Showing posts with label HR. Show all posts
Showing posts with label HR. Show all posts

Daily Tech Digest - August 27, 2025


Quote for the day:

"Success is the progressive realization of predetermined, worthwhile, personal goals." -- Paul J. Meyer


To counter AI cheating, companies bring back in-person job interviews

Google, Cisco and McKinsey & Co. have all re-instituted in-person interviews for some job candidates over the past year. “Remote work and advancements in AI have made it easier than ever for fake candidates to infiltrate the hiring process,” said Scott McGuckin, vice president of global talent acquisition at Cisco. “Identifying these threats is our priority, which is why we are adapting our hiring process to include increased verification steps and enhanced background checks that may involve an in-person component. ... AI has proven benefits for both job seekers and hiring managers/recruiters. Its use in the job search process grew 6.4% over the past year, while use in core tasks surged even higher, according to online employment marketplace ZipRecruiter. The share of job seekers using AI to draft and refine resumes jumped 39% over last year, while AI-assisted cover letter writing climbed 41%, and AI-based interview prep rose 44%, according to the firm. ... HR and hiring managers should insist on well-lit video interviews, watch for delays or mismatches, ask follow-up questions to spot AI use and verify resume details with background checks and geolocation data. “Some assessment or interview platforms can look at geolocation data, use this to ensure consistency with the resume and application,” Chiba said. 


How procedural memory can cut the cost and complexity of AI agents

Memories are built from an agent’s past experiences, or “trajectories.” The researchers explored storing these memories in two formats: verbatim, step-by-step actions; or distilling these actions into higher-level, script-like abstractions. For retrieval, the agent searches its memory for the most relevant past experience when given a new task. The team experimented with different methods, such vector search, to match the new task’s description to past queries or extracting keywords to find the best fit. The most critical component is the update mechanism. Memp introduces several strategies to ensure the agent’s memory evolves. ... One of the most significant findings for enterprise applications is that procedural memory is transferable. In one experiment, procedural memory generated by the powerful GPT-4o was given to a much smaller model, Qwen2.5-14B. The smaller model saw a significant boost in performance, improving its success rate and reducing the steps needed to complete tasks. According to Fang, this works because smaller models often handle simple, single-step actions well but falter when it comes to long-horizon planning and reasoning. The procedural memory from the larger model effectively fills this capability gap. This suggests that knowledge can be acquired using a state-of-the-art model, then deployed on smaller, more cost-effective models without losing the benefits of that experience.


AI Summaries a New Vector for Malware

The attack uses what researchers call "prompt overdose," a technique in which malicious instructions are repeated dozens of times within invisible HTML styled with properties such as zero opacity, white-on-white text, microscopic font sizes and off-screen positioning. When AI summarizers process this content, the repeated hidden text dominates the model's attention mechanisms, pushing legitimate visible content aside. "When processed by a summarizer, the repeated instructions typically dominate the model's context, causing them to appear prominently - and often exclusively - in the generated summary." ... Cybercriminals have been quick to adapt the technique to fool large language models rather than humans. The attack's effectiveness stems from user reliance on AI-generated summaries for quick content triage, often replacing manual review of original materials. Testing showed that the technique works across AI platforms, including commercial services like Sider.ai and custom-built browser extensions. Researchers also identified factors amplifying the attack's potential impact. Summarizers integrated into widely-used applications could enable mass distribution of social engineering lures across millions of users. The technique could lower technical barriers for ransomware deployment by providing non-technical victims with detailed execution instructions disguised as legitimate troubleshooting advice.


