November 04, 2024
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | GRC Consulting | Independent Director | Enterprise & Solution Architecture | Former Sr. VP & CTO of MF Utilities | BU Soft Tech | itTrident
According to AFCOM's 2024 State of Data Center Report, AI is already having a major influence on data center design and infrastructure. Global hyperscalers and data center service providers are increasing their capacity to support AI workloads. This has a direct impact on power and cooling requirements. In terms of power, the average rack density is expected to rise from 8.5 kW per rack in 2023 to 12 kW per rack by the end of 2024, with 55% of respondents expecting higher rack density in the next 12 to 36 months. As GPUs are fitted into these racks, servers will generate more heat, increasing both power and cooling requirements. The optimal temperature for operating a data center hall is between 21 and 24°C (69.8 - 75.2°F), which means that any increase in rack density must be accompanied by improvements in cooling capabilities. ... The efficiency of a data center is measured by a metric called power usage efficiency, PUE, which is the ratio of the total amount of power used by a data center to the power used by its computing equipment. To be more efficient, data center providers aim to reduce their PUE rating and bring it closer to 1. A way to achieve that is to reduce the power consumed by the cooling units through advanced cooling technologies.
Boards and C-suites that have not yet had discussions about the potential risks of GenAI need to start now. “Employees can use and abuse generative AI even when it is not available to them as an official company tool. It can be really tempting for a junior employee to rely on ChatGPT to help them draft formal-sounding emails, generate creative art for a PowerPoint presentation and the like. Similarly, some employees might find it too tempting to use their phone to query a chatbot regarding questions that would otherwise require intense research,” says Banner Witcoff’s Sigmon. “Since such uses don’t necessarily make themselves obvious, you can’t really figure out if, for example, an employee used generative AI to write an email, much less if they provided confidential information when doing so. This means that companies can be exposed to AI-related risk even when, on an official level, they may not have adopted any AI.” ... “As is the case with the use of technology within any large organization, successful implementation involves a careful and specific evaluation of the tech, the context of use, and its wider implications including intellectual property frameworks, regulatory frameworks, trust, ethics and compliance,” says Raeburn in an email interview.?
We’re seeing AI tools that can smash out complex coding tasks in minutes and take even your best senior devs’ hours. At Cosine, we’ve seen this firsthand with our AI, Genie. Many of the tasks we tested were in the four to six-hour range, and Genie could complete them in four to six minutes. It’s a genuine superhuman thing to be able to solve problems that quickly. But here’s where it gets interesting. This isn’t just about raw output. The real mind-bender is that AI is starting to think like an engineer. It’s not just spitting out code — it’s solving problems. ... Suppose we’re looking slightly more pragmatically at what AI could signal for career progression. In that case, there is a counterargument that junior developers won’t be exposed to the same level of problem-solving or acquire the same skill sets, given the availability of AI. This creates a complete headache for HR. How do you structure career progression when the traditional markers of seniority — years of experience, deep technical knowledge — might not mean as much? I think we’ll see a shift in focus. Companies will probably lean more on whether you fulfilled your sprint objectives and shipped what you wanted on time instead of going deeper. As for the companies themselves? Those who don’t get on board with AI coding tools will get left in the dust.
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Ritika is of view that managing employees’ and organisational expectations requires clear communication from the leadership. “It offers employees a transparent view of the organisation's direction and highlights how their contributions drive Amway's success and growth. Our leadership prioritises transparency, ensuring that employees have a clear understanding of the organisation’s direction and how their individual and collaborative efforts contribute to collective goals. This approach fosters a strong sense of purpose and engagement while aligning with the vision and desired culture of the company.” She further calls for having a robust feedback mechanism that allows employees an opportunity to share their honest feedback on areas that matter the most and the ones that impact them. “We believe in the feedback flywheel, our bi-annual culture and employee engagement survey allow employees an opportunity to share feedback. Each feedback is followed by a cycle of sharing results and action planning.” She further adds that frequent check-in conversations between the upline and team members ensure there is clarity of expectations, our performance management system ensures there are 3 formal check-in conversations that are focused on coaching and development and not ‘judgement’.?
OpenAI launched an experimental framework last month called Swarm. It’s a “lightweight” system for the development of agentic AI swarms, which are networks of autonomous AI agents able to work together to handle complex tasks without human intervention, according to OpenAI. Swarm is not a product. It’s an experimental tool for coordinating or orchestrating networks of AI agents. The framework is open-source under the MIT license, and available on GitHub. ... One way to look at agentic AI swarming technology is that it’s the next powerful phase in the evolution of generative AI (genAI). In fact, Swarm is built on OpenAI’s Chat Completions API, which uses LLMs like GPT-4. The API is designed to facilitate interactive “conversations” with AI models. It allows developers to create chatbots, interactive agents, and other applications that can engage in natural language conversations. Today, developers are creating what you might call one-off AI tools that do one specific task. Agentic AI would enable developers to create a large number of such tools that specialize in different specific tasks, and then enable each tool to dragoon any others into service if the agent decides the task would be better handled by the other kind of tool.
Mentorship and coaching are critical for unlocking the leadership potential of emerging talent. By pairing less experienced employees with seasoned leaders, companies provide invaluable hands-on learning experiences beyond formal training programs. These relationships allow future leaders to observe high-level decision-making in action, receive personalized feedback, and cultivate their leadership instincts in real-world scenarios. ... While technical skills are essential, leadership success depends heavily on soft skills like emotional intelligence, communication, and adaptability. These skills help leaders navigate team dynamics, inspire trust, and handle organizational challenges with confidence. Workshops, problem-solving exercises, and leadership programs are effective for developing these abilities. ... Leadership development can’t happen in a vacuum. One of the most effective ways to accelerate growth is through “stretch assignments,” opportunities that push employees beyond their comfort zones by challenging them with responsibilities that test their leadership abilities. These assignments expose future leaders to high-stakes decision-making, cross-functional collaboration, and strategic thinking, all of which prepare them for the demands of more senior roles.