Showing posts with label agritech. Show all posts
Showing posts with label agritech. Show all posts

Daily Tech Digest - July 30, 2024

Cyber security and Compliance: The Convergence of Regtech Solutions

While cybersecurity, in itself, is an area that requires significant resources to ensure compliance, a business organisation needs to deal with numerous other regulations. The business regulatory ecosystem is made up of over 1,500 acts and rules and more than 69,000 compliances. As such, each enterprise needs to figure out the regulatory requirements applicable to their business. The complexity of the compliance framework is such that businesses are often lagging behind their compliance timelines. Take, for instance, a single-entity MSME with a single-state operation involved in manufacturing automotive components. Even such an operation requires the employer to keep up with 624 unique compliances. These requirements can reach close to 1,000 for a pharmaceutical enterprise. Persisting with manual compliance methods while technology has taken over every other business operation has become the root cause of delays, lapses, and defaults. While businesses are investing in the best possible technological solutions for cybersecurity issues, they are disregarding the impact of technology on their compliance functions.


Millions of Websites Susceptible to XSS Attack via OAuth Implementation Flaw

Essentially, the ‘attack’ requires only a crafted link to Google (mimicking a HotJar social login attempt but requesting a ‘code token’ rather than simple ‘code’ response to prevent HotJar consuming the once-only code); and a social engineering method to persuade the victim to click the link and start the attack (with the code being delivered to the attacker). This is the basis of the attack: a false link (but it’s one that appears legitimate), persuading the victim to click the link, and receipt of an actionable log-in code. “Once the attacker has a victim’s code, they can start a new login flow in HotJar but replace their code with the victim code – leading to a full account takeover,” reports Salt Labs. The vulnerability is not in OAuth, but in the way in which OAuth is implemented by many websites. Fully secure implementation requires extra effort that most websites simply don’t realize and enact, or simply don’t have the in-house skills to do so. From its own investigations, Salt Labs believes that there are likely millions of vulnerable websites around the world. The scale is too great for the firm to investigate and notify everyone individually. 


How to Build a High-Performance Analytics Team

The first approach, which he called the “artisan model,” involves building a small team of highly experienced (and highly paid) data scientists. Such skilled and capable team members can generally tackle all aspects of solving a business problem, from subject matter expert engagement to hypothesis testing, production, and iteration. The “factory approach,” on the other hand, resembles more of an assembly line, with a large group of people divvying up tasks based on their areas of expertise: some working on the business problem definition, others handling data acquisition, and so on. This second approach requires hiring more people than the first approach, but the pay differential between the two types of team members is significant enough that the two approaches cost roughly the same. ... An analytics team needs to grow and evolve to survive, and management must treat its staff accordingly. “Data scientists are some of the most sought-after talent in the economy right now,” Thompson stressed, “So I’m working every day to make sure that my team is happy and that they’re getting work they’re interested in ­– that they’re being paid well and treated well.”


Securing remote access to mission-critical OT assets

The two biggest challenges around securing remote access to mission-critical OT assets are different depending on whether it’s a user or machine that needs to connect to the OT asset. In terms of user access, the fundamental challenge is that the cyber security team doesn’t know what the assets are, and who the users are. That’s where the knowledge of the OT engineers – coupled with an inventory of the assets comes into play. The security team can leverage the inventory, experience, and knowledge of the OT engineers to operate as the “first line of defense” to stand up the organizational defenses. With respect to machine-to-machines access organizations typically don’t have an understanding of what “known good” traffic should look like between these assets. Without this understanding knowledge, it’s impossible to spot the anomalies from the baseline. That’s where a good cyber-physical system protection platform comes into play, providing the ability to understand the typical communication patterns that can eventually be operationalized in network segmentation rules to ensure effective security.


CrowdStrike debacle underscores importance of having a plan

To CrowdStrike’s credit, as well as its many partners and the CISO/InfoSec community at large, a lot of oil was burned in the initial days after the faulty update was transmitted as the community collectively jumped in and lent a hand to mitigate the situation. ... “Moving forward, this outage demonstrates that continuous preparation to fortify defenses is vital, especially before outages occur,” Christine Gadsby, CISO at Blackberry, opined. She continued, “Already understanding what areas are most vulnerable within a system prevents a panicked reaction when something looks amiss and makes it more difficult for hackers to wreak havoc. In a crisis, defense is the best offense; the value of confidence that comes with preparation cannot be underestimated.” ... CISOs should also review what needs to be changed, included, or deleted from their emergency response and business continuity playbooks. ... Now is the time for each CISO to do a bit of introspection on their team’s ability to address a similar scenario, and plan, exercise, and be prepared for the unexpected. Which could happen today, tomorrow, or hopefully never.


How Searchable Encryption Changes the Data Security Game

Organizations know they must encrypt their most valuable, sensitive data to prevent data theft and breaches. They also understand that organizational data exists to be used. To be searched, viewed, and modified to keep businesses running. Unfortunately, our Network and Data Security Engineers were taught for decades that you just can't search or edit data while in an encrypted state. ... So why, now, is Searchable Encryption suddenly becoming a gold standard in critical private, sensitive, and controlled data security? According to Gartner, "The need to protect data confidentiality and maintain data utility is a top concern for data analytics and privacy teams working with large amounts of data. The ability to encrypt data, and still process it securely is considered the holy grail of data protection." Previously, the possibility of data-in-use encryption revolved around the promise of Homomorphic Encryption (HE), which has notoriously slow performance, is really expensive, and requires an obscene amount of processing power. However, with the use of Searchable Symmetric Encryption technology, we can process "data in use" while it remains encrypted and maintain near real-time, millisecond query performance.


How Cloud-Based Solutions Help Farmers Improve Every Season

At the start of each growing season, farmers can use previous years’ data to strategically plan where and when to plant seeds, identifying the areas of the field where plants often grow strongly or are typically not as prosperous. From there, planters equipped with robotics, sensors, and camera vision, augmented with field boundaries, guidance lines, and other data provided from the cloud, can precisely place hundreds of seeds per second at an optimal depth and with optimal spacing, avoiding losses from seeds being planted too shallow, deep, or close to another plant. ... Advanced machines gather a wide range of data to support the next step of nurturing plant growth. That data is critical, because while plants are growing, so are weeds. And weeds need to be treated in a timely manner to give crops the best possible conditions to grow. With access to the prior year’s data, farmers can anticipate where weeds are likely to grow and target them directly. Today’s sprayers use computer vision and machine learning to detect where weeds are located as the sprayer moves throughout a field, applying herbicide only where it is needed. This not only reduces costs but is also more sustainable.


