Showing posts with label BCI. Show all posts
Showing posts with label BCI. Show all posts

Daily Tech Digest - March 15, 2026


Quote for the day:

"A leader must inspire or his team will expire." -- Orrin Woodward


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The Last Frontier: Navigating the Dawn of the Brain-Computer Interface Era

In the article "The Last Frontier: Navigating the Dawn of the Brain-Computer Interface Era," Kannan Subbiah explores the transformative rise of Brain-Computer Interfaces (BCIs) as they move from science fiction to strategic reality. BCIs function by bypassing traditional neural pathways to establish a direct communication link between the brain's electrical signals and external hardware. By 2026, the technology has transitioned from clinical trials—aimed at restoring mobility and sensory perception for the paralyzed—into the enterprise sector, where it is used to monitor cognitive load and optimize worker productivity. However, this deep integration between biological and digital intelligence introduces profound risks, including physical inflammation from invasive implants, cybersecurity threats like "brain-jacking," and ethical concerns regarding the erosion of personal agency. To address these vulnerabilities, a global movement for "neurorights" has emerged, led by frameworks from UNESCO and pioneer legislation in nations like Chile to protect mental privacy and integrity. Subbiah argues that while the potential for human augmentation is immense, society must establish rigorous ethical standards to ensure thoughts are treated as expressions of human dignity rather than mere harvestable data. Ultimately, navigating this frontier requires balancing rapid innovation with a "hybrid mind" philosophy that prioritizes psychological continuity and user autonomy.


Is your AI agent a security risk? NanoClaw wants to put it in a virtual cage

In the article "Is your AI agent a security risk? NanoClaw wants to put it in a virtual cage" on ZDNet, Charlie Osborne discusses the newly announced partnership between NanoClaw and Docker, designed to tackle the escalating security concerns surrounding autonomous AI agents. NanoClaw emerged as a lightweight, security-first alternative to OpenClaw, boasting a tiny codebase of fewer than 4,000 lines compared to its predecessor's massive 400,000. This simplicity allows for easier auditing and reduced risk. The integration enables NanoClaw agents to run within Docker Sandboxes, which utilize MicroVM-based, disposable isolation zones. Unlike traditional containers that share a kernel with the host, these MicroVMs provide a "hard boundary," ensuring that even if an agent misbehaves or is compromised, it remains contained and cannot access or damage the host system. This "secure-by-design" approach addresses critical enterprise obstacles, such as the potential for agents to accidentally delete files or leak sensitive credentials. By providing a controlled environment where agents can independently install tools and execute workflows without constant human oversight, the collaboration unlocks greater productivity while maintaining rigorous enterprise-grade safeguards. Ultimately, the partnership shifts the security paradigm from trusting an agent's behavior to enforcing OS-level isolation, making it safer for organizations to deploy powerful AI agents in production.


Banks Turn to Unified Data Platforms to Manage Risk Intelligence

In the article "Banks Turn to Unified Data Platforms to Manage Risk Intelligence," Sandhya Michu explores how financial institutions are addressing the complexities of digital banking by consolidating fragmented data environments into strategic unified platforms. The rapid growth of digital transactions has scattered operational and customer data across mobile apps and backend systems, creating a "brittle" infrastructure that often hinders the scalability of AI and analytics initiatives. To overcome this, leading banks are building centralized data lakes and unified digital layers to aggregate structured and unstructured information. These centralized environments empower business, compliance, and risk departments with shared datasets, significantly improving regulatory reporting and customer analytics. Additionally, unified platforms enhance operational observability by enabling faster incident analysis through log correlation across diverse systems. Beyond reliability, these data frameworks are revolutionizing credit risk management by providing real-time underwriting capabilities and early warning systems that ingest external market data. By digitizing legacy archives and investing in real-time data stores, banks are creating a robust foundation for advanced generative AI applications and continuous analytics. Ultimately, this shift toward a unified data architecture is essential for maintaining transparency, regulatory oversight, and enterprise-wide decision-making in an increasingly volatile and data-intensive financial landscape.


Why nobody cares about laptop touchscreens anymore

In the article "Why nobody cares about laptop touchscreens anymore," author Chris Hoffman argues that the once-coveted feature has become a neglected afterthought for both hardware manufacturers and Microsoft. While touchscreens remain prevalent on Windows 11 devices, they are rarely showcased in marketing because the industry has shifted focus toward performance, battery life, and AI integration. Hoffman posits that the initial appeal of touchscreens was largely a workaround for the poor-quality trackpads found on older Windows 10 machines. With the advent of highly responsive, "precision" touchpads across modern laptops, the functional necessity of reaching for the screen has vanished. Furthermore, Windows 11 lacks a truly optimized touch interface, and the ecosystem of touch-first applications has stagnated since the Windows 8 era. Even on 2-in-1 convertible devices, the "tablet mode" is described as an imperfect compromise with awkward ergonomics and watered-down software gestures. Unless a user specifically requires pen input for digital art or note-taking, Hoffman suggests that a touchscreen is now a "check-box" feature that adds little real-world value. Ultimately, the piece advises consumers to prioritize other specifications, as the current Windows environment remains firmly a mouse-and-keyboard-first experience, leaving the touchscreen as a redundant relic of past design ambitions.


How AI is changing your mind

In the Computerworld article "How AI is changing your mind," Mike Elgan warns that the widespread adoption of artificial intelligence is fundamentally altering human cognition and social interaction. Drawing on recent research from institutions like Cornell and USC, Elgan identifies two primary dangers: behavioral manipulation and the homogenization of thought. Studies show that biased AI autocomplete tools can successfully shift user opinions on controversial topics—even when individuals are warned of the bias—because the interactive nature of co-writing makes the influence feel internal. Simultaneously, the reliance on a few dominant Large Language Models (LLMs) is erasing linguistic and cultural diversity, nudging global expression toward a bland, Western-centric "hive mind" through a feedback loop of generic training data. These chatbots act as "co-reasoners," fostering sycophancy and simulated validation that can distort reality, particularly for isolated individuals. To combat this cognitive erosion, Elgan suggests practical strategies: disabling autocomplete, writing without AI to preserve individuality, and treating chatbots as intellectual sparring partners rather than authority figures. Ultimately, the piece argues that while AI offers immense utility, users must consciously protect their mental autonomy from being subtly rewritten by algorithms that prioritize consensus and efficiency over authentic human perspective and diversity of thought.
In the Information Age article "The value of reducing middle-office emissions for ESG," Danielle Price explores how the modernization of middle-office functions—such as reconciliation, trade matching, and risk management—can significantly advance corporate sustainability. Historically, these processes have been energy-intensive, running continuously on legacy on-premise servers at peak capacity. As ESG performance increasingly influences a bank’s cost of capital, CIOs must view the middle office as a strategic asset for decarbonization. Migrating these data-heavy workloads to public, cloud-native infrastructure can reduce operational emissions by 60% to 80% without requiring fundamental changes to business processes. This transition is becoming essential as Pillar 3 disclosures demand more granular ESG reporting and evidence of measurable year-on-year reductions. Financially, high ESG scores are linked to lower credit spreads and reduced regulatory capital charges, making infrastructure efficiency a direct factor in a firm’s financial health. Furthermore, the shift to cloud-native platforms creates a powerful network effect; when shared systems lower their carbon footprint, the entire counter-party ecosystem benefits. Ultimately, the article argues that aligning operational efficiency with ESG objectives is no longer optional, but a strategic imperative that combines environmental stewardship with enhanced financial competitiveness in today's global capital markets.