A scalable framework for evaluating health language models

While auto-eval techniques are well equipped to handle the increased volume of evaluation criteria, the completion of the proposed Precise Boolean rubrics by human annotators was prohibitively resource intensive. To mitigate such burden, we refined the Precise Boolean approach to dynamically filter the extensive set of rubric questions, retaining only the most pertinent criteria, conditioned on the specific data being evaluated. This data-driven adaptation, referred to as the Adaptive Precise Boolean rubric, enabled a reduction in the number of evaluations required for each LLM response. ... Current evaluation of LLMs in health often uses Likert scales. We compared this baseline to our data-driven Precise Boolean rubrics. Our results showed significantly higher inter-rater reliability using Precise Boolean rubrics, measured by intra-class correlation coefficients (ICC), compared to traditional Likert rubrics. A key advantage of our approach is its efficiency. The Adaptive Precise Boolean rubrics resulted in high inter-rater agreement of the full Precise Boolean rubric while reducing evaluation time by over 50%. This efficiency gain makes our method faster than even Likert scale evaluations, enhancing the scalability of LLM assessment. The fact that this also provides higher inter-rater reliability supports the argument that this simpler scoring also provides a higher quality signal.


Outdated Fraud Defenses Are a Green Light for Scammers Everywhere

Financial institutions get stuck in a reactive cycle, responding to breaches after the fact and relying heavily on network alerts and reissuing cards en masse to mitigate damage. That’s problematic on all fronts. It’s expensive, increases call center volume and fails to address the root problem. Beyond that, it disrupts the cardholder experience, putting the institution at risk of losing a cardholder’s trust and business. After experiencing a fraudulent attack, cardholders adjust their payment behaviors, regardless of whether the fraudster was successful or not. This could mean they stop using the affected card altogether, switch to a competitor’s product or close their account entirely. ... The tables are turned on the scammer. Instead of detecting fraud as it occurs, financial institutions now have up to 180 days’ lead time to identify a fraud pattern, take action and contain it. This strategic lead time enables early intervention, giving teams the ability to identify emerging fraud typologies, disrupt bad actor behavior patterns and contain the spread before widespread damage occurs. It shifts the institution’s playbook from defense to offense. It also eliminates the need to reissue thousands of cards preemptively, instead identifying small subsets of cardholders most likely to be impacted. Reissues happen only when absolutely necessary, which saves on cost and reputation management. 


SysAdmins: The First Responders of the Digital World

Unlike employees in other departments like sales, finance, marketing, and HR, who can typically log off at 5 p.m. and check out of work until the next morning, IT professionals carry the unique burden of having to be “always on.” For technology vendors in particular, this is especially prevalent; when situations arise that compromise the integrity of key systems and networks, both employees and users can face disruptions to cost organizations revenue and reputational damage. Whether it’s hardware or software issues, the system administrator is there to jump in and patch the issue. ... IT departments are increasingly viewed as “profit protectors,” critical to the bottom line by preventing unplanned expenses and customer churn. As demonstrated by the anecdotes above, system administrators ensure the daily functionality and operational resilience of their organizations, enabling every other team to do their job efficiently. Without system administrators’ constant attention to ensuring things behind the scenes are running smoothly, employees would struggle to fulfill their daily tasks every time an incident occurs. ... Business leaders can show appreciation for these employees by prioritizing mental health initiatives, ensuring IT teams are sufficiently staffed to prevent burnout, and promoting workload balance with generous time-off packages. 


A wake-up call for identity security in devops

The GitHub incident exposed what security teams already suspect—that devops is running headlong into an identity sprawl problem. Identities (human and non-human) are multiplying, permissions are stacking up, and third-party apps are the new soft underbelly. This is where identity security posture management (ISPM) steps in. ISPM takes the principles of cloud security posture management (CSPM)—continuous monitoring, posture scoring, risk-based controls—and applies them to identity. It doesn’t stop at who can log in; it extends into who has access, why they have it, what they can do, and how that access is granted, including via OAuth. ... Modern identity security platforms are stepping in to close this gap. The leading solutions give you deep visibility into the web of permissions spanning developers, service accounts, and third-party OAuth apps. It’s no longer enough to know that a token exists. Teams need full context: who issued the token, what scopes it has, what systems it touches, and how those privileges compare across environments. ... Developers aren’t asking for more security tools, policies, or friction. What they want is clarity, especially if it helps them stay out of the next breach postmortem. That’s why visibility-first approaches work. When security teams show developers exactly what access exists, and why it matters, the conversation shifts from “Why are you blocking me?” to “Thanks for the heads-up.”