Thinking Like an Architect

The world we're in is not simple. The applications we build today are complex because they are based on distributed systems, event-driven architectures, asynchronous processing, or scale-out and auto-scaling capabilities. While these are impressive capabilities, they add complexity. Models are an architect’s best tool to tackle complexity. Models are powerful because they shape how people think. Dave Farley illustrated this with an example: long ago, people believed the Earth was at the center of the universe and this belief made the planets' movements seem erratic and complicated. The real problem wasn't the planets' movements but using an incorrect model. When you place the sun at the center of the solar system, everything makes sense. Architects explaining things to others who operate differently may believe that others don't understand when they simply use a different mental model. ... Architects can make everyone else a bit smarter by seeing multiple dimensions. By expanding the problem and solution space, architects enable others to approach problems more intelligently. Often, disagreements arise when two parties view a problem from different angles, akin to debating between a square and a triangle without progress.


CrowdStrike Outage Could Cost Cyber Insurers $1.5 Billion

Most claims will center on losses due to "business interruption, which is a primary contributor to losses from cyber incidents," it said. "Because these losses were not caused by a cyberattack, claims will be made under 'systems failure' coverage, which is becoming standard coverage within cyber insurance policies." But, not all systems-failure coverage will apply to this incident, it said, since some policies exclude nonmalicious events or have to reach a certain threshold of losses before being triggered. The outage resembled a supply chain attack, since it took out multiple users of the same technology all at once - including airlines, doctors' practices, hospitals, banks, stock exchanges and more. Cyber insurance experts said the timing of the outage will also help mitigate the quantity of claims insurers are likely to see. At the moment CrowdStrike sent its update gone wrong, "more Asia-Pacific systems were online than European and U.S. systems, but Europe and the U.S. have a greater share of cyber insurance coverage than does the Asia-Pacific region," Moody's Reports said. The outage, dubbed "CrowdOut" by CyberCube, led to 8.5 million Windows hosts crashing to a Windows "blue screen of death" and then getting stuck in a constant loop of rebooting and crashing.


Open-source AI narrows gap with proprietary leaders, new benchmark reveals

As the AI arms race intensifies, with new models being released almost weekly, Galileo’s index offers a snapshot of an industry in flux. The company plans to update the benchmark quarterly, providing ongoing insight into the shifting balance between open-source and proprietary AI technologies. Looking ahead, Chatterji anticipates further developments in the field. “We’re starting to see large models that are like operating systems for this very powerful reasoning,” he said. “And it’s going to become more and more generalizable over the course of the next maybe one to two years, as well as see the context lengths that they can support, especially on the open source side, will start increasing a lot more. Cost is going to go down quite a lot, just the laws of physics are going to kick in.” He also predicts a rise in multimodal models and agent-based systems, which will require new evaluation frameworks and likely spur another round of innovation in the AI industry. As businesses grapple with the rapid pace of AI advancement, tools like Galileo’s Hallucination Index will likely play an increasingly crucial role in informing decision-making and strategy. 



Quote for the day:

"Uncertainty is a permanent part of the leadership landscape. It never goes away." -- Andy Stanley

Daily Tech Digest - March 01, 2024

Why Large Language Models Won’t Replace Human Coders

Are any of these GenAI tools likely to become substitutes for real programmers? Unless the accuracy of coding answers supplied by models increases to within an acceptable margin of error (i.e 98-100%), then probably not. Let’s assume for argument’s sake, though, that GenAI does reach this margin of error. Does that mean the role of software engineering will shift so that you simply review and verify AI-generated code instead of writing it? Such a hypothesis could prove faulty if the four-eyes principle is anything to go by. It’s one of the most important mechanisms of internal risk control, mandating that any activity of material risk (like shipping software) be reviewed and double-checked by a second, independent, and competent individual. Unless AI is reclassified as an independent and competent lifeform, then it shouldn’t qualify as one pair of eyes in that equation anytime soon. If there’s a future where GenAI becomes capable of end-to-end development and building Human-Machine Interfaces, it’s not in the near future. LLMs can do an adequate job of interacting with text and elements of an image. There are even tools that can convert web designs into frontend code.


The future of farming

SmaXtec’s solution requires cows to swallow what the company calls a “bolus” - a small device that consists of sensors to measure a cow’s pH and temperature, an accelerometer, and a small processor. “It sits inside the cow and constantly measures very important body health parameters, including temperature, the amount of water intake, the drinking volume, the activity of the animal, and the contraction of the rumen in the dairy cow,” Scherer said. Rumination is a process of regurgitation and re-digestion. “You could almost envision this as a Fitbit for cows,” he said, adding that by constantly measuring those parameters at a high density - short timeframes with high robustness and high accuracy - SmaXtec can make assessments about potential diseases that are about to break out. ... Small Robot Company is known for its Tom robot. Tom - the robot - distantly recalls memories of Doctor Who’s dog K9. The device wheels itself up and down fields, capturing images and mapping out the land. The data is then taken from Tom’s SSD and uploaded to the cloud, where an AI identifies the different plants and weeds, and provides a customized fertilizer and herbicide plan for the crops.


The CISO: 2024’s Most Important C-Suite Officer

Short- and long-term solutions to navigating increased regulatory and plaintiff bar scrutiny start with the CISO. Cybersecurity defense strategies, implementation and monitoring fall under the purview of the CISO, who must closely coordinate with other members of the C-suite as well as boards of directors. Recent lawsuits highlight individual fiduciary liability for cybersecurity controls and accurate disclosures. Individual liability demands increased knowledge of, participation in and shared ownership of cybersecurity defense decisions. Gone are the days when liability risks could be eliminated by placing the blame on a single security officer. Boards and other C-suite executives now have personal risks over company cybersecurity defenses and preparedness. CISOs carry primary ownership for formulating and maintaining robust cybersecurity defenses and preparedness. This starts with implementing secure by design and other leading security frameworks. It extends to effective real-time threat monitoring and continual technology assessment of company capabilities to defend against advanced cyber threats or the “Defining Threat of Our Time.”


Generative AI and the big buzz about small language models

LLMs can create a wide array of content from text and images to audio and video, with multimodal systems emerging to handle more than one of the above tasks. They process massive amounts of information to execute natural language processing (NLP) tasks that approximate human speech in response to prompts. As such, they are ideal for pulling from vast amounts of data to generate a wide range of content, as well as conversational AI tasks. This requires a significant number of servers, storage and the all-too-scarce GPUs that power the models — at a cost some organizations are unwilling or unable to bear. It’s also tough to satisfy ESG requirements when LLMs hog compute resources for training, augmenting, fine-tuning and other tasks organizations require to hone their models. In contrast, SLMs consume fewer computing resources than their larger brethren and provide surprisingly good performance — in some cases on par with LLMs depending on certain benchmarks. They’re also more customizable, allowing organizations to execute specific tasks. For instance, SLMs may be trained on curated data sets and run through retrieval-augmented generation (RAG) that help refine search. For many organizations, SLMs may be ideal for running models on premises.


