Daily Tech Digest - June 18, 2024

The Intersection of AI and Wi-Fi 7

Wi-Fi 7 is the newest standard in wireless networking. Though official ratification isn't expected until the end of 2024, Wi-Fi 7 client devices and wireless access points are already available. The top line speed of Wi-Fi 7 is often stated at 46 Gbps, but actual speeds will be lower. The higher speeds of Wi-Fi 7 are delivered by using a 320 MHz wide channel, increasing the transmission rate to 4K QAM and increasing the number of transmit and receive chains to 16. Another key advantage of Wi-Fi 7 is a significant reduction in packet latency, thanks to a feature called Multi-Link Operation (MLO). ... AI Autonomous Networks consolidate key performance indicators to aid decision-making. During the shift from 2.4 GHz and 5 GHz to 6 GHz networking, IT managers can use AI to expose timing and predict improvements, facilitating timely network upgrades. Another example is digital twin architecture, which simulates the network environment using real-world client analytics to model behavior, evaluate security changes, and assess configuration adjustments. The goal is to provide IT managers with tools for timely and accurate decisions.

Linux in your car: Red Hat’s milestone collaboration with exida

Red Hat’s collaboration with exida marks a significant milestone. While it may not be obvious to all of us, Linux is playing an increasingly important role in the automotive industry. In fact, even the car you’re driving today could be using Linux in some capacity. Linux is very well known and appreciated in the automotive industry with increasing attention being paid both to its reliability and its security. The phrase “open source for the open road” is now being used to describe the inevitable fit between the character of Linux and the need for highly customizable code in all sorts of automotive equipment. The safety of vehicles that get us from one place to another on a nearly daily basis has become a serious priority. ... Their focus on ensuring the safety of both individual components and the operating system as a whole is crucial. This latest achievement brings them even closer to realizing the first continuously-certified in-vehicle Linux Red Hat In-Vehicle Operating System. Their open source first approach to the organization, culture and thought process is an exemplary superset of what exida regards as a best practice for world-class safety culture. 

How CIOs Can Integrate AI Among Employees Without Impacting DEI

As technology adoption accelerates, employees risk falling behind in adapting to meet enterprise demands. This trend has been evident across computing eras, from PCs to the current AI and Internet of Things era. Each phase widens the gap between technology introduction and employees’ ability to use it effectively. ... To prioritize DEI in addressing employee upskilling to leverage AI, CIOs can embrace a spectrum of initiatives, from establishing peer mentorship programs to providing access to online courses, workshops, and conferences. The aim is to promote educational opportunities for those most at risk of falling behind, which will increase the cost risk in the future due to the extra cost of retraining staff or seeking new talent. To successfully link digital dexterity to DEI to prepare employees, CIOs should implement a training program that equitably exposes all workforce segments to AI and the machine economy to develop soft and technical skills. Shift the focus of AI adoption away from solely business needs and focus on individual empowerment

What is a CAIO — and what should they know?

CAIOs and others tasked with overseeing AI deployments play an essential role in “shaping an organization’s strategic, informed and responsible use of AI,” he said. “There are many responsibilities baked into the role, but at its core, it’s about steering the direction of AI initiatives and innovation to align with company goals. AI leads must also create a culture of collaboration and continuous learning.” ... While CAIOs might not always be seated at the C-suite table, those who are there are keenly focused on genAI and its potential to drive efficiencies and profits. Without an executive guiding those deployments, achieving the performance and ROI organizations seek will be tough, she said. “It’s hard to imagine how pieces come together and how you’d bring together so many players,” Kosar said, noting that PwC has more than a dozen different LLMs running internally to power AI tools and products in virtually every business unit. “You have to have the ability to do short-term and long-term planning and balance the two and stay focused on innovation,” she continued. “At the same time, you need to recognize the pace of change while not getting distracted by the latest shiny object.”

How AI is impacting data governance

Every organization needs to establish policies around the handling of its data—informed by federal, state, industry, and international regulations as well as internal business rules. In larger enterprises, a data governance committee sets those policies and specifies how they should be followed in a living document that evolves as regulations and procedures change. The natural language capabilities of generative AI can pop out first drafts of that documentation and make subsequent changes much less onerous. By analyzing data usage patterns, regulatory requirements, and internal workflows, AI can help organizations define and enforce data retention policies and automatically identify data that has reached the end of its useful life. ... AI-powered disaster recovery systems can help organizations develop sound recovery strategies by predicting potential failure scenarios and establishing preventive measures to minimize downtime and data loss. Backup systems infused with AI can ensure the integrity of backups and, when disaster strikes, automatically initiate recovery procedures to restore lost or corrupted data.