"Think Big to Achieve Big": A CEO's advice to today's HR leaders

The traditional perception of HR as an administrative function is obsolete. Today's CHRO is a key driver of organisational transformation, working in close collaboration with the CEO to formulate and achieve overarching goals. This partnership is essential for ensuring that HR initiatives are not just about hiring, but about building a future-ready organisation. This involves enabling talent with the latest technologies, skills, and continuous learning opportunities. Goyal's own collaboration with his CHRO is a model of this integrated approach. They work together to ensure that HR initiatives are fully aligned with the Group's long-term objectives, a dynamic that goes far beyond traditional HR functions. This partnership is what drives sustainable growth and navigates complex challenges. The modern workplace presents a unique set of challenges, from heightened uncertainty to the distinct expectations of Gen Z. Goyal's response to this is a philosophy of active adaptation. To attract and retain young talent, he believes companies must be open to revisiting policies, embracing flexible working hours, and promoting a culture of continuous learning. He emphasises the need for leaders to have an open mindset toward the new generation, just as they would for their own children.


Inside a quantum data center

Quantum-focused measures that might need to be considered include vibrations, electromagnetic sensitivity, and potentially even the speed of the elevators moving hardware between floors. Whether or not there would be one standard encompassing the different types of quantum computers – supercooled, rack-based, optical-tabled etc – or multiple standards to suit all comers is unclear at this stage. ... IBM does also host some dedicated quantum systems at its facilities for customers who don’t want their QPUs on-site, but on-premise enterprise deployments are rare beyond the likes of IBM’s agreement with Cleveland Clinic. They will likely be the exception rather than the norm for enterprises for some time to come, IQM’s Goetz says. “Corporate enterprise customers are not yet buying full systems,” says Goetz. “They are usually accessing the systems through the cloud because they are still ramping up their internal capabilities with the goal to be ready once the quantum computers really have the full commercial value.” Quite what the geography of a world with commercially-useful quantum computers will look like is unclear. Will enterprises be happy with a few centralized ‘quantum cloud’ regions, demand in-country capacity in multiple jurisdictions, or go so far as demanding systems be placed in on-premise or colocated facilities?


Simpler models can outperform deep learning at climate prediction

The researchers see their work as a “cautionary tale” about the risk of deploying large AI models for climate science. While deep-learning models have shown incredible success in domains such as natural language, climate science contains a proven set of physical laws and approximations, and the challenge becomes how to incorporate those into AI models. “We are trying to develop models that are going to be useful and relevant for the kinds of things that decision-makers need going forward when making climate policy choices. While it might be attractive to use the latest, big-picture machine-learning model on a climate problem, what this study shows is that stepping back and really thinking about the problem fundamentals is important and useful,” says study senior author Noelle Selin ... “Large AI methods are very appealing to scientists, but they rarely solve a completely new problem, so implementing an existing solution first is necessary to find out whether the complex machine-learning approach actually improves upon it,” says Lütjens. Some initial results seemed to fly in the face of the researchers’ domain knowledge. The powerful deep-learning model should have been more accurate when making predictions about precipitation, since those data don’t follow a linear pattern. 

Daily Tech Digest - July 29, 2025


Quote for the day:

"Great leaders do not desire to lead but to serve." -- Myles Munroe


AI Skills Are in High Demand, But AI Education Is Not Keeping Up

There’s already a big gap between how many AI workers are needed and how many are available, and it’s only getting worse. The report says the U.S. was short more than 340,000 AI and machine learning workers in 2023. That number could grow to nearly 700,000 by 2027 if nothing changes. Faced with limited options in traditional higher education, most learners are taking matters into their own hands. According to the report, “of these 8.66 million people learning AI, 32.8% are doing so via a structured and supervised learning program, the rest are doing so in an independent manner.” Even within structured programs, very few involve colleges or universities. As the report notes, “only 0.2% are learning AI via a credit-bearing program from a higher education institution,” while “the other 99.8% are learning these skills from alternative education providers.” That includes everything from online platforms to employer-led training — programs built for speed, flexibility, and real-world use, rather than degrees. College programs in AI are growing, but they’re still not reaching enough people. Between 2018 and 2023, enrollment in AI and machine learning programs at U.S. colleges went up nearly 45% each year. Even with that growth, these programs serve only a small slice of learners — most people are still turning to other options.