Captive centers are back. Is DIY offshoring right for you?

Captive centers are no longer just means of value creation, providing cost savings and driving process standardization. They are driving organization-wide innovation, facilitating digital transformations, and contributing to revenue growth. Unlike earlier generations of what are increasingly being called “global capabilities centers,” which tended to be large operations set up by multinationals, more than half of last year’s new centers were launched by first-time adopters — and on the smaller side, with less than 250 full-time employees; in some cases, less than 50. The desire to build internal IT capabilities amid a tight talent market is at the heart of the trend. As companies have grown comfortable with offshore and nearshore delivery, the captive model offers the opportunity to tap larger populations of lower-cost talent without handing the reins to a third party. “Eroding customer satisfaction with outsourcing relationships — per some reports, at an all-time low — has caused some companies to opt to ‘do it themselves,’” says Dave Borowski, senior partner, operations excellence, at West Monroe. What’s more, establishing up a captive center no longer needs to be entirely DIY. 


Questioning cloud’s environmental impact

Contrary to popular belief, cloud computing is not inherently green. Cloud data centers require a lot of energy to power and maintain their infrastructure. That should be news to nobody. Cloud is becoming the largest user of data center space, perhaps only to be challenged by the growth of AI data centers, which are becoming a developer’s dream. But wait, don’t cloud providers use solar and wind? Although some use renewable energy, not all adopt energy-efficient practices. Many cloud services rely on coal-fired power. Ask cloud providers which data centers use renewable. Most will provide a non-answer, saying their power types are complex and ever-changing. I’m not going too far out on a limb in stating that most use nonrenewable power and will do so for the foreseeable future. The carbon emissions from cloud computing largely stem from the power consumed by the providers’ platforms and the inefficiencies embedded within applications running on these platforms. The cloud provider itself may do an excellent job in building a multitenant system that can provide good optimization for the servers they run, but they don’t have control over how well their customers leverage these resources.


Revolutionizing Real-Time Data Processing: The Dawn of Edge AI

For effective edge computing, efficient and computationally cost-effective technology is needed. One promising option is reservoir computing, a computational method designed for processing signals that are recorded over time. It can transform these signals into complex patterns using reservoirs that respond nonlinearly to them. In particular, physical reservoirs, which use the dynamics of physical systems, are both computationally cost-effective and efficient. However, their ability to process signals in real time is limited by the natural relaxation time of the physical system. This limits real-time processing and requires adjustments for best learning performance. ... Recently, Professor Kentaro Kinoshita, and Mr. Yutaro Yamazaki developed an optical device with features that support physical reservoir computing and allow real-time signal processing across a broad range of timescales within a single device. Speaking of their motivation for the study, Prof. Kinoshita explains: “The devices developed in this research will enable a single device to process time-series signals with various timescales generated in our living environment in real-time. In particular, we hope to realize an AI device to utilize in the edge domain.”


Agile software promises efficiency. It requires a cultural shift to get right

The end result of these fake agile practices is lip service and ceremonies at the expense of the original manifesto’s principles, Bacon said. ... To get agile right, Wickham recommended building on situations in your organization where agile is practiced relatively effectively. Most often, that involves teams building internal tools, such as administrative panels for customer support or CI/CD pipelines. Those use cases have more tolerance for “let’s put something up, ask for feedback, iterate, repeat,” he said. After all, internal customers expect to accept seeing something that’s initially imperfect. “This indicates to me that people comprehend agile and have at least a baseline understanding of how to use it, but a lack of willingness to use it as defined when it comes to external customers,” said Wickham. ... “Agile is an easy term to toss around as a ‘solution,’” Richmond said. “But effective agile does not have a cookie-cutter solution to improving execution.” Getting it right requires a focus on what has to happen to understand the company’s challenges, how those challenges manifest out of the business environment, in what way those challenges impact business outcomes, and then, finally, identifying how to apply agile concepts to the business.


Building a Strong Data Culture: A Strategic Imperative

Effective executive backing is crucial for prioritizing and financing data initiatives that help cultivate an organization’s data-centric culture. Initiatives such as data literacy programs equip employees with vital data skills that are fundamental to fostering such a culture. Nonetheless, these programs often fail to thrive without the robust support of leadership. Results from the same Alation research show that only 15 percent of companies with moderate or weak data leadership integrate data literacy across most departments or throughout the entire organization. This is in stark contrast to the 61 percent adoption rate in companies with strong data leadership. Moreover, strong data leadership involves more than just endorsement; it requires executives to actively engage and set an example in data culture initiatives. For instance, when an executive carves out time from her hectic schedule to partake in data literacy training, it conveys a much more powerful message to her team than if she were to simply instruct others to prioritize such training. This hands-on approach by leaders underscores the importance of data literacy and demonstrates their commitment to embedding a data-driven culture in the organization.


Cybercriminals harness AI for new era of malware development

Threat actors have already shown how AI can help them develop malware only with a limited knowledge of programming languages, brainstorm new TTPs, compose convincing text to be used in social engineering attacks, and also increase their operational productivity. Large language models such as ChatGPT remain in widespread use, and Group-IB analysts have observed continued interest on underground forums in ChatGPT jailbreaking and specialized generative pre-trained transformer (GPT) development, looking for ways to bypass ChatGPT’s security controls. Group-IB experts have also noticed how, since mid-2023, four ChatGPT-style tools have been developed for the purpose of assisting cybercriminal activity: WolfGPT, DarkBARD, FraudGPT, and WormGPT – all with different functionalities. FraudGPT and WormGPT are highly discussed tools on underground forums and Telegram channels, tailored for social engineering and phishing. Conversely, tools like WolfGPT, focusing on code or exploits, are less popular due to training complexities and usability issues. Yet, their advancement poses risks for sophisticated attacks.



Quote for the day:

"It takes courage and maturity to know the difference between a hoping and a wishing." -- Rashida Jourdain

Daily Tech Digest - November 25, 2023

Building a Successful Data Quality Program

Assessing Data Quality often includes establishing a standard of acceptable Data Quality, using data profiling and analysis techniques, and using statistical methods to identify and correct any Data Quality issues. The key features (often called “dimensions”) that should be examined and measured are: Completeness:- Data should not be missing or have incomplete values. Uniqueness:- Locate and eliminate copies to ensure the information in the organization’s data files is free of duplication. Validity:- This refers to how useful the data is, and how well the data conforms to the organization’s standards. Timeliness:- Old information that is often no longer true or accurate needs to be removed. Data can be measured using its relevance and freshness. Out-of-date data should be eliminated, so as not to cause confusion. Accuracy:- This is the precision of data, and how accurately it represents the real-world information. Consistency:- When data is copied, the information should be consistent and accurate. The need for a single source of accurate in-house data provides a good argument for the use of master data and its best practices.