New European Emissions Regs Include Cybersecurity Rules

The article from Data Breach Today details the integration of new cybersecurity requirements into the European Union's "Euro 7" emissions regulations, marking a significant shift in automotive compliance. Prompted by the "Dieselgate" scandal, these rules mandate that gas-powered vehicles feature on-board systems to monitor emissions data, which must be protected from tampering, spoofing, and unauthorized over-the-air updates. While the regulations primarily target malicious external hackers, they also aim to prevent corporate fraud. However, a major point of contention has emerged: the potential conflict with the "right-to-repair" movement. The same secure gateway technologies used to prevent unauthorized modifications to engine control units could effectively lock out independent mechanics, who require access to diagnostic data for legitimate repairs. Automotive experts warn that while most passenger vehicle manufacturers are prepared, the commercial sector lags behind, and the industry faces an immense architectural challenge in balancing security with equitable data access. Furthermore, as cars become increasingly connected, broader risks—including remote takeovers and sensitive data leaks—remain a concern for EU public safety, suggesting that current type-approval regimes may need to evolve to address nation-state threats and organized cybercrime.


Why Data Governance Fails in Many Organizations: The Accountability Crisis and Capability Gaps

In the article "Why Data Governance Fails in Many Organizations," Stanyslas Matayo explores the critical factors behind the high failure rate of data governance initiatives, specifically highlighting the "accountability crisis" and "capability gaps." Despite significant investments, many organizations engage in "governance theater," where committees exist on paper but lack the executive authority, seniority, and enforcement mechanisms to drive change. This accountability gap is exacerbated when governance roles report to mid-level IT rather than leadership, rendering them expendable scribes rather than strategic governors. Simultaneously, a "capability deficit" arises when initiatives are treated as purely technical projects. Teams often overlook essential non-technical skills like change management, ethics, and learning design, assuming technical expertise alone is sufficient for organizational transformation. To combat these failures, the author references the DMBOK framework, advocating for four pillars: formal role clarification (e.g., Data Owners and Stewards), governed metadata, explicit quality mechanisms, and aligned communication flows. Ultimately, success requires moving beyond technical delivery to establish a business-led discipline where data is managed as a strategic asset through senior-level sponsorship and a holistic integration of diverse organizational capabilities, ensuring that governance structures possess the actual power to resolve conflicts and enforce standards.


AI coding agents keep repeating decade-old security mistakes

The Help Net Security article "AI coding agents keep repeating decade-old security mistakes" details a 2026 study by DryRun Security that evaluated the security performance of Claude Code, OpenAI Codex, and Google Gemini. Researchers discovered that despite their rapid software generation capabilities, these AI agents introduced vulnerabilities in 87% of the pull requests they created. The study identified ten recurring vulnerability categories across all three agents, with broken access control, unauthenticated sensitive endpoints, and business logic failures being the most prevalent. For example, agents frequently failed to implement server-side validation for critical actions or neglected to wire authentication middleware into WebSocket handlers. While OpenAI Codex generally produced the fewest vulnerabilities, all agents struggled with secure JWT secret management and rate limiting. The report emphasizes that traditional regex-based static analysis tools often miss these complex logic and authorization flaws, as they cannot reason about data flows or trust boundaries effectively. Consequently, the study recommends that development teams scan every pull request, incorporate security reviews into the initial planning phase, and utilize contextual security analysis tools. Ultimately, while AI agents significantly accelerate development, their lack of inherent security-centric reasoning necessitates rigorous human oversight and advanced scanning to prevent the recurrence of foundational security errors.


Impact of Artificial Intelligence (AI) in Enterprise Architecture (EA) Discipline

The article "Impact of Artificial Intelligence (AI) in Enterprise Architecture (EA) Discipline" examines how AI is fundamentally reshaping the traditional responsibilities of enterprise architects. By integrating advanced AI tools into the EA framework, organizations can automate labor-intensive tasks such as data mapping and technical documentation, allowing architects to focus on higher-value strategic initiatives that drive business value. AI-driven analytics provide architects with deeper, real-time insights into complex system dependencies, enabling more accurate predictive modeling and significantly faster decision-making across the enterprise. This technological shift encourages a transition away from static, reactive architectures toward dynamic, proactive ecosystems that can autonomously adapt to rapid market changes and emerging digital threats. However, the author emphasizes that this transition is not without its hurdles; it necessitates a robust foundation in data governance, careful ethical considerations regarding AI bias, and a long-term commitment to upskilling the existing workforce. Ultimately, the fusion of AI and EA facilitates much better alignment between high-level business goals and underlying IT infrastructure, driving continuous innovation and operational efficiency. As the discipline evolves, the most successful enterprise architects will be those who leverage AI as a sophisticated collaborative partner to manage organizational complexity and provide strategic foresight in an increasingly competitive digital landscape.

Daily Tech Digest - February 08, 2026


Quote for the day:

"The litmus test for our success as Leaders is not how many people we are leading, but how many we are transforming into leaders" -- Kayode Fayemi



Why agentic AI and unified commerce will define ecommerce in 2026

Agentic AI and unified commerce are set to shape ecommerce in 2026 because the foundations are now in place: consumers are increasingly comfortable using AI tools, and retailers are under pressure to operate seamlessly across channels. ... When inventory, orders, pricing, and customer context live in disconnected systems, both humans and AI struggle to deliver consistent experiences. When those systems are unified, retailers can enable more reliable automation, better availability promises, and more resilient fulfillment, especially at peak. ... Unified commerce platforms matter because they provide a single operational framework for inventory, orders, pricing, and customer context. That coordination is increasingly critical as more interactions become automated or AI-assisted. ... The shift toward “agentic” happens when AI can safely take actions, like resolving a customer service step, updating a product feed, or proposing a replenishment recommendation, based on reliable data and explicit rules. That’s why unified commerce matters: it reduces the risk of automation acting on partial truth. Because ROI varies dramatically by category, maturity, and data quality, it’s safer to avoid generic percentage claims. The defensible message is: companies that pair AI with clean operational data and clear governance will unlock automation faster and with fewer reputational risks. ... Ultimately, success in 2026 will not be defined by how many AI features a retailer deploys, but by how well their systems can interpret context, act reliably, and scale under pressure.


