November 06, 2024

Enter the ‘Whisperverse’: How AI voice agents will guide us through our days

Within the next few years, an AI-powered voice will burrow into your ears and take up residence inside your head. It will do this by whispering guidance to you throughout your day, reminding you to pick up your dry cleaning as you walk down the street, helping you find your parked car in a stadium lot and prompting you with the name of a coworker you pass in the hall. It may even coach you as you hold conversations with friends and coworkers, or when out on dates, give you interesting things to say that make you seem smarter, funnier and more charming than you really are. ... Most of these devices will be deployed as AI-powered glasses because that form-factor gives the best vantage point for cameras to monitor our field of view, although camera-enabled earbuds will be available too. The other benefit of glasses is that they can be enhanced to display visual content, enabling the AI to provide silent assistance as text, images, and realistic immersive elements that are integrated spatially into our world. Also, sensored glasses and earbuds will allow us to respond silently to our AI assistants with simple head nod gestures of agreement or rejection, as we naturally do with other people. ... On the other hand, deploying intelligent systems that whisper in your ears as you go about your life could easily be abused as a dangerous form of targeted influence.

How to Optimize Last-Mile Delivery in the Age of AI

Technology is at the heart of all advancements in last-mile delivery. For instance, a typical map application gives the longitude and latitude of a building — its location — and a central access point. That isn't enough data when it comes to deliveries. In addition to how much time it takes to drive or walk from point A to point B, it's also essential for a driver to understand what to do at point B. At an apartment complex, for example, they need to know what units are in each building and on which level, whether to use a front, back, or side entrance, how to navigate restricted or gated areas, and how to access parking and loading docks or package lockers. Before GenAI, third-party vendors usually acquired this data, sold it to companies, and applied it to map applications and routing algorithms to provide delivery estimates and instructions. Now, companies can use GenAI in-house to optimize routes and create solutions to delivery obstacles. Suppose the data surrounding an apartment complex is ambiguous or unclear. For instance, there may be conflicting delivery instructions — one transporter used a drop-off area, and another used a front door. Or perhaps one customer was satisfied with their delivery, but another parcel delivered to the same location was damaged or stolen. 

Cloud providers make bank with genAI while projects fail

Poor data quality is a central factor contributing to project failures. As companies venture into more complex AI applications, the demand for tailored, high-quality data sets has exposed deficiencies in existing enterprise data. Although most enterprises understood that their data could have been better, they haven’t known how bad. For years, enterprises have been kicking the data can down the road, unwilling to fix it, while technical debt gathered. AI requires excellent, accurate data that many enterprises don’t have—at least, not without putting in a great deal of work. This is why many enterprises are giving up on generative AI. The data problems are too expensive to fix, and many CIOs who know what’s good for their careers don’t want to take it on. The intricacies in labeling, cleaning, and updating data to maintain its relevance for training models have become increasingly challenging, underscoring another layer of complexity that organizations must navigate. ... The disparity between the potential and practicality of generative AI projects is leading to cautious optimism and reevaluations of AI strategies. This pushes organizations to carefully assess the foundational elements necessary for AI success, including robust data governance and strategic planning—all things that enterprises are considering too expensive and too risky to deploy just to make AI work.

Why cybersecurity needs a better model for handling OSS vulnerabilities

Identifying vulnerabilities and navigating vulnerability databases is of course only part of the dependency problem; the real work lies in remediating identified vulnerabilities impacting systems and software. Aside from general bandwidth challenges and competing priorities among development teams, vulnerability management also suffers from challenges around remediation, such as the real potential that implementing changes and updates can potentially impact functionality or cause business disruptions. ... Reachability analysis “offers a significant reduction in remediation costs because it lowers the number of remediation activities by an average of 90.5% (with a range of approximately 76–94%), making it by far the most valuable single noise-reduction strategy available,” according to the Endor report. While the security industry can beat the secure-by-design drum until they’re blue in the face and try to shame organizations into sufficiently prioritizing security, the reality is that our best bet is having organizations focus on risks that actually matter. ... In a world of competing interests, with organizations rightfully focused on business priorities such as speed to market, feature velocity, revenue and more, having developers quit wasting time and focus on the 2% of vulnerabilities that truly present risks to their organizations would be monumental.

The new calling of CIOs: Be the moral arbiter of change

Unfortunately, establishing a strategy for democratizing innovation through gen AI is far from straightforward. Many factors, including governance, security, ethics, and funding, are important, and it’s hard to establish ground rules. ... What’s clear is tech-led innovation is no longer the sole preserve of the IT department. Fifteen years ago, IT was often a solution searching for a problem. CIOs bought technology systems, and the rest of the business was expected to put them to good use. Today, CIOs and their teams speak with their peers about their key challenges and suggest potential solutions. But gen AI, like cloud computing before it, has also made it much easier for users to source digital solutions independently of the IT team. That high level of democratization doesn’t come without risks, and that’s where CIOs, as the guardians of enterprise technology, play a crucial role. IT leaders understand the pain points around governance, implementation, and security. Their awareness means responsibility for AI, and other emerging technologies have become part of a digital leader’s ever-widening role, says Rahul Todkar, head of data and AI at travel specialist Tripadvisor.

5 Strategies For Becoming A Purpose-Driven Leader

Purpose-driven leaders are fueled by more than sheer ambition; they are driven by a commitment to make a meaningful impact. They inspire those around them to pursue a shared purpose each day. This approach is especially powerful in today’s workforce, where 70% of employees say their sense of purpose is closely tied to their work, according to a recent report by McKinsey. Becoming a purpose-driven leader requires clarity, strategic foresight, and a commitment to values that go beyond the bottom line. ... Aligning your values with your leadership style and organizational goals is essential for authentic leadership. “Once you have a firm grasp of your personal values, you can align them with your leadership style and organizational goals. This alignment is crucial for maintaining authenticity and ensuring that your decisions reflect your deeper sense of purpose,” Blackburn explains. ... Purpose-driven leaders embody the values and behaviors they wish to see reflected in their teams. Whether through ethical decision-making, transparency, or resilience in the face of challenges, purpose-driven leaders set the tone for how others in the organization should act. By aligning words with actions, leaders build credibility and trust, which are the foundations of sustainable success.

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