Why chaos engineering is becoming essential for enterprise resilience

Enterprises should treat chaos engineering as a routine practice, just like sports teams before every game. These groups would never participate in matches without understanding their opponent or ensuring they are in the best possible position to win. They train under pressure, run through potential scenarios, and test their plays to identify the weaknesses of their opponents. This same mindset applies to enterprise engineering teams preparing for potential chaos in their environments. By purposely simulating disruptions like server outages, latency, or dropped connections, or by identifying bugs and poor code, enterprises can position themselves to perform at their best when these scenarios occur in real life. They can adopt proactive approaches to detecting vulnerabilities, instituting recovery strategies, building trust in systems and, in the end, improving their overall resilience. ... Additionally, chaos engineering can help improve scalability within the organisation. Enterprises are constantly seeking ways to grow and enhance their apps or platforms so that more and more end-users can see the benefits. By doing this, they can remain competitive and generate more revenue. Yet, if there are any cracks within the facets or systems that power their apps or platforms, it can be extremely difficult to scale and deliver value to both customers and the organisation.


Fractional CXOs: A New Model for a C-Everything World

Fractional leadership isn’t a new idea—it’s long been part of the advisory board and consulting space. But what’s changed is its mainstream adoption. Companies are now slotting in fractional leaders not just for interim coverage or crisis management, but as a deliberate strategy for agility and cost-efficiency. It’s not just companies benefiting either. Many high-performing professionals are choosing the fractional path because it gives them freedom, variety, and a more fulfilling way to leverage their skills without being tied down to one company or role. For them, it’s not just about fractional time—it’s about full-spectrum opportunity. ... Whether you’re a company executive exploring options or a leader considering a lifestyle pivot, here are the biggest advantages of fractional CxOs:Strategic Agility: Need someone to lead a transformation for 6–12 months? Need guidance scaling your data team? A fractional CxO lets you dial in the right leadership at the right time. Cost Containment: You pay for what you need, when you need it. No long-term employment contracts, no full comp packages, no redundancy risk. Experience Density: Most fractional CxOs have deep domain expertise and have led across multiple industries. That cross-pollination of experience can bring unique insights and fast-track solutions.


Cyberattacks reshape modern conflict & highlight resilience needs

Governments worldwide are responding to the changing threat landscape. The United States, European Union, and NATO have increased spending on cyber defence and digital threat-response measures. The UK's National Cyber Force has broadened its recruitment initiatives, while the European Union has introduced new cyber resilience strategies. Even countries with neutral status, such as Switzerland, have begun investing more heavily in cyber intelligence. ... Critical infrastructure encompasses power grids, water systems, and transport networks. These environments often use operational technology (OT) networks that are separated from the internet but still have vulnerabilities. Attackers typically exploit mechanisms such as phishing, infected external drives, or unsecured remote access points to gain entry. In 2024, a group linked to Iran, called CyberAv3ngers, breached several US water utilities by targeting internet-connected control systems, raising risks of water contamination. ... Organisations are advised against bespoke security models, with tried and tested frameworks such as NIST CSF, OWASP SAMM, and ISO standards cited as effective guides for structuring improvement. The statement continues, "Like any quality control system it is all about analysis of the situation and iterative improvements. Things evolve slowly until they happen all at once."