EU's Digital Sovereignty Depends On Investment In Open-Source And Talent

We argue that Europe must think differently and invest where it matters, leveraging its strengths, and open technologies are the place to look. While Europe does not have the tech giants of the US and China, it possesses a huge pool of innovation and human capital, as well as a small army of capable and efficient technology service providers, start-ups, and SMEs. ... Recent data shows that while Europe accounts for a substantial share of global open source developers, its contribution to open source-derived infrastructure remains fragmented across countries, with development being concentrated in a small number of countries. ... Europe may not have a Silicon Valley, but it has something better: a robust open source workforce. We are beginning to recognize this through fora such as the recent European Open Source Awards, which celebrated European citizens and residents working on things ranging from the Linux kernel and open office suites to open hardware and software preservation. ... Europe has a chance of succeeding. Historically, Europe has done a good job in making open source and open standards a matter of public policy. For example, the European Commission's DG DIGIT has an open source software strategy which is being renewed this year, and Europe possesses three European Standards Organizations, including CEN, CENELEC, and ETSI. While China has an open source software strategy, Europe is arguably leading the US in harnessing the potential of open technologies as a matter of public and industrial policy, and it has a strong foundation for catching up to China.


Is artificial general intelligence already here? A new case that today's LLMs meet key tests

Approaching the AGI question from different disciplinary perspectives—philosophy, machine learning, linguistics, and cognitive science—the four scholars converged on a controversial conclusion: by reasonable standards, current large language models (LLMs) already constitute AGI. Their argument addresses three key questions: What is general intelligence? Why does this conclusion provoke such strong reactions? And what does it mean for ... "There is a common misconception that AGI must be perfect—knowing everything, solving every problem—but no individual human can do that," explains Chen, who is lead author. "The debate often conflates general intelligence with superintelligence. The real question is whether LLMs display the flexible, general competence characteristic of human thought. Our conclusion: insofar as individual humans possess general intelligence, current LLMs do too." ... "This is an emotionally charged topic because it challenges human exceptionalism and our standing as being uniquely intelligent," says Belkin. "Copernicus displaced humans from the center of the universe, Darwin displaced humans from a privileged place in nature; now we are contending with the prospect that there are more kinds of minds than we had previously entertained." ... "We're developing AI systems that can dramatically impact the world without being mediated through a human and this raises a host of challenging ethical, societal, and psychological questions," explains Danks.


Biometrics deployments at scale need transparency to help businesses, gain trust

As adoption invites scrutiny, more biometrics evaluations, completed assessments and testing options come available. Communication is part of the same issue, with major projects like EES, U.S. immigration and protest enforcement, and more pedestrian applications like access control and mDLs all taking off. ... Biometric physical access control is growing everywhere, but with some key sectorial and regional differences, Goode Intelligence Chief Analyst Alan Goode explains in a preview of his firm’s latest market research report on the latest episode of the Biometric Update Podcast. Imprivata could soon be on the market, with PE owner Thoma Bravo working with JPMorgan and Evercore to begin exploring its options. ... A panel at the “Identity, Authentication, and the Road Ahead 2026” event looked at NIST’s work on a playbook to help businesses implement mDLs. Representatives from the NCCoE, Better Identity Coalition, PNC Bank and AAMVA discussed the emerging situation, in which digital verifiable credentials are available, but people don’t know how to use them. ... DHS S&T found 5 of 16 selfie biometrics providers met the performance goals of its Remote Identity Validation Rally, Shufti and Paravision among them. RIVR’s first phase showed that demographically similar imposters still pose a significant problem for many face biometrics developers.


The Invisible Labor Force Powering AI

A low-cost labor force is essential to how today’s AI models function. Human workers are needed at every stage of AI production for tasks like creating and annotating data, reinforcing models, and moderating content. “Today’s frontier models are not self-made. They’re socio-technical systems whose quality and safety hinge on human labor,” said Mark Graham, a professor at the University of Oxford Internet Institute and a director of the Fairwork project, which evaluates digital labor platforms. In his book Feeding the Machine: the Hidden Human Labor Powering AI (Bloomsbury, 2024), Graham and his co-authors illustrate that this global workforce is essential to making these systems usable. “Without an ongoing, large human-in-the-loop layer, current capabilities would be far more brittle and misaligned, especially on safety-critical or culturally sensitive tasks,” Graham said. ... The industry’s reliance on a distributed, gig-work model goes back years. Hung points to the creation of the ImageNet database around 2007 as the moment that set the referential data practices and work organization for modern AI training. ... However, cost is not the only factor. Graham noted that cost arbitrage plays a role, but it is not the whole explanation. AI labs, he said, need extreme scale and elasticity, meaning millions of small, episodic tasks that can be staffed up or down at short notice, as well as broad linguistic and cultural coverage that no single in-house team can reproduce.


Code smells for AI agents: Q&A with Eno Reyes of Factory

In order to build a good agent, you have to have one that's model agnostic. It needs to be deployable in any environment, any OS, any IDE. A lot of the tools out there force you to make a hard trade off that we felt wasn't necessary. You either have to vendor lock yourself to one LLM or ask everyone at your company to switch IDEs. To build like a true model agnostic, vendor agnostic coding agent, you put in a bunch of time and effort to figure out all the harness engineering that's necessary to make that succeed, which we think is a fairly different skillset from building models. And so that's why we think companies like us actually are able to build agents that outperform on most evaluations from our lab. ... All LLMs have context limits so you have to manage that as the agent progresses through tasks that may take as long as eight to ten hours of continuous work. There are things like how you choose to instruct or inject environment information. It's how you handle tool calls. The sum of all of these things requires attention to detail. There really is no individual secret. Which is also why we think companies like us can actually do this. It's the sum of hundreds of little optimizations. The industrial process of building these harnesses is what we think is interesting or differentiated. ... Of course end-to-end and unit tests. There are auto formatters that you can bring in, SaaS static application security testers and scanners: your sneaks of the world.