Building brand trust in a new era of data privacy

Emily emphasized the importance of anonymizing data to utilize it in aggregate without compromising individual privacy, a task that requires close collaboration between technical and marketing departments. Anita introduced the intriguing concept of a Chief Trust Officer, a role highlighted by Deloitte, which spans data, business, and marketing, safeguarding all aspects of compliance and privacy. The idea of having such a partner resonated with her, underlining the multifaceted nature of trust in business operations. Jake echoed the sentiment, stressing the need for understanding the types of data at hand and leveraging them without violating regulations - a balance that is critical yet challenging to achieve. These insights from the panelists underscore a common theme: building brand trust in the digital age is a multifaceted challenge that requires a blend of transparency, consistency, and compliance. As we continue to delve into this topic, it's clear that the role of data privacy is not just a technical issue but a cornerstone of the customer-brand relationship.


How Does Technical Debt Affect QA Testers

How many times have your testers been caught off guard at the last minute when the delivery manager abruptly appeared and said, “Guys, we need to launch our product in a week, and we are very sorry for not communicating this sooner? Please complete all test tasks ASAP so that we can begin the demo.” Simply put, any missing tests or “fix it later” attitude can result in a tech debt problem. Lack of test coverage, excessive user stories, short sprints, and other forms of “cutting corners” due to time constraints all contribute significantly to the building of technical debt in QA practice. When the complexity of the testing mesh began to grow with each new sprint, a US-based online retailer with a strong presence across various websites and mobile apps found itself in a real-world “technical debt” dilemma. ... Most QA managers mistakenly believe that tech debt is a legitimate result of putting all of your work on the current sprint alone, which leads to completing test coverage manually and completely ignoring automation. According to agile principles, we should see the tech debt problem as an inability to maintain and meet QA benchmarks.


How digital twins will enable the next generation of precision agriculture

Digital twins are digital representations of physical objects, people or processes. They aid decision-making through high-fidelity simulations of the twinned physical system in real time and are often equipped with autonomous control capabilities. In precision agriculture, digital twins are typically used for monitoring and controlling environmental conditions to stimulate crop growth at an optimal and sustainable rate. Digital twins provide a live dashboard to observe the environmental conditions in the growing area, and with varying autonomy, digital twins can control the environment directly. ... Agriculture is among the lowest-digitalized sectors, and digital maturity is an absolute prerequisite to adopting digital twins. As a consequence, costs related to digital maturity often overshadow technical costs in smart agriculture. A company undergoing the early stages of digitalization will have to think about choosing a cloud provider, establishing a data strategy and acquiring an array of software licences, to name just a few critical challenges.


What are Software Design Patterns?

Software design patterns are an essential aspect of software development that helps developers and engineers create reusable and scalable code. These patterns provide solutions to commonly occurring problems in software design, enabling developers to solve these problems efficiently and effectively. In essence, a software design pattern is a general solution to a recurring problem in software design that has been proven to be effective. It's like a blueprint for a specific type of problem that developers can use to create software systems that are reliable, maintainable, and scalable. Software design patterns have been around for a long time and are widely used in the software development industry. They are considered to be a best practice in software design because they provide a standardized approach to solving common problems, making it easier for developers to communicate and collaborate with one another. In this blog, we will explore what software design patterns are, the different types of software design patterns, and the benefits of using them in software development. 


Examples of The Observer Pattern in C# – How to Simplify Event Management

The observer pattern is an essential software design pattern used in event-driven programming and user interface development. It is composed of three primary elements: the subject, observer, and concrete observers. The subject class is responsible for keeping track of the observer objects and notifying them of changes in the subject’s state. On the other hand, the observer is the object that wishes to be notified when the state of the subject changes. Finally, the concrete observer is an implementation of the observer interface. One of the observer pattern’s significant advantages is its capability to facilitate efficient event management in software development. By leveraging this ability, developers can trigger related events without the need for tightly coupling the pieces of code leading to the events. The observer pattern also ensures that the code continues to be free from changes that would cause a ripple effect or the chain reaction of changes. The observer pattern’s primary components are the Subject, Observer, and Concrete Observer. The subject defines the interface for attaching and detaching observers from the subject object. 


Cloud Computing: A Comprehensive Guide to Trends and Strategies

As a company moves to the cloud, they reduce the number of servers and other hardware their IT department has to maintain. Cloud computing efficiently uses today’s powerful processors, fast networks, and massive amounts of storage. Cloud virtual machines allow businesses to run multiple servers on one physical machine. Containers take that concept a step further. Containers are a lightweight form of virtualization that packages applications and their dependencies in a portable manner. This means that if, for instance, a company wants to run a web server, they no longer have to devote physical or virtual machines to host the server software. A container with only the needed bits runs in the cloud, appearing to the outside world as if it were its dedicated machine. Many containers can run in the same cloud instance for maximum efficiency. This approach is sometimes called serverless computing or Function as a Service (FaaS). The application-level isolation inherent in serverless computing restricts the attack surface that attackers can exploit.


Judges Urged To Stay Abreast Of Electronic Tools

The Cyber Security Authority (CSA), with funding support from the European Commission Technical Assistance and Information Exchange (TAIEX) Instrument is undertaking a series of workshops across Ghana to enhance the capacity of the judiciary and prosecutors regarding cybercrime and electronic evidence as a decisive factor in contributing to the rule of law. Expressing excitement about the training, the Chief Justice said e-commerce, e-trade, e-contracts, and intellectual property rights, among others, were now being conducted virtually, and the expertise of judges in these new trends was a prerequisite for the efficient trial of cyber-related cases, particularly in the gathering of electronic data. “Judges must develop new working skills by staying abreast of the digital space. You must develop leadership skills in this arena if you want to remain relevant in the system,” she stressed. Albert Antwi-Boasiako, stated that the major regulatory activity being undertaken by the Authority to license cybersecurity service providers and accredit cybersecurity establishments and professionals was tailored to support the training of the judges.


Candy Alexander Explains Why Bandwidth and Security are Both in High Demand

It became painfully clear to everyone that the primary component for productivity depended on bandwidth. The increased bandwidth of networks has become the primary factor of success; whether you're a business just looking to ensure the productivity of your remote workers or provide a cloud service, throughput is everything. And with that, the world has expanded ubiquitous access and high availability of networks. In today's digital world, businesses of all sizes rely on data. That data is used to make decisions, operate efficiently, and serve customers. Data is essential for everything, from product to development, marketing, and customer support. However, with the rise of remote work and cloud computing, it has become more challenging to ensure that the data is always accessible and secure. The application of cybersecurity's golden triad of confidentiality, integrity, and availability is now focused on data rather than the on-premises systems and networks. Again, it's data that has become more important than ever before. 


