How APAC enterprises can scale up their AI initiatives

whitePaper | January 8, 2020

AI in manufacturing is a game-changer. It has the potential to transform performance across the breadth and depth of manufacturing operations. However, the massive potential of this new Industrial 4.0 era will only be realized if manufacturers really focus their efforts on where AI can add most value and then drive the solutions to scale.

whitePaper | February 11, 2020

Deepwave Digital has leveraged the Artificial Intelligence Radio Transceiver (AIR-T) to create the first deep learning sensor for a 5G network. This network, the Citizens Broadband Radio Service (CBRS), will be the first spectrum sharing service provided by the telecommunications industry that leverages real time RF sensing. Critical to the operation of CBRS is the ability to determine if priority users are active on specific frequency channels. When no priority users are present, the spectrum may be reallocated for commercial networks to provide new enterprise services or additional bandwidth to existing services.

whitePaper | August 18, 2021

Among retail marketers, a reliance on traditional business intelligence tools has left the intuitive decision-making in the hands of the marketing team. Download this guide to learn how to solve this AI dilemma.

whitePaper | May 15, 2023

The future of AI is hybrid. As generative AI adoption grows at record-setting speeds1 and drives higher demand for compute,2 AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential – just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices. A hybrid AI architecture distributes and coordinates AI workloads among cloud and edge devices, rather than processing in the cloud alone. The cloud and edge devices, such as smartphones, vehicles, PCs, and IoT devices, work together to deliver more powerful, efficient, and highly optimized AI.

whitePaper | October 11, 2021

AI forms the bedrock to help organizations unlock business value from the deluge of unstructured information. Improving operational efficiency by extracting structured data from unstructured documents enables organizations with faster and contextrich decision-making to adapt and thrive in the new normal.

whitePaper | August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.