Software-Defined Vehicles Transform Auto Industry With Four-Stage Maturity Framework For Engineers

More refined software architectures in both edge and cloud enable the interpretation of real-time data for predictive maintenance, adaptive user interfaces, and autonomous driving functions, while cloud-based AI virtualized development systems enable continuous learning and updates. Electrification has only further accelerated this evolution as it opened the door for tech players from other industries to enter the automotive market. This represents an unstoppable trend as customers now expect the same seamless digital experiences they enjoy on other devices. ... Legacy vehicle systems rely on dozens of electronic control units (ECUs), each managing isolated functions, such as powertrain or infotainment systems. SDVs consolidate these functions into centralized compute domains connected by high-speed networks. This architecture provides hardware and software abstraction, enabling OTA updates, seamless cross-domain feature integration, and real-time data sharing, are essential for continuous innovation. ... Processing sensor data at the edge – directly within the vehicle – enables highly personalized experiences for drivers and passengers. It also supports predictive maintenance, allowing vehicles to anticipate mechanical issues before they occur and proactively schedule service to minimize downtime and improve reliability. Equally important are abstraction layers that decouple software applications from underlying hardware.


Cybersecurity and Privacy Risks in Brain-Computer Interfaces and Neurotechnology

Neuromorphic computing is developing faster than predicted by replicating the human brain's neural architecture for efficient, low-power AI computation. As highlighted in talks around brain-inspired chips and meshing, these systems are blurring distinctions between biological and silicon-based computation. In the meanwhile, bidirectional communication is made possible by BCIs, such as those being developed by businesses and research facilities, which can read brain activity for feedback or control and possibly write signals back to affect cognition. ... Neural data is essentially personal. Breaches could expose memories, emotions, or subconscious biases. Adversaries may reverse-engineer intentions for coercion, fraud, or espionage as AI decodes brain scans for "mind captioning" or talent uploading. ... Compromised BCIs blur cyber-physical boundaries farther than OT-IT convergence already has. A malevolent actor might damage medical implants, alter augmented reality overlays, or weaponize neurotech in national security scenarios. ... Implantable devices rely on worldwide supply chains prone to tampering. Neuromorphic hardware, while efficient, provides additional attack surfaces if not designed with zero-trust principles. Using AI to process neural signals can introduce biases, which may result in unfair treatment in brain-augmented systems 


Designing for Failure: Chaos Engineering Principles in System Design

To design for failure, we must understand how the system behaves when failure inevitably happens. What is the cost? What is the impact? How do we mitigate it? How do we still maintain over 99% uptime? This requires treating failure as a default state, not an exception. ... The first step is defining steady-state behavior. Without this, there is no baseline to measure against. ... Chaos experiments are most valuable in production. This is where real traffic patterns, real user behavior, and real data shapes exist. That said, experiments must be controlled. ... Chaos Engineering is not a one-off exercise. Systems evolve. Dependencies change. Teams rotate. Experiments should be automated, repeatable, and run continuously, either as scheduled jobs or integrated into CI/CD pipelines. Over time, experiments can be expanded to test higher-impact scenarios. ... Additional considerations include health checks, failover timing, and data consistency. Strong consistency simplifies reasoning but reduces availability. Eventual consistency improves availability but introduces complexity and potential inconsistency windows. ... Network failures are unavoidable in distributed systems. Latency spikes, packets get dropped, DNS fails, and sometimes the network splits entirely. Many system outages are not caused by servers crashing, but by slow or unreliable communication between otherwise healthy components. This is where several of the classic fallacies of distributed computing show up, especially the assumption that the network is reliable and has zero latency.


Why SMBs Need Strong Data Governance Practices

Good data governance for small businesses is about building trust, control and scalability into your data from day one. Governance should be built into the data foundation, not bolted on later. Small businesses move fast, and governance works best when it’s native to how data is managed. That means choosing platforms that apply security, access controls and compliance consistently across all data, without requiring manual oversight or specialized teams. Additionally, clear visibility and control over what data exists and who can access it is essential. Even at a smaller scale, businesses handle sensitive information ranging from customer and financial data to operational insights. ... Governance also future proofs the business. Regulations are becoming more complex, customer expectations for data protection are rising, and AI systems must have high-quality, well-governed data to perform reliably. Small businesses that treat governance as a foundation are better positioned to adopt AI and safely expand into new use cases, markets and regulatory environments without needing to rearchitect later. At the same time, strong data governance improves day-to-day efficiency. When data is well governed, teams can spend more time acting on insights and less time questioning data quality, managing access manually or duplicating work. ... From a cybersecurity perspective, governance provides the controls and visibility needed to reduce attack surfaces and detect misuse. 

Daily Tech Digest - April 13, 2025


Quote for the day:

"I've learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel." -- Maya Angelou



The True Value Of Open-Source Software Isn’t Cost Savings

Cost savings is an undeniable advantage of open-source software, but I believe that enterprise leaders often overlook other benefits that are even more valuable to the organization. When developers use open-source tools, they join a collaborative global community that is constantly learning from and improving on the technology. They share knowledge, resources and experiences to identify and fix problems and move updates forward more rapidly than they could individually. Adopting open-source software can also be a win-win talent recruitment and retention strategy for your enterprise. Many individual contributors see participating in open-source software communities as a tangible way to build their own profiles as experts in their field—and in the process, they also enhance your company’s reputation as a cool place where tech leaders want to work. However, there’s no such thing as a free meal. Open-source software isn't immune to vendor lock-in, when your company becomes so dependent on a partner’s product that it is prohibitively costly or difficult to switch to an alternative. You may not be paying licensing fees, but you still need to invest in support contracts for open-source tools. The bigger challenge from my perspective is that it’s still rare for enterprises to contribute regularly to open-source software communities. 


The Growing Cost of Non-Compliance and the Need for Security-First Solutions

Regulatory bodies across the globe are increasing their scrutiny and enforcement actions. Failing to comply with well-established regulations like HIPAA or GDPR, or newer ones like the European Union’s Digital Operational Resilience Act (DORA) and NY DFS Cybersecurity requirements, can result in penalties that can reach millions of dollars. But the costs do not stop there. Once a company has been found to be non-compliant, it often faces reputational damage that extends far beyond the immediate legal repercussions. ... A security-first approach goes beyond just checking off boxes to meet regulatory requirements. It involves implementing robust, proactive security measures that safeguard sensitive data and systems from potential breaches. This approach protects the organization from fines and builds a strong foundation of trust and resilience in the face of evolving cyber threats. ... Many businesses still rely on outdated, insecure methods of connecting to critical systems through terminal emulators or “green screen” interfaces. These systems, often running legacy applications, can become prime targets for cybercriminals if they are not properly secured. With credential-based attacks rising, organizations must rethink how they secure access to their most vital resources.


