The following forecast looks at how generative AI will create incremental value for companies in each different enterprise vertical. ABI Research expects each generative AI vertical market to adopt the technology at different rates depending on the business use cases that will create the most value.
Whether it’s new recreational entertainment or a novel healthcare monitoring application, consumer technology is always evolving. Older tech is phased out and replaced with the latest and greatest offerings brought about by various companies’ exhaustive product developments. To help manufacturers, content providers, and other vendors pinpoint the current state of consumer markets, here’s a thorough rundown of 8 consumer technology trends in 2023.
The most efficient manufacturers worldwide generate profits and provide value for customers while using minimal resources, including energy, scarce minerals and materials, and freshwater. With electricity and commodity costs at record highs, there are many reasons why companies are pursuing long-term business strategies focused on resource efficiencies and sustainability. Global regulations and stakeholders, including investors, employees, and customers, are also demanding that businesses respond to climate change. According to the World Economic Forum (WEF), roughly 40% of global energy consumption and more than 30% of global Greenhouse Gas (GHG) emissions come from the industrial sector processes. Unsurprisingly, manufacturers are looking for cost-effective ways to reduce their carbon footprint.
In the technology space, it’s vital that your organization stay on top of prevailing trends in your respective industry. This extends to keeping tabs on the competition or, if you’re seeking a solution provider, weighing your options. That’s why ABI Research released its 40 Technology Companies To Watch In 2023 whitepaper to better understand which tech firms are winning in terms of innovation and implementation of their technology products/software.
By 2027, ABI Research forecasts the installed base of Artificial Intelligence (AI)-enabled cameras to be 976.4 million, signaling a growing need for machine vision technologies. Today’s companies offering machine vision solutions are vital to the betterment of a number of applications, encompassing manufacturing, smart cities, building development, public safety, logistics, and transportation. An abundance of modern Machine Learning (ML)-based software products are embedded with edge ML capabilities that vastly improve a wide range of use cases, notably image-based inspection. This means a robotic system with an installed camera stacks pallets correctly or a flaw on a product's surface can be detected. To give you a better idea of how these systems work and who is providing them, this post highlights eight machine vision software companies that are helping enterprise customers work more efficiently.
Machine Learning (ML) is increasingly being integrated into edge computing solutions. ML at the edge improves the user experience via latency reduction, near-real-time data analysis, privacy, and security. Vendors are stepping up to the plate to provide services and platforms that streamline processes and reduce the time to market. In this post, you'll read about five examples of edge ML to better conceptualize this helpful combination.
According to ABI Research forecasts, the total installed base of devices with Artificial Intelligence will grow from 2.7 billion in 2019 to 4.5 billion in 2024. Billions of petabytes of data flow through AI devices every day. However, right now, most of these AI devices are working independently of one another. Yet, as the volume of data flowing through these devices increases in the coming years, technology companies and implementers will take advantage of multimodal learning – and it is fast becoming one of the most exciting and potentially transformative fields of AI.
This is part 2 of a series of blogs covering the NVIDIA GTC '22 event. You can read part 1 here and part 3 here.
This is part 3 of a series of blogs covering the NVIDIA GTC '22 event. You can read part 1 here and part 2 here.