Why Departments Hoard Data—and How to Get Them to Share

"Data hoarding within organizations can be attributed to a combination of cultural, operational and psychological factors," said Jon Morgan, CEO and editor-in-chief of Venture Smarter, a consulting firm in San Francisco. "When departments view data as a source of power or control, they are less inclined to share it with others, fearing that it might diminish their influence." Operational inefficiencies can also lead to data hoarding. "If access to data is cumbersome or time-consuming, employees may be less motivated to share it, preferring to keep it close for their own convenience," Morgan said. In addition, "psychological factors like fear of criticism or a desire to protect one's domain can also drive data hoarding." Employees may worry that sharing data will expose their mistakes or weaknesses, leading to a reluctance to collaborate, he said. Jace McLean, senior director of strategic architecture at Domo, a data platform based in American Fork, Utah, said he believes that cultural factors are the most important lever to use in changing data-hoarding habits. 



Quote for the day:

"If you don't demonstrate leadership character, your skills and your results will be discounted, if not dismissed." -- Mark Miller

Daily Tech Digest - June 04, 2023

Insider risk management: Where your program resides shapes its focus

Choi says that while the information security team is ultimately responsible for the proactive protection of an organization’s information and IP, most of the actual investigation into an incident is generally handled by the legal and HR teams, which require fact-based evidence supplied by the information security team. “The CIO/CISO team need to be able to supply facts and evidence in a consumable, easy-to-understand fashion and in the right format so their legal and HR counterparts can swiftly and accurately conduct their investigation.” ... Water flows downhill and so does messaging on topics that many consider ticklish, such as IRM programs. Payne noted that “few, if any CEOs wish to discuss their threat risk management programs as it projects negativity — i.e., ‘we don’t trust you’ and they prefer to have positive messaging.” Few CISOs enjoy having an IRM program under their remit as “who wants to monitor their colleagues?” Payne adds, “Whacking external threats is easy; when it’s your colleague it becomes more problematic.”


What is the medallion lakehouse architecture?

The medallion architecture describes a series of data layers that denote the quality of data stored in the lakehouse. Databricks recommends taking a multi-layered approach to building a single source of truth for enterprise data products. This architecture guarantees atomicity, consistency, isolation, and durability as data passes through multiple layers of validations and transformations before being stored in a layout optimized for efficient analytics. The terms bronze (raw), silver (validated), and gold (enriched) describe the quality of the data in each of these layers. It is important to note that this medallion architecture does not replace other dimensional modeling techniques. Schemas and tables within each layer can take on a variety of forms and degrees of normalization depending on the frequency and nature of data updates and the downstream use cases for the data. Organizations can leverage the Databricks Lakehouse to create and maintain validated datasets accessible throughout the company. 


AppSec ‘Worst Practices’ with Tanya Janca

Having reasonable service-level agreements is so important. When I work with enterprise clients, they already have tons of software that’s in production doing its thing, but they’re also building and updating new stuff. So I have two service-level agreements and one is the crap that was here when I got here and the other stuff is all the beautiful stuff we’re making now. So I’ll set up my tools so that you can have a low vulnerability, but if it’s medium or above, it’s not going to production if it’s new. But all the stuff that was there when I scanned for the first time, we’re going to do a slower service-level agreement. That way we can chip away at our technical debt. The first time I came up with parallel SLAs was when this team lead asked, “Am I going to get fired because we have a lot of technical debt, and it would literally take us a whole year just to do the updates from the little software compositiony thing you were doing.” “No one’s getting fired!” I said. So that’s how we came up with the parallel SLAs so we could pay legacy technical debt down slowly like a student loan versus handling new development like credit card debt that gets paid every single month. There’s no running a ticket on the credit card!


Revolutionizing the Nine Pillars of DevOps With AI-Engineered Tools

Leadership Practices: Leadership is vital to drive cultural changes, set vision and goals, encourage collaboration and ensure resources are allocated properly. Strong leadership fosters a successful DevOps environment by empowering teams and supporting innovation. AI can assist leaders in decision-making by analyzing large datasets to identify trends and predict outcomes, providing valuable insights to guide strategic planning. Collaborative Culture Practices: DevOps thrives in a culture of openness, transparency and shared responsibility. It’s about breaking down the silos that can exist between different teams and promoting effective communication and collaboration. AI-powered tools can improve collaboration through smart recommendations, fostering more effective communication and knowledge sharing. Design-for-DevOps Practices: This involves designing software in a way that supports the DevOps model. This can include aspects like microservices architecture, modular design and considering operability and deployability from the earliest stages of design.


The ethics of innovation in generative AI and the future of humanity

Humans answer questions based on our genetic makeup (nature), education, self-learning and observation (nurture). A machine like ChatGPT, on the other hand, has the world’s data at its fingertips. Just as human biases influence our responses, AI’s output is biased by the data used to train it. Because data is often comprehensive and contains many perspectives, the answer that generative AI delivers depends on how you ask the question. AI has access to trillions of terabytes of data, allowing users to “focus” their attention through prompt engineering or programming to make the output more precise. This is not a negative if the technology is used to suggest actions, but the reality is that generative AI can be used to make decisions that affect humans’ lives. ... We have entered a crucial phase in the regulatory process for generative AI, where applications like these must be considered in practice. There is no easy answer as we continue to research AI behavior and develop guidelines


7 CIO Nightmares And How Enterprise Architects Can Help

The deeper you dig into cyber security, the more you find. Do you know what data your business actually needs to secure? A mission-critical application might be dependent on a spreadsheet in an outdated system. That data may be protected under regulation, but supplied from a cloud-based application that's reliant on open-source coding, and so on. Every CIO needs to know the top-ten, mission-critical, crown jewel applications and data centers that their business cannot live without, and what their connections and dependencies are. Each needs to have a clear plan of action in case of a security breach. The Solution: Mapping your tech stack with an enterprise architecture management (EAM) tool allows you to see exactly how mission critical each application is. This equates one-to-one with how much you need to invest in cyber security for each area. You can also gain clarity on which application is dependent on which platform. Likewise, you can find where crucial data is stored and where it feeds to.