Researchers unveil nearly invisible brain-computer interface

Today's BCI systems consist of bulky electronics and rigid sensors that prevent the interfaces from being useful while the user is in motion during regular activities. Yeo and colleagues constructed a micro-scale sensor for neural signal capture that can be easily worn during daily activities, unlocking new potential for BCI devices. His technology uses conductive polymer microneedles to capture electrical signals and conveys those signals along flexible polyimide/copper wires—all of which are packaged in a space of less than 1 millimeter. A study of six people using the device to control an augmented reality (AR) video call found that high-fidelity neural signal capture persisted for up to 12 hours with very low electrical resistance at the contact between skin and sensor. Participants could stand, walk, and run for most of the daytime hours while the brain-computer interface successfully recorded and classified neural signals indicating which visual stimulus the user focused on with 96.4% accuracy. During the testing, participants could look up phone contacts and initiate and accept AR video calls hands-free as this new micro-sized brain sensor was picking up visual stimuli—all the while giving the user complete freedom of movement.


Creating SBOMs without the F-Bombs: A Simplified Approach to Creating Software Bills of Material

It's important to note that software engineers are not security professionals, but in some important ways, they are now being asked to be. Software engineers pick and choose from various third-party and open source components and libraries. They do so — for the most part — with little analysis of the security of those components. Those components can be — or become — vulnerable in a whole variety of ways: Once-reliable code repositories can become outdated or vulnerable, zero days can emerge in trusted libraries, and malicious actors can — and often do — infect the supply chain. On top of that, risk profiles can change overnight, making what was a well considered design choice into a vulnerable one almost overnight. Software engineers never before had to consider these things, and yet the arrival of the SBOM is making them do so like never before. Customers can now scrutinize their releases, and then potentially reject or send them back for fixing — resulting in even more work on short notice and piling on pressure. Even if the risk profile of a particular component changes between the creation of an SBOM and a customer reviewing it, then the release might be rejected. This is understandably the cause of much frustration for software engineers who are often already under great pressure.


Risk & Quality: The Hidden Engines of Business Excellence

In the world of consultancy, firms navigate a minefield of challenges—tight deadlines, budget constraints, and demanding clients. Then, out of nowhere, disruptions such as regulatory shifts or resource shortages strike, threatening project delivery. Without a robust risk management framework, these disruptions can snowball into major financial and reputational losses. ... Some leaders see quality assurance as an added expense, but in reality, it’s a profit multiplier. According to the American Society for Quality (ASQ), organizations that emphasize quality see an average of 4-6% revenue growth compared to those that don’t. Why? Because poor quality leads to rework, client dissatisfaction, and reputational damage. ... The cost of poor quality is substantial. Firms that don’t embed quality into their culture ultimately face consequences like customer churn, regulatory fines, and declining market share. Additionally, fixing mistakes after the fact is far more expensive than ensuring quality from the outset. Organizations that invest in quality from the start avoid unnecessary costs, improve efficiency, and strengthen their bottom line. As Philip Crosby, a pioneer in quality management, stated, “Quality is free. It’s not a gift, but it’s free. What costs money are the unquality things—all the actions that involve not doing jobs right the first time.” 


Enabling a Thriving Middleware Market

A more unified regulatory approach could reduce uncertainty, streamline compliance, and foster an ecosystem that better supports middleware development. However, given the unlikelihood of creating a new agency, a more feasible approach would be to enhance coordination among existing regulators. The FTC could address antitrust concerns, the FCC could promote interoperability, and the Department of Commerce could support innovation through trade policies and the development of technical standards. Even here, slow rulemaking and legal challenges could hinder progress. Ensuring agencies have the necessary authority, resources, and expertise will be critical. A soft-law approach, modeled after the National Institute for Standards and Technology (NIST) AI Risk Management Framework, might be the most feasible option. A Middleware Standards Consortium could help establish best practices and compliance frameworks. Standards development organizations (SDOs), such as the Internet Engineering Task Force or the World Wide Web Consortium (W3C), are well-positioned to lead this effort, given their experience crafting internet protocols that balance innovation with stability. For example, a consortium of SDOs with buy-in from NIST could establish standards for API access, data portability, and interoperability of several key social media functionalities.


How to Supercharge Application Modernization with AI

The refactoring of code – which means restructuring and, often, partly rewriting existing code to make applications fit a new design or architecture – is the most crucial part of the application modernization process. It has also tended in the past to be the most laborious because it required developers to pore over often very large codebases, painstakingly tweaking code function-by-function or even line-by-line. AI, however, can do much of this dirty work for you. Instead of having to find places where code should be rewritten or modified in order to optimize it, developers can leverage AI tools to look for code that requires attention. ... When you move applications to the cloud, the infrastructure that hosts them is effectively a software resource – which means you can configure and manage it using code. By extension, you can use AI tools like Cursor and Copilot to write and test your code-based infrastructure configurations. Specifically, AI is capable of tasks such as writing and maintaining the code that manages CI/CD pipelines or cloud servers. It can also suggest opportunities to optimize existing infrastructure code to improve reliability or security. And it can generate the ancillary configurations, such as Identity and Access Management (IAM) policies, that govern and help to secure cloud infrastructure.


Balancing Generative AI Risk with Reward

As businesses start evolving in their use of this technology and exposing it to a broader base inside and outside their companies, risks can increase. “I’ve always loved to say AI likes to please,” said Danielle Derby, director of enterprise data management at TriNet, who joined Rodarte at the presentation. Risk manifests “because AI doesn’t know when to stop,” said Derby, and you, for example, may not have thought about including a human or technology guardrail to keep it from answering a question you hadn’t prepared it to be able to accurately manage. “There are a lot of areas where you’re just not sure how someone who’s not you is going to handle this new technology,” she said. ... Improper data splitting can lead to data leakage, resulting in overly optimistic model performance, which you can mitigate by using techniques like stratified sampling to ensure representative splits and by always splitting the data before performing any feature engineering or preprocessing. Inadequate training data can lead to overfitting and too little test data can yield unreliable performance metrics, and you can mitigate these by ensuring there is enough data for both training and testing based on problem size, and using a validation set in addition to training and test sets.