The trials of HR manufacturing: AI in blue-collar rebellion

The challenge of automation isn't just technological, it’s deeply human. How do you convince someone who has operated a ride in your park for almost two decades, who knows every sound, every turn, every lever by heart, that the new sleek control panel is an upgrade and not a replacement? That the machine learning model isn’t taking their job; it’s opening doors to something better? For many workers, the introduction of automation doesn’t feel like innovation but like erasure. A line shuts down. A machine takes over. A skill that took them years to master becomes irrelevant overnight. In this reality, HR’s role extends far beyond workflow design; it now must navigate fear, build trust, and lead people through change with empathy and clarity. Upskilling entails more than just access to platforms that educate you. It’s about building trust, ensuring relevance, and respecting time. Workers aren’t just asking how to learn, but why. Workers want clarity on their future career paths. They’re asking, “Where is this ride taking me?” As Joseph Fernandes, SVP of HR for South Asia at Mastercard, states, change management should “emphasize how AI can augment employee capabilities rather than replace them.” Additionally, HR must address the why of training, not just the how. Workers don’t want training videos; rather, they want to know what the next five years of their job look like. 


What Do DevOps Engineers Think of the Current State of DevOps

The toolchain is consolidating. CI/CD, monitoring, compliance, security and cloud provisioning tools are increasingly bundled or bridged in platform layers. DevOps.com’s coverage tracks this trend: It’s no longer about separate pipelines, it’s about unified DevOps platforms. CloudBees Unify is a prime example: Launched in mid‑2025, it unifies governance across toolchains without forcing migration — an AI‑powered operating layer over existing tools. ... DevOps education and certification remain fragmented. Traditional certs — Kubernetes (CKA, CKAD), AWS/Azure/GCP and DevOps Foundation — remain staples. But DevOps engineers express frustration: Formal learning often lags behind real‑world tooling, AI integration, or platform engineering practices. Many engineers now augment certs with hands‑on labs, bootcamps and informal community learning. Organizations are piloting internal platform engineer training programs to bridge skills gaps. Still, a mismatch persists between the modern tech stack and classroom syllabi. ... DevOps engineers today stand at a crossroads: Platform engineering and cloud tooling have matured into the ecosystem, AI is no longer experimentation but embedded flow. Job markets are shifting, but real demand remains strong — for creative, strategic and adaptable engineers who can shepherd tools, teams and AI together into scalable delivery platforms.


7 enterprise cloud strategy trends shaking up IT today

Vertical cloud platforms aren’t just generic cloud services — they’re tailored ecosystems that combine infrastructure, AI models, and data architectures specifically optimized for sectors such as healthcare, manufacturing, finance, and retail, says Chandrakanth Puligundla, a software engineer and data analyst at grocery store chain Albertsons. What makes this trend stand out is how quickly it bridges the gap between technical capabilities and real business outcomes, Puligundla says. ... Organizations must consider what workloads go where and how that distribution will affect enterprise performance, reduce unnecessary costs, and help keep workloads secure, says Tanuj Raja, senior vice president, hyperscaler and marketplace, North America, at IT distributor and solution aggregator TD SYNNEX. In many cases, needs are driving a move toward a hybrid cloud environment for more control, scalability, and flexibility, Raja says. ... We’re seeing enterprises moving past the assumption that everything belongs in the cloud, says Cache Merrill, founder of custom software development firm Zibtek. “Instead, they’re making deliberate decisions about workload placement based on actual business outcomes.” This transition represents maturity in the way enterprises think about making technology decisions, Merrill says. He notes that the initial cloud adoption phase was driven by a fear of being left behind. 


Beyond the Rack: 6 Tips for Reducing Data Center Rental Costs

One of the simplest ways to reduce spending on data center rentals is to choose data centers located in regions where data center space costs the least. Data center rental costs, which are often measured in terms of dollars-per-kilowatt, can vary by a factor of ten or more between different parts of the world. Perhaps surprisingly, regions with the largest concentrations of data centers tend to offer the most cost-effective rates, largely due to economies of scale. ... Another key strategy for cutting data center rental costs is to consolidate servers. Server consolidation reduces the total number of servers you need to deploy, which in turn minimizes the space you need to rent. The challenge, of course, is that consolidating servers can be a complex process, and businesses don’t always have the means to optimize their infrastructure footprint overnight. But if you deploy more servers than necessary, they effectively become a form of technical debt that costs more and more the longer you keep them in service. ... As with many business purchases, the list price for data center rent is often not the lowest price that colocation operators will accept. To save money, consider negotiating. The more IT equipment you have to deploy, the more successful you’ll likely be in locking in a rental discount. 