7 Stages of Application Testing: How to Automate for Continuous Security

Pen testing allows organizations to simulate an attack on their web application, identifying areas of weaknesses that could be exploited by a malicious attacker. When done correctly, pen testing is an effective way to detect and remediate security vulnerabilities before they can be exploited. ... Traditional pen testing delivery often takes weeks to set up and the results are point in time. With the rise of DevOps and cloud technology, traditional once-a-year pen testing is no longer sufficient to ensure continuous security. To protect against emerging threats and vulnerabilities, organizations need to execute ongoing assessments: continuous application pen testing. Pen Testing as a Service (PTaaS) offers a more efficient process for proactive and continuous security compared to traditional pen testing approaches. Organizations are able to access a view into to their vulnerability finding in real time, via a portal that displays all relevant data for parsing vulnerabilities and verify the effectiveness of a remediation as soon as vulnerabilities are discovered.


Technological Innovation Poses Potential Risk of Rising Agricultural Product Costs

While technology has undeniably improved farming practices, its implementation requires significant financial investment. The upfront costs associated with purchasing advanced machinery, upgrading infrastructure, and adopting new technologies can burden farmers, particularly smaller-scale operations. These costs can ultimately be passed on to consumers, potentially leading to an increase in the prices of agricultural products. The seductive promises of cutting-edge machinery, precision agriculture, and genetically modified crops have mesmerised farmers worldwide. It is true, these technological marvels have unleashed unprecedented efficiency, capable of revolutionising the way we grow and harvest our sustenance. Yet, in their wake, they leave a trail of exorbitant expenses, shaking the very foundation of the agricultural landscape. ... Modern farming equipment is often equipped with advanced technology and features that improve efficiency, precision, and productivity.


Open Source Jira Alternative, Plane, Lands

Indeed, “Plane is a simple, extensible, open source project and product management tool powered by AI. It allows users to start with a basic task-tracking tool and gradually adopt various project management frameworks like Agile, Waterfall, and many more, wrote Vihar Kurama, co-founder and COO of Plane, in a blog post. Yet, “Plane is still in its early days, not everything will be perfect yet, and hiccups may happen. Please let us know of any suggestions, ideas, or bugs that you encounter on our Discord or GitHub issues, and we will use your feedback to improve on our upcoming releases,” the description said. Plane is built using a carefully selected tech stack, comprising Next.js for the frontend and Django for the backend, Kurama said. “We utilize PostgreSQL as our primary database and Redis to manage background tasks,” he wrote in the post. “Additionally, our architecture includes two microservices, Gateway and Pilot. Gateway serves as a proxy server to our database, preventing the overloading of our primary server, while Pilot provides the interface for building integrations. ...”


Emerging AI Governance is an Opportunity for Business Leaders to Accelerate Innovation and Profitability

Firstly, regulation can help establish clear guidelines and standards for developing and deploying AI systems, for example, standards in accuracy, reliability, and risk management. Such guidelines can provide a stable and predictable framework for innovation, reducing uncertainty and risk in AI system development. This will increase participation in the field from developers and encourage greater investment from public and private organizations, thereby boosting the industry as a whole. ... Governments and governance organizations have a strong history of successfully investing in AI technologies and their inputs (e.g., Open Data Institute, Horizon Europe), as well as acting as demand side stimulators for long-term, high-risk innovations that are the foundations of many of the technologies we use today. Such examples include innovation at DARPA that formed the foundations of the Internet, or financial support to novel technologies through subsidy systems e.g., consumer solar panels.



Quote for the day:

"Try not to become a man of success but a man of value." -- Albert Einstein

Daily Tech Digest - May 14, 2023

How to Balance Data Governance with Data Democracy

Data democratization is important to an organization because it ensures an effective and efficient method of providing all users, regardless of technical expertise, the ability to analyze readily accessible and reliable data to influence data-driven decisions and drive real-time insights. This eliminates the frustration of requesting access, sorting information, or reaching out to IT for help. ... The solution to this problem lies in data federation, which makes data from multiple sources accessible under a uniform data model. This model acts as a "single point of access" such that organizations create a virtual database where data can be accessed where it already lives. This makes it easier for organizations to query data from different sources in one place. With a single point of access, users can go to one location for searching, finding, and accessing every piece of data your organization has. This will make it easier to democratize data access because you won’t need to facilitate access across many different sources.


Will ChatGPT and Generative AI “Replace” Testing?

It stands to reason, then, that ChatGPT and generative AI will not "replace" testing or remove the need to invest in QA. Instead, like test execution automation before it, generative AI will provide a useful tool for moving faster. Yet, there will always be a need for more work, and at least a constant (if not greater) need for human input. Testers' time might be applied less to repetitive tasks like scripting, but new processes will fill the void. Meanwhile, the creativity and critical thinking offered by testers will not diminish in value as these repetitive processes are automated; such creativity should be given greater freedom. At the same time, your testers will have vital insight into how generative AI should be used in your organization. Nothing is adopted overnight, and identifying the optimal applications of tools like ChatGPT will be an ongoing conversation, just as the testing community has continually explored and improved practices for getting the most out of test automation frameworks. Lastly, as the volume of possible test scenarios grows, automation and AI will need a human steer in knowing where to target its efforts, even as we can increasingly use data to target test generation.


How agtech is poised to transform India into a farming powerhouse

Collaboration will be crucial. While agtechs might facilitate better decision making and replace manual farming practices like spraying, reducing dependence on retailers and mandis, incumbents remain important in the new ecosystem for R&D and the supply of chemicals and fertilizers. There are successful platforms already emerging that offer farmers an umbrella of products and services to address multiple, critical pain points. These one-stop shop agri-ecosystems are also creating a physical backbone/supply chain—which makes it easier for incumbents and start-ups to access the fragmented farmer base. Agtechs have a unique opportunity to become ideal partners for companies seeking market access. In this scenario, existing agriculture companies are creating value for the farmer by having more efficient and cost-effective access to the farmer versus traditional manpower-intensive setups. It’s a system that builds: the more agtechs know the farmer, the better products they can develop. India’s farms have been putting food on the table for India and the world for decades. 


How A Non Data Science Person Can Work Effectively With A Data Scientist

Effective communication is essential for a successful partnership. The data scientist should communicate technical procedures and conclusions in a clear and concise manner. In contrast, the non-data science person should communicate business requirements and limitations. Both sides can collaborate successfully by developing a clear understanding of the project objectives and the data science methodologies. Setting expectations and establishing the project’s scope from the beginning is equally critical. The non-data scientist should specify what they expect from the data scientist, including the results they intend to achieve and the project’s schedule. In return, they should describe their areas of strength and the achievable goals that fall within the project’s parameters. It is crucial to keep the lines of communication open and transparent throughout the process. Regular meetings and status reports should be organized to keep everyone informed of the project’s progress and to identify any potential issues.


