April 16, 2024

How to Build a Successful AI Strategy for Your Business in 2024

With a solid understanding of AI technology and your organization’s priorities, the next step is to define clear objectives and goals for your AI strategy. Focus on identifying the problems that AI can solve most effectively within your organization. These objectives should be specific, measurable, achievable, relevant, and time-bound (SMART). ...?By setting well-defined objectives, you can create a targeted AI strategy that delivers tangible results and aligns with your overall business priorities. An AI implementation strategy often requires specialized expertise and tools that may not be available in-house. To bridge this gap, identify potential partners and vendors who can provide the necessary support for your AI strategy.Start by researching AI and machine learning companies that have a proven track record of working in your industry. When evaluating potential partners, consider factors such as their technical capabilities, the quality of their tools and platforms, and their ability to scale as your AI needs grow. Look for vendors who offer comprehensive solutions that cover the entire AI lifecycle, from data preparation and model development to deployment and monitoring.

Internet can achieve quantum speed with light saved as sound

When transferring information between two quantum computers over a distance—or among many in a quantum internet—the signal will quickly be drowned out by noise. The amount of noise in a fiber-optic cable increases exponentially the longer the cable is. Eventually, data can no longer be decoded. The classical Internet and other major computer networks solve this noise problem by amplifying signals in small stations along transmission routes. But for quantum computers to apply an analogous method, they must first translate the data into ordinary binary number systems, such as those used by an ordinary computer. This won't do. Doing so would slow the network and make it vulnerable to cyberattacks, as the odds of classical data protection being effective in a quantum computer future are very bad. "Instead, we hope that the quantum drum will be able to assume this task. It has shown great promise as it is incredibly well-suited for receiving and resending signals from a quantum computer. So, the goal is to extend the connection between quantum computers through stations where quantum drums receive and retransmit signals, and in so doing, avoid noise while keeping data in a quantum state," says Kristensen.

Better application networking and security with CAKES

A major challenge in enterprises today is keeping up with the networking needs of modern architectures while also keeping existing technology investments running smoothly. Large organizations have multiple IT teams responsible for these needs, but at times, the information sharing and communication between these teams is less than ideal. Those responsible for connectivity, security, and compliance typically live across networking operations, information security, platform/cloud infrastructure, and/or API management. These teams often make decisions in silos, which causes duplication and integration friction with other parts of the organization. Oftentimes, “integration” between these teams is through ticketing systems. ... Technology alone won’t solve some of the organizational challenges discussed above. More recently, the practices that have formed around platform engineering appear to give us a path forward. Organizations that invest in platform engineering teams to automate and abstract away the complexity around networking, security, and compliance enable their application teams to go faster.

AI set to enhance cybersecurity roles, not replace them

Ready or not, though, AI is coming. That being the case, I’d caution companies, regardless of where they are on their AI journey, to understand that they will encounter challenges, whether from integrating this technology into current processes or ensuring that staff are properly trained in using this revolutionary technology, and that’s to be expected. As a cloud security community, we will all be learning together how we can best use this technology to further cybersecurity. ... First, companies need to treat AI with the same consideration as they would a person in a given position, emphasizing best practices. They will also need to determine the AI’s function — if it merely supplies supporting data in customer chats, then the risk is minimal. But if it integrates and performs operations with access to internal and customer data, it’s imperative that they prioritize strict access control and separate roles. ... We’ve been talking about a skills gap in the security industry for years now and AI will deepen that in the immediate future. We’re at the beginning stages of learning, and understandably, training hasn’t caught up yet.

Why employee recognition doesn't work: The dark side of boosting team morale

Despite the importance of appreciation, many workplaces prioritise performance-based recognition, inadvertently overlooking the profound impact of genuine appreciation. This preference for recognition over appreciation can lead to detrimental outcomes, including conditionality and scarcity. Conditionality in recognition arises from its link to past achievements and performance outcomes. Employees often feel pressured to outperform their peers and surpass their past accomplishments to receive recognition, fostering a hypercompetitive work environment that undermines collaboration and teamwork. Furthermore, the scarcity of recognition exacerbates this issue, as tangible rewards such as bonuses or promotions are limited. In this competitive landscape, employees may feel undervalued, leading to disengagement and disillusionment. To foster an inclusive and supportive workplace culture, organisations must recognise the intrinsic value of appreciation alongside performance-based recognition. Embracing appreciation cultivates a culture of gratitude, empathy, and mutual respect, strengthening interpersonal connections and boosting employee morale.

Improving decision-making in LLMs: Two contemporary approaches

Training LLMs in context-appropriate decision-making demands a delicate touch. Currently, two sophisticated approaches posited by contemporary academic machine learning research suggest alternate ways of enhancing the decision-making process of LLMs to parallel those of humans. The first, AutoGPT, uses a self-reflexive mechanism to plan and validate the output; the second, Tree of Thoughts (ToT), encourages effective decision-making by disrupting traditional, sequential reasoning. AutoGPT represents a cutting-edge approach in AI development, designed to autonomously create, assess and enhance its models to achieve specific objectives. Academics have since improved the AutoGPT system by incorporating an “additional opinions” strategy involving the integration of expert models. This presents a novel integration framework that harnesses expert models, such as analyses from different financial models, and presents it to the LLM during the decision-making process. In a nutshell, the strategy revolves around increasing the model’s information base using relevant information.?

Read more here ...