By leveraging machine learning algorithms to analyze data on energy output and consumption, the technology can provide new designs that are both more effective and cost-optimal.
Say Aye to Gen AI: Greeted with skepticism and awe in equal measure when it was first unveiled to the world, Generative Artificial Intelligence (AI) has since become an integral part of the entire business landscape, with industries ranging from healthcare to hospitality embracing this futuristic technology and allocating considerable resources to explore more areas for its application to turn their businesses more efficient and profitable. As 2023 draws to a close and the world looks to turn a new page, generative AI and its ever-widening scope of applications are key priorities for all sectors.
How our GenNext will blend in with Gen AI
Gen AI can improve the efficiency of renewable energy sources. Solar and wind power are crucial in mitigating greenhouse gas emissions and addressing the effects of global warming. However, the high installation and maintenance costs of these alternative energy systems remain a challenge. Now it is time to skip to the good part, where generative AI can help. By automating the design process, generative AI can improve the efficiency of renewable energy systems. By leveraging machine learning algorithms to analyze data on energy output and consumption, the technology can provide new designs that are both more effective and cost-optimal.
Time-efficient and learning caddie: Generative AI is a valuable asset to the e-learning industry, serving as an efficient complement to human personnel. Its Natural Language Processing (NLP) capabilities, word-image association, and context-specific answers to focused queries are expected to revolutionize digital learning programs. The conventional processes employed for generating learning materials are often time-consuming and labor-intensive, which is a significant setback in professional settings where workers need to familiarize themselves with new technologies and tools under time constraints. The integration of generative AI in the production of study material can, therefore, save the many hours typically lost in the process. The retail industry has already benefited from its NLP abilities, where generative AI has been utilized for generating product descriptions, among other tasks. With time, more industries are likely to adopt generative AI as a training tool for producing study materials and briefing documents.
Software testing with applied creativity: Among all industries, the software sector is poised to experience the most dramatic effects of generative AI in 2024. Specifically, generative AI will enhance testing efficiency while reducing both time and resource consumption. While software testing has evolved over the years, from manual testing to scripted automation and data-driven AI testing, these approaches have limitations. Generative AI, however, holds the promise of revolutionizing the software testing process entirely. Its ability to autonomously identify weaknesses and create unexpected scenarios for a more comprehensive assessment of a software’s abilities is a game-changer. The capability of generative AI to creatively test software distinguishes it as a significant asset in the software industry.
On Native or Hybrid Cloud Nine? The use of cloud technology, despite its obvious advantages from a computing standpoint, often extracts a huge cost, environmentally. It could be the vast acreage required for server farms or the exhaustive volume of energy required to keep them running. Cloud-based technologies entail the expenditure of multiple resources, not to mention the amount of heat generated by the IT infrastructure. However, leading cloud providers, cognizant of the ecological cost, are collaborating with each other to reduce carbon emissions at server farms. Just as they have worked together to secure data from cyberattacks, they are now joining hands for a greener future. Cloud providers do, however, point out that sustainable solutions in the IT sector cannot be viable without them.
At the level of the software suite, cloud providers will, throughout 2024, probably push for accelerated adoption of low-code and no-code platforms that will, in turn, enable the IT sector to embrace ‘greener’ applications. Increased adoption of low-code and no-code platforms will make the use of networked clouds a more feasible solution. Furthermore, the use of sustainable architectures for the development of networked clouds is slated to increase the efficiency quotient, thereby reducing the amount of energy consumed at server farms. Yet another innovative solution that cloud providers can adopt to decrease their carbon footprint is by offering clients a vendor-agnostic platform. By ensuring that there is no ‘technology lock-in’, cloud providers will be able to assess performance using dynamic metrics, besides developing a system that can be modified as and when ‘greener’ options emerge in the future.
Technology enabling a grassroots revolution: According to a recent report by Deloitte, ‘Smart’ agriculture, whose value is currently estimated at around USD 11.45 billion, is expected to reach USD 30 billion by 2027. In the immediate future—say, 2024—technological advancements will continue to drive agricultural productivity. While the use of Internet of Things (IoT) devices, smart sensors, and edge computing solutions on farms is now par for the course, digital transformation tools can enable the creation of a more congenial ecosystem for farmers and agriculture-related businesses. For instance, deployment of the ‘Digital Real-Time Analyst’ can help all stakeholders in the agriculture system seek and receive timely assistance. In the event of contact or customer service centers being shortstaffed, digital real-time analysts can offer invaluable guidance to those at the grassroots.
Digital Twinning in Agriculture: One particular transformative technology that can revolutionize agriculture is the ‘Digital Twin’. Given the complete lack of room for error in agricultural processes, where mistakes such as use of the wrong fertilizer or lack of compatibility between choice of crop and soil can leave farmers reeling under losses, the digital twin technology can enable them to foresee and effectively preempt many such problems. Although the use of digital twin technology on farms is still in its nascent stages, the scope for its application in agriculture is vast. To begin with, digital twin technologies can offer the farmers a ‘dry run’, albeit in a virtual setting, of their year-long cycle to assess the viability of their harvest. Digital twins, coupled with cloud and data analytics tools, can help the farmer envision the future and prepare for many eventualities. Given that digital twins can be integrated with ‘Big Data’ tools, they can offer farmers information on long-term meteorological patterns, enabling those working on the fields to make arrangements beforehand to guard their harvest against damage.
Technology and Therapeutics: 2024 will see technology play a wider role in medicine, much broader than video visits and e-consults. Digital therapeutics will assume center stage as evidence-based therapeutic interventions driven by software to prevent, manage, or treat a medical disorder or disease.
Digital Therapeutics (DTx) has the potential to enhance the quality of life and clinical outcomes for patients by empowering them to self-manage their symptoms. DTx leverages digital technologies such as mobile devices, apps, sensors, virtual reality, the Internet of Things, and other tools to encourage behavioral modifications in patients.
Looking ahead, cloud-powered transformative technologies already in use, such as the digital twin and edge computing devices, are likely to find wider application. On the other hand, across the business landscape, demand for data-driven digital solutions is likely to increase, which, in turn, is likely to fuel innovation in technology companies. However, with concerns mounting over threats to data sovereignty, both the private and public sectors are equally likely to invest in technology that can better secure the confidentiality of sensitive information. To that end, innovations that can enable increased localization of data storage without driving both cost and energy requirements can be expected to alter the cybersecurity landscape in the years to come.
Also read: Organizations should be driven based on people and processes instead of emphasizing technology
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