Why Metadata Is a Critical Asset for Storage and IT Managers

Advanced metadata is handled differently by file storage and object storage environments. File storage organizes data in directory hierarchies, which means you can’t easily add custom metadata attributes. ... Metadata is massive because the volume and variety of unstructured data – files and objects – are massive and difficult to wrangle. Data is spread across on-premises and edge data centers and clouds and stored in potentially many different systems. To leverage metadata, you first need a process and tools for managing data. Managing metadata requires both strategy and automation; choosing the best path forward can be difficult when business needs are constantly changing and data types may also be morphing from the collection of new data types such as IoT data, surveillance data, geospatial data, and instrument data. Managing metadata as it grows can also be problematic. Can you have too much? One risk is a decrease in file storage performance. Organizations must consider how to mitigate this; one large enterprise we know switched from tagging metadata at the file level to the directory level.


Understand the 3 major approaches to data migration

Application data migration—sometimes called logical data migration or transaction-level migration—is a migration approach that utilizes the data mobility capabilities built natively into the application workload itself. ... Technique: Some applications offer proprietary data mobility features. These capabilities usually facilitate or assist with configuring backups or secondary storage. These applications then synchronously or asynchronously ensure that the secondary storage is valid and, when necessary, can be used without the primary copy. ... Block-level data migration is performed at the storage volume level. Block-level migrations are not strictly concerned about the actual data stored within the storage volume. Rather, they include file system data of any kind, partitions of any kind, raw block storage, and data from any applications. Technique: Block-level migration tools synchronize one storage volume to another storage volume from the beginning of the volume (byte 0) to the end of the entire volume (byte N) without processing any data content.


Open Source MongoDB Alternative FerretDB Now Generally Available

FerretDB works as a proxy that translates MongoDB wire protocol queries to SQL, with PostgreSQL as the database backend. Started as an open-source alternative to MongoDB, FerretDB provides the same MongoDB APIs without developers needing to learn a new language or command. Peter Farkas, co-founder and CEO of FerretDB, explains: We are creating a new standard for document databases with MongoDB compatibility. FerretDB is a drop-in replacement for MongoDB, but it also aims to set a new standard that not only brings easy-to-use document databases back to its open-source roots but also enables different database engines to run document database workloads using a standardized interface. While FerretDB is built on PostgreSQL, the database is designed with a pluggable architecture to support other backends, with projects for Tigris, SAP HANA, and SQLite currently in the working. Written in Go, the project was originally started as the Server Side Public License (SSPL) that MongoDB adopted in 2018 does not meet all criteria for open-source software set by the Open Source Initiative.


Wardley Mapping and Strategy for Software Developers

This is a more engineering-focused way to look at a business and isn’t dependent on stories, aphorisms or strange MBA terms. A few people have asked me personally whether this method really works. But it isn’t a “method” as such; just a way to agree on the environment that may otherwise be left unchallenged. Jennifer Riggins has already covered the background to Wardley mapping in detail, so I only need to summarize what we need to become aware of. ... So how do you map your own projects? One good start is simply to get your team together and see if they can map just the build process — with a build as the final product (the cup of tea). For example; starting from an agreed story, through to a change in the code in the repository, to a checkout into a staging build, to deployment. See if everyone even agrees what this looks like. The result should eventually be a common understanding. There are plenty of introductions to mapping, but the important thing is to recognize that you can represent a business in a fairly straightforward way. 


The Leader's Role in Building Independent Thinkers: How to Equip Your Team for Success

Striving for perfection can often lead to "analysis paralysis," hindering progress and preventing team members from taking action. To encourage independent thinking, leaders must prioritize action over perfection. By creating a culture of experimentation and iteration, employees learn from their mistakes, build confidence, and become less afraid of failure. ... Standing firmly behind your values and vision is a powerful way for leaders to generate independent thinking in their teams. When team members see their leader living by strong values and embodying a clear vision, they feel empowered to follow their example. This approach cultivates an environment of trust and confidence, enabling your employees to think critically and independently. ... It is essential for leaders to avoid merely delegating tasks and stepping back. Instead, actively participate in the work alongside your team, providing guidance and offering support when needed. This approach instills a sense of collaboration and helps your team feel part of something bigger. 


The Great Resignation takes a dark turn: Is it now the Great Layoff? Expert weighs in

The main challenges that Gen-Z employees face in the event of a layoff are a lack of savings, a lack of job experience, and a lack of job security. Many Generation Z workers are just starting out in their careers and haven't had time to save. Many people may have little or no savings in case of a financial emergency, such as job loss. Because Generation Z is so young, they have yet to have the opportunity to gain the experience that their elders have. If they are laid off, they are concerned that they will not have the necessary experience to re-enter the workforce. Finally, even if Gen Z workers are employed, they may believe their job is in jeopardy due to the pandemic's impact on their industry. They may be concerned that their employer will lay off employees or that their position will become obsolete as the company adapts to the changing business environment. Because of these challenges and ongoing economic uncertainty, Generation Z remains concerned about the possibility of layoffs. 



Quote for the day:

"Innovation distinguishes between a leader and a follower." -- Steve Jobs

Daily Tech Digest - January 12, 2023

Agritech forces gain ground across Africa

One of the crucial issues that agriculture in Africa is currently solving, according to Gaddas, is a lack of water. He says that in Senegal, Tunisia and many other countries, companies are working hard on intelligent irrigation, and on how to optimize water resources that are becoming increasingly scarce, especially in the context of climate change and unpredictable rainfall. “Managing water is becoming crucial,” he says. “We’ve met start-ups that use drones, which, through their precision devices, help to collect data that can be used by farmers, such as the levels of nitrogen from the fields, precise mapping of areas with fertiliser deficits,and others that solve plant disease problems by making diagnoses. There are also ERP systems for farm management and to know what is happening in real time—the management of inputs, fertilizers and more.” He also appreciated the digital aquaculture companies that allow for very rational management of aquaculture farms, while praising the impressive diversity of solutions. “The diversity of problems that farmers face in Africa is very wide but creativity is not the weak point of Africans,” he says. 


Ushering in an era of pervasive intelligence, powered by 6G

The impact that this new era will have cannot be understated. It will power economies, drive sector convergence, enable the distributed infrastructure behind Web 3.0 and scale and interconnect metaverses. Put simply, it will transform all aspects of life. But getting there isn’t straightforward, and we need to act now to lay the foundations that are necessary if we are to harness its power. This on its own is not the most straightforward undertaking, as is evidenced by the issues with the 5G+ rollout and adoption. The right infrastructure and business models were not in place, which led to delays and innovative potential left on the table. Let’s learn from past mistakes, course correct and ensure we’re ready for the future of pervasive intelligence. ... Transformation into the pervasive intelligence era will first require the establishment of a high performance, integrated ecosystem made up of a range of partners from different industries and sectors. This is critical as pervasive intelligence will only be reached in an environment where data and information can move freely and securely. This, however, cannot happen if companies operate in silos or in isolation.