Ransomware will thrive until we change our strategy

We need to remember that those behind ransomware attacks are part of organized criminal gangs. These are professional criminal enterprises, not lone hackers, with access to global infrastructures, safe havens to operate from, and laundering mechanisms to clean their profits. ... Disrupting ransomware gangs isn’t just about knocking a website or a dark marketplace offline. It requires trained personnel, international legal instruments, strong financial intelligence, and political support. It also takes time, which means political patience. We can’t expect agencies to dismantle global criminal networks with only short-term funding windows and reactive mandates. ... The problem of ransomware, or indeed cybercrime in general, is not just about improving how organizations manage their cybersecurity, we also need to demand better from the technology providers that those organizations rely on. Too many software systems, including ironically cybersecurity solutions, are shipped with outdated libraries, insecure default settings, complex patching workflows, and little transparency around vulnerability disclosure. Customers have been left to carry the burden of addressing flaws they didn’t create and often can’t easily fix. This must change. Secure-by-design and secure-by-default must become reality, and not slogans on a marketing slide or pinkie-promises that vendors “take cybersecurity seriously”.


The challenges for European data sovereignty

The false sense of security created by the physical storage of data in European data centers of US companies deserves critical consideration. Many organizations assume that geographical storage within the EU automatically means that data is protected by European law. In reality, the physical location is of little significance when legal control is in the hands of a foreign entity. After all, the CLOUD Act focuses on the nationality and legal status of the provider, not on the place of storage. This means that data in Frankfurt or Amsterdam may be accessible to US authorities without the customer’s knowledge. Relying on European data centers as being GDPR-compliant and geopolitically neutral by definition is therefore misplaced. ... European procurement rules often do not exclude foreign companies such as Microsoft or Amazon, even if they have a branch in Europe. This means that US providers compete for strategic digital infrastructure, while Europe wants to position itself as autonomous. The Dutch government recently highlighted this challenge and called for an EU-wide policy that combats digital dependency and offers opportunities for European providers without contravening international agreements on open procurement.

Daily Tech Digest - November 03, 2024

How AI-Powered Vertical SaaS Is Taking Over Traditional Enterprise SaaS

Enterprise decision-makers no longer care about the underlying technology itself—they care about what it delivers. They care about tangible outcomes like cost savings, operational efficiencies, and improved customer experiences. This shift in focus is causing companies to rethink their approach to enterprise software. ... Unlike traditional SaaS, which is built for broad use cases, vertical SaaS is deeply tailored to specific industries. By using AI, it can offer real-time insights, automation, and optimisations that solve problems unique to each sector. ... This hyper-targeted approach allows vertical SaaS to deliver tangible business outcomes rather than generic efficiencies. AI powers this shift by enabling platforms to adapt to industry-specific challenges, automate routine tasks, and provide insights at a scale and speed that was previously unattainable. Think of traditional SaaS like a Swiss Army knife — versatile, but not always the best tool for a specific task. vertical SaaS, however, is like a surgeon’s scalpel or a craftsman’s chisel — precisely designed for a specific job, delivering results with pinpoint accuracy and efficiency. What would you rather use for mission-critical work: a multi-tool that does everything adequately or an instrument built to perform one task perfectly?


Ending Microservices Chaos: How Architecture Governance Keeps Your Microservices on Track

With proper software architecture governance, you can reduce microservices complexity, ramp up developers faster, reduce MTTR, and improve the resiliency of your system, all while building a culture of intentionality. ... In addition to controlling the chaos of microservices with governance and observability, maintaining a high standard of security and code quality is essential. When working with distributed systems, the complexity of microservices — if left unchecked — can lead to vulnerabilities and technical debt. ... Tools from SonarSource — such as SonarLint or SonarQube — focus on continuous code quality and security. They help developers identify potential issues such as code smells, duplication, or even security risks like SQL injection. By integrating seamlessly with CI/CD pipelines, they ensure that every deployment follows strict security and code quality standards. The connection between code quality, application security, and architectural observability is clear. Poor code quality and unresolved vulnerabilities can lead to a fragile architecture that is prone to outages and security incidents. By proactively managing your code quality and security using these tools, you reduce the risk of microservices complexity spiraling out of control.


