Various technology experts have shared their predictions for 2024
Encompassing advancements in AI, cybersecurity, and quantum computing. These experts shed light on the progress made in these fields and the potential they hold for the future.
As we approach the end of the year, the business landscape of 2024 is poised for a profound transformation due to a convergence of disruptive forces. The immense potential of Generative AI in terms of innovation and problem-solving will uncover hidden efficiencies. Sustainability, no longer a mere buzzword, will become an essential strategic priority, particularly in the realm of AI model development. Additionally, quantum computing, once considered a product of science fiction, will unveil unimaginable possibilities.
Technology Magazine engages in conversations with industry leaders in the tech sector to uncover the major trends that will dominate the year 2024.
AI is poised to assume a central role, transitioning from mere theory to tangible application.
John Roese, the Global Chief Technology Officer at Dell Technologies, anticipates a transition in the GenAI dialogue from theoretical discussions to practical implementation. This shift will involve a focus on the cost and efficiency of inference and operational aspects, rather than solely on training infrastructure and expenses.
According to Roese, although GenAI has generated numerous innovative ideas on how it can revolutionize businesses and society, there are currently limited real-world, large-scale GenAI initiatives. However, as we progress into 2024, the initial wave of GenAI enterprise projects will mature, shedding light on crucial aspects of GenAI that are still not fully comprehended in the early stages.
The integration of IT and security teams has led to a harmonization of skills and collaboration.
In 2024, with the emergence of new threats, the boundaries between IT and security responsibilities are becoming blurred. Zeki Turedi, CTO Europe at CrowdStrike, foresees an opportunity to strengthen organizational resilience by merging IT and security teams within enterprises.
A robust and dynamic ecosystem will be propelled by hyperscalers.
The utilization of generative AI has often been condemned for its reliance on outdated data to drive crucial outcomes. However, Rodrigo Liang, the CEO of SambaNova Systems, envisions a revolutionary transformation in the data analytics landscape through the collaboration between hyperscalers and AI models. This partnership will enable the synchronization of real-time fine tuning with up-to-date data, leading to substantial advancements in speed, accuracy, and cost-effectiveness.
He suggests that we will witness a continuous shift towards real-time fine-tuning, allowing models to dynamically adjust and comprehend current data. Consequently, this will drive advancements in AI applications across various industries. The combination of advanced chips and hyperscale data capabilities will establish a potent ecosystem, fostering the development of highly extensive Composition of Experts models. These models will be capable of addressing even more complex use cases than what we have encountered thus far in sectors like marketing, advertising, healthcare, climate, banking, and more.
There is a growing emphasis on zero trust models.
In the current hybrid work environment, individuals heavily rely on a multitude of devices, applications, and services, many of which are hosted in the cloud and beyond the direct control of corporate IT. This evolving landscape necessitates the adoption of a zero-trust model.
Looking ahead, Chris Peake, the CISO and SVP of Security at Smartsheet, anticipates that organizations will enhance their existing models by incorporating additional layers of security. For instance, some organizations may implement role-based security, enabling them to assign specific roles to different user types and manage their access accordingly. This approach will not only safeguard sensitive information but also streamline access for authorized individuals. Furthermore, organizations may introduce time-based access controls, allowing them to regulate users’ access to information based on the duration of their involvement in a particular project.
Moreover, the utilization of Generative AI holds immense potential in fortifying data security and providing an extra layer of protection. Given the sheer volume of data flowing through businesses, it is impractical for manual monitoring to suffice. Intelligent systems powered by machine learning can learn to discern what is considered normal and promptly flag any anomalies that deviate from the norm.