Why Cybersecurity-as-a-Service is the Future for MSPs and SaaS Providers

For MSPs and SaaS providers, adopting a proactive, scalable approach to cybersecurity—one that provides continuous monitoring, threat intelligence, and real-time response—is crucial. By leveraging Cybersecurity-as-a-Service (CSaaS), businesses can access enterprise-grade security without the need for extensive in-house expertise. This model not only enhances threat detection and mitigation but also ensures compliance with evolving cybersecurity regulations. ... The increasing complexity and frequency of cyber threats necessitate a proactive and scalable approach to security. CSaaS offers a flexible solution by outsourcing critical security functions to specialized providers. This ensures continuous monitoring, threat intelligence, and incident response without the need for extensive in-house resources. As cyber threats evolve, CSaaS providers continuously update their tools and techniques, ensuring we stay ahead of emerging vulnerabilities. CSaaS enhances our ability to protect sensitive data and allows us to confidently focus on core business operations. As threats evolve, CSaaS providers continually update their tools and techniques, ensuring companies stay ahead of emerging vulnerabilities. ... Embracing CSaaS is essential for maintaining a robust security posture in an increasingly complex digital landscape.


Meta: WhatsApp Vulnerability Requires Immediate Patch

Meta has voluntarily disclosed the new WhatsApp vulnerability, now published as CVE-2025-30401, after investigating it internally as a submission to its bug bounty program. The company says there is not yet evidence that it has been exploited in the wild. The issue likely impacts all Windows versions prior to 2.2450.6. The WhatsApp vulnerability hinges on an attacker sending a malicious attachment, and would require the target to attempt to manually view the attachment within the software. A spoofing issue makes it possible for the file opening handler to execute code that has been hidden as a seemingly valid MIME type such as an image or document. That could pave the way for remote code execution, though a CVE score has yet to be assigned as of this writing. ... The WhatsApp vulnerability exploited by Paragon was a much more devastating zero-click (and one that targeted phones and mobile devices), similar to one exploited by NSO Group on the platform to compromise over a thousand devices. That landed the spyware vendor in trouble in US courts, where it was found to have violated national hacking laws. The court found that NSO Group had obtained WhatsApp’s underlying code and reverse-engineered it to create at least several zero-click vulnerabilities that it put to use in its spyware.

Daily Tech Digest - February 22, 2022

Partner Across Teams to Create a Cybersecurity Culture

Just because a software engineer doesn’t work on the security team doesn’t mean that security isn’t their responsibility. In addition to the standard security training, you can further empower your engineering teams by training and encouraging them to think like hackers. I was fortunate enough to work for a company some time ago that scheduled annual competitions with prizes and bragging rights. These competitions served as security training and engaged us in a series of engineering puzzles that included SQL injection, cross-site scripting (XSS), cryptography and social engineering. ... Even with well-implemented training programs and a dedicated cadre of security-minded engineers building your applications, there is still plenty for your security engineers to work on. The shared-responsibility model will reduce the risk of successful phishing attacks or other malicious activity, but it won’t remove it entirely. Ideally, security teams will move from a place where they are constantly fighting fires to one where they can engage in strategic initiatives to further improve security for the organization, automate risk detection wherever possible, and prepare your organization for the future.


Agile Doesn’t Work Without Psychological Safety

Soon after implementing agile, many organizations revert to the default position of worshiping at the altar of technical processes and tools, because cultural considerations seem abstract and difficult to operationalize. It’s easier to pay lip service to the human side and then move on to scrumming, sprinting, kanbaning, and kaizening because these processes serve as tangible, measurable, and observable indicators, giving the illusion of success and the appearance of developing agile at scale. Begin your agile transformation by framing agile as a cultural rather than a technical or mechanical implementation. In doing so, be careful not to approach culture as a workstream. A workstream is defined as the progressive completion of tasks required to finish a project. When we approach culture as a workstream within the context of agile, we classify it as something that can be completed. Culture cannot be completed. Yet I see agile teams attempting to project-manage it as part of the work breakdown structure, as if it has a beginning, middle, and end. It doesn’t.


Inside the U.K. lab that connects brains to quantum computers

While BCIs and quantum computers are undoubtedly promising technologies emerging at the same point in history, the question is why bring them together – which is exactly what the consortium of researchers from the U.K.’s University of Plymouth, Spain’s University of Valencia and University of Seville, Germany’s Kipu Quantum, and China’s Shanghai University are seeking to do. Technologists love nothing more than mashing together promising concepts or technologies in the belief that, when united, they will represent more than the sum of their parts. Sometimes this works gloriously. As the venture capitalist Andrew Chen describes in his book The Cold Start Problem, Instagram leveraged the emergence of camera-equipped smartphones and the simultaneous powerful network effects of social media to become one of the fastest-growing apps in history. Taking two must-have technologies and combining them doesn’t always work, though. Apple CEO Tim Cook once quipped that “you can converge a toaster and a refrigerator, but, you know, those things are probably not going to be pleasing to the user.”


Three ways COVID-19 is changing how banks adapt to digital technology

Bank leaders face the difficult task of balancing the traditional approach to risk management with the need to respond quickly to a crisis that has created massive changes to their operating environment. Criminal cyber activity, including fraud and phishing attacks, has increased as more employees work remotely. However, as one participant said: “We have not yet seen the massive increase in sophisticated, advance persistent threat cyber attacks that we normally associate with events like these.” As banks shift from crisis mode, their boards need to address new emerging risks, such as video and voice communication surveillance with everyone using Zoom and other platforms, data security controls for the use of personal equipment, and cases of third and fourth parties falling victim to cyber issues. ... As the economic impacts of the pandemic become clearer, banks are updating risk models and stress scenarios in an attempt to stay ahead of the curve. However, uncertainty in the operating environment continues to pose challenges. A lack of regulatory harmonization may further complicate benchmarking among peers across countries, though there is hope that this will improve soon.


The threat of quantum computing to security infrastructure

The report states:”The encryption technologies that are securing Canada’s financial systems today will one day become obsolete. If we do nothing, the financial data that underpins Canada’s economy will inevitably become more vulnerable to cyber criminals.” In the US, as noted above, the National Security Agency took an early lead in identifying the perceived threat. On January 19, 2022, an action from the US president came public. The White House issued a “Memorandum on Improving the Cybersecurity of National Security, Department of Defense and Intelligence Community Systems.” The document shows the urgency needed to address perceived major threats. It outlines major actions to avoid security lapses that would be created by quantum computers targeting critical secret data and related infrastructure. It also identifies the management responsibilities in the various agencies to implement these measure within a matter of months. This perceived threat to existing cybersecurity will generate a great deal of private industry and bring well-funded new companies into the business of transition to new security solutions.