What is quiet leadership? Examples, traits & benefits

Quiet leadership is a leadership style defined by empathy, creativity, active listening, and attention to detail. It focuses on collaboration and communication instead of control. At its core is quiet confidence, not arrogance. Quiet leaders prefer to solve problems through teamwork and encouragement, not aggression. They are compassionate, understanding, open, and approachable. Most importantly, they earn their team’s respect instead of demanding it. ... Instead of criticizing yourself for not being an extroverted leader, embrace who you are. Don’t try to be someone you’re not. You might wonder if a quiet style can work because of leadership stereotypes. But in reality, it can be comforting to others. Build self-awareness and notice how you positively impact people. By accepting your unique leadership style, you’ll find what works best for you and your team. If you use your strengths, being a quiet leader can be a superpower. For example, quiet leaders are great listeners. Active listening is rare, so be proud if you have that skill. ... As a quiet leader, you’ll need to step outside your comfort zone at times. This can be exhausting, so make time to recharge and regain energy. 


From Code To Conscience: Humanities’ Role In Fintech’s Evolution

Reflecting on the day, it became clear that studying for a career in fintech—or any technology field—is not just about understanding mechanics; it’s about grasping the bigger picture and realizing the power of technology to serve people, not just profit. In a sector as influential as fintech, this balanced approach is crucial. A humanities background fosters exactly the kind of critical, thoughtful perspective that today’s technology fields demand. Combining technical knowledge with grounding in ethics, history, and critical problem-solving will be essential for tomorrow’s leaders, especially as fintech continues to shape societal norms and economic structures. The Pace of Fintech conference underscored how the intersection of AI, fintech, and the humanities is shaping a more thoughtful future for technology. Artificial intelligence, while transformative, requires a balance between innovation and ethics—an understanding of both its potential and its responsibilities. Humanities-trained thinkers bring crucial perspectives to this field, prompting questions about fairness, transparency, and societal impact that purely technical approaches may overlook.


Overcoming data inconsistency with a universal semantic layer

As if the data landscape weren’t complex enough, data architects began implementing semantic layers within data warehouses. Architects might think of the data assets they manage as the single source of truth for all use cases. However, that is not typically the case because millions of denormalized table structures are typically not “business-ready.” When semantic layers are embedded within various warehouses, data engineers must connect analytics use cases to data by designing and maintaining data pipelines with transforms that create “analytics-ready” data. ... What is needed is a universal semantic layer that defines all the metrics and metadata for all possible data experiences: visualization tools, customer-facing analytics, embedded analytics, and AI agents. With a universal semantic layer, everyone across the business agrees on a standard set of definitions for terms like “customer” and “lead,” as well as standard relationships among the data (standard business logic and definitions), so data teams can build one consistent semantic data model. A universal semantic layer sits on top of data warehouses, providing data semantics (context) to various data applications. It works seamlessly with transformation tools, allowing businesses to define metrics, prepare data models, and expose them to different BI and analytics tools.


Server accelerator architectures for a wide range of applications

The highest-performing architecture for AI performance is a system that allows the accelerators to communicate with each other without having to communicate back to the CPU. This type of system requires that the accelerators be mounted on their own baseboard with a high-speed switch on the baseboard itself. The initial communication that initializes the application that runs on the accelerators is over a PCIe path. When completed, the results are then also sent back to the CPU over PCIe. The CPU-to-accelerator communication should be limited, allowing the accelerators to communicate with each other over high-speed paths. A request from one accelerator is made directly or through a non-blocking switch (4 of them) and sent to the appropriate GPU. The performance of GPU to GPU is significantly higher than using the PCIe path, which allows for applications to use more than one GPU for an application without the need to interact with the CPU over the relatively slow PCIe lanes. ... A common and well-defined interface between CPUs and accelerators is to communicate over PCIe lanes. This architecture allows for various configurations in the server and the number of accelerators. 