The impact of compliance technology on small FinTech firms

However, smaller firms often struggle to adapt quickly due to resource constraints, leading to a more reactive compliance management approach. For smaller firms, running on thin resources could mean higher risks. Many operate with minimal compliance staff or assign compliance duties to employees who juggle multiple roles. This can stretch employees too thin, making it tough to keep up with regulatory changes or manage conflicts of interest that might jeopardize the firm. The use of basic tools like spreadsheets and emails increases the risk of missing important updates or failing to adequately address identified risks due to the lack of clear ownership and effective action plans. Furthermore, regulatory penalties can disproportionately impact smaller firms that lack the financial buffer to absorb significant fines. The ever-evolving regulatory landscape poses an ongoing risk to compliance. Smaller firms must navigate a vast array of compliance policies and procedures. Even those with dedicated compliance or legal experts face the challenge of sifting through extensive documentation to identify relevant changes. 

Revolutionising firms’ security with SASE

For Indian companies, today is an opportune time to have a well-thought long-term SASE strategy and identify short-term consolidation tactics to achieve your desired SASE model. There may be a change required in the firm’s IT culture to adopt integrated networking and security teams, which involves a shift from silo ways of working to shared control. Because no two SASE journeys are the same, therefore, it is up to enterprises to prepare differently and plan for different or customized outcomes. And the first step to doing so is selecting a trusted partner to help in the assessment of your network and security roadmaps against SASE as the reference architecture. Just as significant as the delivery and operational components of SASE, is having a partner who understands innovation and agility, with an eye towards the future. The partner should be able to assist in technology evaluation, establish proof of value, and recommend adaptations to integrate SASE components – all of which go toward laying the foundation for the firm’s security and network roadmaps. Firms should know that when it comes to executing SASE, it isn’t just done and dusted but a multi-disciplinary project with moving parts.

The Next Phase of the Fintech Revolution: Inside the Disruption and the Challenges Facing Banking

The thing that’s causing the most waves right now, frankly, is the regulators. We had evolved to this architecture where you had fintechs doing their thing. You had sponsor banks of various types underneath who were actually bearing the regulatory burden and holding the cash — things that only banks can really do. And then you had these middleware companies that are generically kind of known as banking as a service companies (BaaS). That architecture, which underpins much of the payments, lending and banking innovation that we’ve seen, has now been called into question by regulators and is being litigated ... The most important theme right now is the implications of generative AI for financial services and, not least of all, retail banking. What’s being funded right now are basically vendors. So, this new crop of technology companies is springing up to serve banks and financial institutions more generally and help them with digital transformation as it relates to generative AI. So, you could think of chatbot companies as being probably the most advanced wedge on this and customer service generally as a way to introduce generative AI, lower OpEx and create more customer delight.

Data Governance and AI Governance: Where Do They Intersect?

AI governance needs to cover the contents of the data fed to and retrieved through AI, in addition to considering the level of AI intelligence. Doing so addresses issues like biases, privacy, use of intellectual property, and misuse of the technology. Consequently, AIG needs to guide what subject matter can be processed through AI, when, and in what contexts. ... AIG and DG share common responsibilities in guiding data as a product that AI systems create and consume, despite their differences. Both governance programs evaluate data integration, quality, security, privacy, and accessibility. ... The data governance team audits the product data pipeline and finds inconsistent data standards and missing attributes feeding into the AI model. However, the AI governance team also identifies opportunities to enhance the recommendation algorithm’s logic for weighting customer preferences. The retailer could resolve the data quality issues through DG while AIG improved the AI model’s mechanics by taking a collaborative approach with both data governance and AI governance perspectives. 

Enhancing security through collaboration with the open-source community

Without funding, it is difficult for open-source projects to get official certifications. So, companies in regulated sectors that need those certifications often can’t use open-source solutions. For the rest, open-source really has “eaten the world.” Most modern tech companies wouldn’t exist without open-source tools, or would have drastically different offerings. ... Too many just download the open-source project and run away. One way for corporate entities to get involved is by contributing bug fixes and small features. This can be done through anonymous email accounts if it’s necessary to keep the company’s involvement private. Companies should also use the results of their security analysis to help improve the original project. There is some self-interest involved here. Why should a company use its resources to maintain proprietary patches for an open-source project when it can instead send those patches back and have the community maintain them for free? Google has been doing a good job of this with their OSS-FUZZ project. It has found many bugs and helped a large number of the open-source projects using it.

Quote for the day:

"Develop success from failures. Discouragement and failure are two of the surest stepping stones to success." -- Dale Carnegie

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