AI fairness in banking: the next big issue in tech

“People want to be treated fairly by an agent whether artificial or not. The difference for a lot of applications is that people are not aware of the full extent of the decision making and the statistical regularities across a larger population where some of these issues can arise. There is a lot of cynicism around these decisions.” He adds that there are technical as well as organisational solutions that financial services providers need to apply. This, combined with policies of transparency about the processes in place all combine to provide an overall strategy. He adds: “The first thing is to have processes of regularly reporting on and examining and making corrections to data that is used to train models as well as to test them. “So, a simple test is representation of people that belong to legally protected categories by race, age, gender, ethnic origin and religious status to determine if there is enough data to represent each of these groups with accurate models. In addition, these is a need to determine whether there are other inputs to the model or features that could be corelated with these protected classes and have a potentially adverse or discriminatory impact on the output of the model.”


4 common misunderstandings about enterprise open source software

It might seem natural to download community-supported bits from the Internet rather than purchase an integrated product. This is especially the case when the community projects are relatively simple and self-contained or if you have reasons to develop independent expertise or do extensive customization. (Although working with a vendor to get needed changes into the upstream project is a possible alternative in the latter case.) However, if the software isn’t a differentiating capability for your business, hiring the right highly-skilled engineers is neither easy nor cheap. There’s also the ongoing support burden if your downloaded projects turn into a fork of the upstream community project. And if you don’t want them to, you’ll need to factor in the time to work in the upstream projects to get needed features added. There’s also a lot of complexity in categories like enterprise open source container platforms in the cloud-native space. Download Kubernetes? You’re just getting started. How about monitoring, distributed tracing, CI/CD, serverless, security scanning, and all the other features you’ll want in a complete platform? 


Leadership when the chips are down

Particularly noteworthy is the obsessive nature of Shackleton’s encounter with a territory so resistant to accurate perception. We risk bathos to say that the business landscape presents challenges on a par with the South Pole, yet the perceptual difficulties posed by Antarctica offer clear parallels for executives and entrepreneurs. The southernmost continent is unpredictable, unstable, and unforgiving. Compasses don’t behave normally. Much of what appears terra firma is actually floating ice, and deadly crevasses lurk under the snow. Snow blindness, a painful effect of the dazzling surroundings, can make vision itself impossible. ... Shackleton’s failings as a manager were manifest in his planning for the Heart of the Antarctic expedition. For a trip on foot of 1,720 miles to and from the Pole, his four-man unit brought food for just 91 days of hard labor, high altitude, and mind-numbing cold. His return instructions to the crew of the Nimrod, the ship that dropped off his party, were impossibly vague. 


How can banks remain relevant in the fastest growing digital market in the world?

While bolting on a digital banking system may be a quick fix for incumbents, the only way for FIs to truly keep up with the pace of change and future-proof their business is to invest in modern architecture which offers them the flexibility required to develop and deploy products and services at speed. Built with advanced customisation at their core, modern platforms enable FIs to approach product development with a different mindset to those struggling with legacy systems. As a result, FIs benefit from faster time-to-market, being able to scale up innovative digital operations, offer new products or services, and respond to ever-changing market requirements much faster. Shifting consumer behaviours, coupled with intensified competition, is making it increasingly difficult for banks in the APAC region to remain relevant. They are fighting not only to keep their loyal customer base, but stay ahead of the curve by offering customers the advanced digital services they require. Only by ensuring they have a comprehensive, future-proof system in place, underpinning their operations, will they truly be able to embrace the digital future.


Sustaining Agile Transformation – Our Experience

The organization needs to rethink and create a career roadmap for the Agile roles like Product Owner, Scrum Master, and Developers. The organization must build and enhance the self-paced learning experience, embed learning experience, develop role-based training, develop new learning areas, etc. For certain key roles, the organizations can focus on establishing academies such as Scrum Master Academy. This will ensure there is continuous learning and flow of trained Scrum Masters as and when needed. Coaching skills should be taught and embedded in Agile leaders and change agents. Ensure Leaders are trained and embrace foundational values and principles. Establishing and retaining a Central team such as a lean CoE will be very beneficial to oversee the transformation and support when needed. The organization can deliberate on the establishment of the CoE at divisional or organization levels. Collaborative forums like the CoPs, Guilds, Chapters, etc. should be established and run successfully. 



Quote for the day:

"Leaders must see the dream in their mind before they will accomplish the dream with their team." -- Orrin Woodward

Daily Tech Digest - October 17, 2021

Multi-User IP Address Detection

When an Internet user visits a website, the underlying TCP stack opens a number of connections in order to send and receive data from remote servers. Each connection is identified by a 4-tuple (source IP, source port, destination IP, destination port). Repeating requests from the same web client will likely be mapped to the same source port, so the number of distinct source ports can serve as a good indication of the number of distinct client applications. By counting the number of open source ports for a given IP address, you can estimate whether this address is shared by multiple users. User agents provide device-reported information about themselves such as browser and operating system versions. For multi-user IP detection, you can count the number of distinct user agents in requests from a given IP. To avoid overcounting web clients per device, you can exclude requests that are identified as triggered by bots and we only count requests from user agents that are used by web browsers. There are some tradeoffs to this approach: some users may use multiple web browsers and some other users may have exactly the same user agent. 


Critical infrastructure security dubbed 'abysmal' by researchers

"While nation-state actors have an abundance of tools, time, and resources, other threat actors primarily rely on the internet to select targets and identify their vulnerabilities," the team notes. "While most ICSs have some level of cybersecurity measures in place, human error is one of the leading reasons due to which threat actors are still able to compromise them time and again." Some of the most common issues allowing initial access cited in the report include weak or default credentials, outdated or unpatched software vulnerable to bug exploitation, credential leaks caused by third parties, shadow IT, and the leak of source code. After conducting web scans for vulnerable ICSs, the team says that "hundreds" of vulnerable endpoints were found. ... Software accessible with default manufacturer credentials allowed the team to access the water supply management platform. Attackers could have tampered with water supply calibration, stop water treatments, and manipulate the chemical composition of water supplies.


What is a USB security key, and how do you use it?

There are some potential drawbacks to using a hardware security key. First of all, you could lose it. While security keys provide a substantial increase in security, they also provide a substantial increase in responsibility. Losing a security key can result in a serious headache. Most major websites suggest that you set up backup 2FA methods when enrolling a USB security key, but there's always a small but real chance that you could permanently lose access to a specific account if you lose your key. Security-key makers suggest buying more than one key to avoid this situation, but that can quickly get expensive. Cost is another issue. A hardware security key is the only major 2FA method for which you have to spend money. You can get a basic U2F/WebAuthn security key standards for $15, but some websites and workplaces require specialized protocols for which compatible keys can cost up to $85 each. Finally, limited usability is also a factor. Not every site supports USB security keys. If you're hoping to use a security key on every site for which you have an account, you're guaranteed to come across at least a few that won't accept your security key.