AI Testing: More Coverage, Fewer Bugs, New Risks

The productivity gains from AI in testing are substantial. We now have a vast international bank that we have helped leverage our solution to such an extent it managed to increase test automation coverage across two of its websites (supporting around ten different languages), taking it from a mere forty percent to almost ninety percent in a matter of weeks. I believe this is an amazing achievement, not only because of the end results but also because working in an enterprise environment with its security and integrations can typically take forever. While traditional test automation might be limited to a single platform or language and the capacity of one person, AI-enhanced testing breaks these limitations. Testers can now create and execute tests on any platform (web, mobile, desktop), in multiple languages, and with the capacity of numerous testers. This amplifies testing capabilities and introduces a new level of flexibility and efficiency. ... Upskilling QA teams with AI brings the significant advantage of multilingual testing and 24/7 operation. In today’s global market, software products must often cater to diverse users, requiring testing in multiple languages. AI makes this possible without requiring testers to know each language, expanding the reach and usability of software products.


Why Great Leaders Embrace Broad Thinking — and How It Transforms Organizations

Broad thinking starts with employing three behaviors. First, spend time following your thoughts in an exploratory way rather than simply trying to find an answer or idea and moving on. Second, look at things from different angles and consider a wide range of options carefully before acting. Third, consistently consider the bigger picture and resist getting caught up in the smaller details. ... Companies want action. They don't want employees sitting around wringing their hands, frozen with indecision. They also don't want employees overanalyzing decisions to the point of inertia. Therefore, they often train employees to make decisions faster and more efficiently. However, decisions made for speed don't always make for great decisions. Especially seemingly simple ones that have larger downstream ramifications. ... Broad thinking considers the parts as being inseparable from the whole. The elephant parts are inseparable from the entire animal, just like the promotional campaign was inseparable from the other aspects of the organization it impacted. When you broaden your perspective, you also become more sensitive to subtleties of differentiation: how elements that are seemingly irrelevant, extraneous, or opposites can interconnect.


How Edge Computing Is Enhancing AI Solutions

Edge computing enhances the privacy and security of AI solutions by keeping sensitive data local rather than transmitting it to centralized cloud servers. Such an approach is most advantageous in industries such as managing and providing healthcare where privacy is of high value, especially in regards to patient information. By processing medical images or patient records at the edge, healthcare providers can ensure compliance with data protection regulations while still leveraging AI for improved diagnostics and treatment planning. Furthermore, edge AI minimizes the number of exposed data points that can be attacked through the networks by translating data tasks into localized subsets. ... As the volume of data generated by IoT devices continues to grow exponentially, transmitting all this information to the cloud for processing becomes increasingly impractical and expensive. This problem is solved in edge computing by sorting and analyzing data. This approach has dramatic effects in reducing the bandwidth required and the overall costs attached to it and in addition enhancing the system performance.


Why being in HR is getting tougher—and how to break through

The HR function lives in the friction between caring for the employee and caring for the organization. HR’s role is to represent the best interests of the organizations we work for and deliver care to employees for their end-to-end life cycle at those organizations. When you live in that friction, at times, you’re underdelivering that care to employees. At this moment—when employees’ needs are at an all-time high and organizations are struggling with costs and resetting around historical growth expectations—that gap is even wider than during less volatile times. There’s also an assumption that the employees’ interests and the company’s interests aren’t aligned—when many times they are. I have several tools to help people when they’re struggling. We can get a little bit caught up in the myths and expectations of people wanting too much, and that’s where the HR professional has to pull back and say, “This is what I can do, and it’s actually quite good.” ... Trust is hard earned but can go away in a second. And it can go away in a second because of HR but also, unfortunately, because of business leaders. 



Quote for the day:

"You can't be a leader if you can't influence others to act." -- Dale E. Zand