DeFi Labs Revolutionises Decentralized Finance by Leveraging AI

According to the co-founder of DeFiLabs, “With our AI-powered yield farm, we’re introducing a new level of innovation to the DeFi space. We’re making it possible for users of all levels to earn high returns on their investments, while also minimizing risk. Our goal is to provide our users with the best investment opportunities available in the DeFi space, and our AI-powered yield farm is just the beginning. We’re excited to see how our users will benefit from this new offering.” This launch is also a significant step for the Binance Smart Chain ecosystem, as it showcases the capabilities and the potential for growth of Binance Smart Chain. This yield farm will encourage the usage of the Binance Smart Chain and drive the adoption of DeFi on this network. The yield farm is live and fully operational, and users can start staking their Binance Coin (BNB) or other supported tokens to earn high returns on their investments. The DeFiLabs team is constantly working to add new features, tokens, and investment options to the yield farm, making it even more valuable for users.


The importance of collaboration in maximising cybersecurity

The CISO has a vital role within companies, and one which is currently evolving. Beyond technical knowledge, one of the most important aspects of the CISO’s role in an enterprise is collaboration. Information, security and data protection controls permeates all levels and departments of a company, not just limited to tech. As such, it is important to relay technical information succinctly to all relevant directors and parties, ensuring all teams are adequately equipped to manage cyber risks. There is a wide range of cybersecurity services that can be adopted. This includes perimeter and cloud security, device security, network security, threat hunting, DevSecOps, and web and mobile application security. To make them all function, and operate as tightly as possible, you must work with a team of experts, to ensure that your company is at the forefront of new advances in cybersecurity. The removal of silos is therefore integral to ensuring companies are prepared and equipped to defend themselves against cyber-attacks.


IT supply issues have organizations shifting from just-in-time to just-in-case buying

One thing more enterprises should be looking for is greater visibility from their suppliers. "A lot of people are realizing that we're living in a more transparent world now," said Genpact's Waite. And integration between companies has increased, with some providers offering more information to their customers. ... With this approach, vendors are selected not just based on technical fit, form, and function but also based on where in the world they source their materials, or how big of a company they are. Supply chain visibility is particularly important for manufacturers. They need to know if the supplies they need are on track, or if alternate sources have to be found in order to avoid production delays. "Our supply chain is built entirely on transparency," says Carl Nothnagel, COO at specialty hardware manufacturer MBX Systems. "With every supplier, we push for that information. Sometimes we don’t get it, and we’re left with projecting, or guessing as best as we can. We have some manufacturers that are very transparent and we can see where it's going to hit every day, and some are a bit of black hole."


6 Data Governance Principles Corporate Leaders Should Apply in 2023

The success of your data governance plan depends on what your employees do with the data they handle. Therefore, once you’ve created a data governance plan, you should share it with your employees. Successful data governance requires a holistic, organization-wide approach that demands transparency across your organization. You can further demonstrate internal transparency by documenting all data governance decisions and actions. This documentation can help you learn from past mistakes and protect your corporation if you experience a data breach, lawsuit, investigation, or other regulatory action. ... Responsibility and accountability are integral parts of any corporation’s data governance processes. Traditionally, your information technology (IT) department would be responsible for managing your corporation’s data. But now that most—if not all—of your employees deal with data on a daily basis, employees throughout your organization must see themselves as the stewards of your data. So, who is responsible for what data? That is something you will need to decide. 


Study shows attackers can use ChatGPT to significantly enhance phishing and BEC scams

The more complex and long a phishing message is, the more likely it is that attackers will make grammatical errors or include weird phrasing that careful readers will pick up on and become suspicious. With messages generated by ChatGPT, this line of defense that relies on user observation is easily defeated at least as far as the correctness of the text is concerned. Detecting that a message was written by an AI model is not impossible and researchers are already working on such tools. While these might work with current models and be useful in some scenarios, such as schools detecting AI-generated essays submitted by students, it's hard to see how they can be applied for email filtering because people are already using such models to write business emails and simplify their work. "The problem is that people will probably use these large language models to write benign content as well," WithSecure Intelligence Researcher Andy Patel tells CSO. ... Attackers can take it much further than writing simple phishing lures. They can generate entire email chains between different people to add credibility to their scam.


Insights on Nordic artificial intelligence strategies

The Nordics are generally early adopters of technology – and AI is no exception. More than 25% of the Nordic companies are already investing at least 20% of their research and development budget in AI projects. Moreover, the Nordic countries are planning to get ahead – or at least keep up with other industrial nations. Each of the four countries have at least one top-ranking AI-related educational institution – and private investment in AI has more than doubled in the region since 2021. ... Finnish AI research runs primarily along three different dimensions. The first is to optimise the performance of AI algorithms to head off the problem where computational requirements get too far ahead of what hardware can deliver. As a small country, Finland is particularly sensitive to the increasing costs of computational power – even though they house what is currently Europe’s most powerful supercomputer, LUMI. The second dimension is trustworthy AI. Ethics and values are important to Finland, as they are in all other Nordic countries. Research in trustworthy AI aims to overcome the complex ethical challenges inherent to AI.


Structured Data Management for Discovery and Insight

Polanco says the chief data officer, chief compliance officer, and CISO should collaborate on finding an effective structured data management practice that provides a well-governed, fully-compliant data architecture that connects data sources for data consumers. “Data must be findable, accessible, interoperable, and re-usable for [data] consumers, while also ensuring compliance with data quality standards and data security and privacy measures,” he adds. Anyone in a managerial position who encounters data will likely have considered best practices for data management already. “While those managers may be responsible for implementing data management resources for their respective teams, the initial solution can come from technology companies that weld together the manual knowledge of what the data needs to look like and the efficiency of a more automated sorting process,” Polanco says. Macosky adds that while the chief data officer position is fairly new across industries, he expects to see the role become more important and vital as organizations prioritize and value data management.


How to Measure the Energy Consumption of Bugs

It is very important to always have the underlying architecture and communication to all the connected services in mind. Often it may seem that a bug does not affect energy consumption at first sight. This impression can quickly change when the broader context of the feature where it occurs is taken into account. A QA engineer needs to understand communication between the services, how it is implemented (in collaboration with the developers), when it takes place, where it initiated, and where the services and features run. In practice this means that QA engineers who want to measure the energetic impact of their product in more detail must not only understand the customers’ perspective (as usual), but in addition many implementation details from different perspectives. Where do particular services run? On which infrastructure? Which libraries are used? How can the implementation of the product be modified in order to measure energy consumption. Improvement of energy consumption is not something that can be activated by just pushing a button. 



Quote for the day:

"If you don't demonstrate leadership character, your skills and your results will be discounted, if not dismissed." -- Mark Miller