders to pay attention to it and buy into the idea that these are real threats, and they must be addressed? ... We learned of cyberattacks across the state through Louisiana’s fusion center. They were very active, very vocal about other threats. We gained a lot of insights, a lot of information, and they were on the ground helping those agencies to recover. The state had almost 200 volunteers in its response arsenal, led by the Louisiana National Guard and the state of Louisiana’s fusion center. During our cyberattack, the group of volunteers that was helping other agencies came from those events straight to New Orleans for our event.


How cyber insurance shapes risk: Ascension and the limits of lessons learned

As research has supported, simple cost-benefit conditions among victims incentivize immediate payment to cyber criminals unless perfect mitigation with backups is possible and so long as the ransom is priced to correspond with victim budgets. Any delay incurs unnecessary costs to victims, their clients, and — cumulatively — to the insurer. The result is the rapid payment posture mentioned above. The singular character of cyber risk for these companies also sets limits on the lessons that can be learned for the average CISO working to safeguard organizations across the vast majority of America’s private enterprise. ... CISOs across the board should support firmer discussions with the federal government about increasingly strict and even punitive rules for limiting the payout of criminal fees. Limiting criminal incident payouts would remove the incentives for consistent high-tempo strikes on major infrastructure providers, which the federal government could compensate for in the near term by providing better resources for Sector Risk Management Agencies and beginning to resolve the abnormal dynamics surrounding the insurer-critical infrastructure relationship.


Transform, don't just change: Palladium India’s Neha Zutshi

The world of work is evolving rapidly, and HR is at the forefront of this transformation. One of the biggest challenges we face is managing change effectively, as poorly planned and communicated changes often meet resistance and fail. To navigate this, organisations must build the capability to manage change quickly and efficiently. This involves fostering an agile, learning culture where adaptability is valued, and employees are encouraged to embrace new ways of working. Upskilling and reskilling are critical in this process, ensuring that our workforce remains relevant and equipped to handle emerging challenges. ... Technology and AI are pervasive, permeating every industry, and HR is no exception. Various aspects of AI, such as machine learning and digital systems, have streamlined HR processes and automate mundane tasks. However, even though there are early adopter advantages, it is crucial to assess the need and risks related to adopting innovative HR technologies. Policy and ethical considerations must be addressed when adopting these technologies. Clear policies governing confidentiality, fairness, and accuracy are essential to ensure a smooth transition.



Quote for the day:

"Successful and unsuccessful people do not vary greatly in their abilities. They vary in their desires to reach their potential." -- John Maxwell

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