Future-proofing the organization the ‘helix’ way

The leaders need a high level of domain expertise, obviously, but other skills as well. As capability managers, these leaders must excel at strategic workforce management, for example—not short-sighted resource attribution for the products at hand, but the strategic foresight and long-term perspective to understand what the workload will be today, tomorrow, three to five years from now. They need to understand what skills they don’t have in-house and must acquire or build. These leaders become supply-and-demand managers of competence. They must also be excellent—and rigid—portfolio managers who make their resource decisions in line with the overall transformation. The R&D organization, for example, cannot start research projects inside a product line whose products are classified as “quick return,” even if they have people idle. It’s a different mindset. In fact, R&D leaders don’t necessarily have to be the best technologists in order to be successful. They must be farsighted and able to anticipate trends—including technological trends—but ultimately what matters is their ability to build the department in a way that ensures it’s ready to carry the demands of the organization going forward.


Robots Will Replace Our Brains

Over the years, despite numerous fruitless attempts, no one has come close to achieving the recreation of this organ with all its intricate details; it is challenging to fathom such an invention in the scientific world at this point, considering the discoveries that surface every other day. As one research director mentions, we are very good at gathering data and developing algorithms to reason with that data. Nevertheless, that reasoning is only as sound as the data, one step removed from reality for the AI we have now. For instance, all science fiction movies conceive movies that depict only a mere thin line that separates human intelligence from artificial intelligence. ... A new superconducting switch is being constructed by researchers at the U.S. National Institute of Standards and Technology (NIST) and updated that will soon enable computers to analyze and make decisions just like humans do. The conclusive goal is to integrate this switch into everyday life; from transportation to medicine, this invention also contains an artificial synapse, processes electrical signals just like a biological synapse does, and converts it to an adequate output, just like the brain does.


Data Storage Strategies - Simplified to Facilitate Quick Retrieval of Data and Security

No matter what the reason for the downtime, it may be very costly. An efficient data strategy goes beyond just deciding where data will be kept on a server. When it comes to disaster recovery, hardware failure, or a human mistake, it must contain methods for backing up the data and ensuring that it is simple and fast to restore. Putting in place a disaster recovery plan, although it is a good start and guarantees that data and the related systems are available after a minimum of disruption is experienced. Cloud-based disaster recovery, as well as virtualization, are now required components of every disaster recovery strategy. They can work together to assure you that no customer will ever experience more downtime than they can afford at any given moment. By relying only on the cloud storage service, the company can outsource the storage issue. By using online data storage, the business can minimize the costs associated with internal resources. With this technology, the business does not need any internal resources or assistance to manage and keep their data; the Data warehousing consulting services provider takes care of everything. 


RISC-V: The Next Revolution in the Open Hardware Movement

You could always build your own proprietary software and be better than your competitors, but the world has changed. Now almost everyone is standing on the shoulders of giants. When you need an operating system kernel for a new project, you can use Linux directly. No need to recreate a kernel from scratch, and you can also modify it for your own purpose (or write your drivers). You’ll be certain to rely on a broadly tested product because you are just one of a million users doing the same. That would be exactly what relying on an open source CPU architecture could provide. No need to design things from scratch; you can innovate on top of the existing work and focus on what really matters to you, which is the value you are adding. At the end of the day, it means lowering the barriers to innovate. Obviously, not everyone is able to design an entire CPU from scratch, and that’s the point: You can bring only what you need or even just enjoy new capabilities provided by the community, exactly the same way you do with open source software, from the kernel to languages.


The Conundrum Of User Data Deletion From ML Models

As the name says, approximation deletion enables us to eliminate the majority of the implicit data associated with users from the model. They are ‘forgotten,’ but only in the sense that our models can be retrained at a more opportune time. Approximate deletion is particularly useful for rapidly removing sensitive information or unique features associated with a particular individual that could be used for identification in the future while deferring computationally intensive full model retraining to times of lower computational demand. Approximate deletion can even accomplish the exact deletion of a user’s implicit data from the trained model under certain assumptions. The deletion challenge has been tackled differently by researchers than by their counterparts in the field. Additionally, the researchers describe a novel approximate deletion technique for linear and logistic models that is feature-dimensionally linear and independent of training data. This is a significant improvement over conventional systems, which are superlinearly dependent on the extent at all times.


9 reasons why you’ll never become a Data Scientist

Have you ever invested an entire weekend in a geeky project? Have you ever spent your nights browsing GitHub while your friends were out to party? Have you ever said no to doing your favorite hobby because you’d rather code? If you could answer none of the above with yes, you’re not passionate enough. Data Science is about facing really hard problems and sticking at them until you found a solution. If you’re not passionate enough, you’ll shy away at the sight of the first difficulty. Think about what attracts you to becoming a Data Scientist. Is it the glamorous job title? Or is it the prospect of plowing through tons of data on the search for insights? If it is the latter, you’re heading in the right direction. ... Only crazy ideas are good ideas. And as a Data Scientist, you’ll need plenty of those. Not only will you need to be open to unexpected results — they occur a lot! But you’ll also have to develop solutions to really hard problems. This requires a level of extraordinary that you can’t accomplish with normal ideas. 


Why Don't Developers Write More Tests?

If deadlines are tight or the team leaders aren’t especially committed to testing, it is often one of the first things software developers are forced to skip. On the other hand, some developers just don’t think tests are worth their time. “They might think, ‘this is a very small feature, anyone can create a test for this, my time should be utilized in something more important.’” Mudit Singh of LambdaTest told me. ... In truth, there are some legitimate limitations to automated tests. Like many complicated matters in software development, the choice to test or not is about understanding the tradeoffs. “Writing automated tests can provide confidence that certain parts of your application work as expected,” Aidan Cunniff, the CEO of Optic told me, “but the tradeoff is that you’ve invested a lot of time ‘stabilizing’ and making ‘reliable’ that part of your system.” ... While tests might have made my new feature better and more maintainable, they were technically a waste of time for the business because the feature wasn’t really what we needed. We failed to invest enough time understanding the problem and making a plan before we started writing code.



Quote for the day:

"Leaders are readers, disciples want to be taught and everyone has gifts within that need to be coached to excellence." -- Wayde Goodall