Global tech market advisory firm ABI Research’s “2021 Trend Report” forecasts that edge Artificial Intelligence (AI) and edge AI servers will be instrumental in the rise of distributed intelligence in 2021. This also what the research firm describes as “steep and steady rise of these gateways and servers.”
Distributed intelligence is an architecture that breaks computation workloads hosted in a centralized system into a combination of a central and end node.
According to ABI Research, they see an increase in annual shipments of edge AI gateways and AI servers to grow from 8.55 million and 69,000 in 2020 to over 10 million and 105,000 in 2021, respectively. This will also pave the way for distributed intelligence to go mainstream over the next decade. The market advisory firm sees annual shipments of edge AI gateways to reach 59.5 million and AI server shipments to hit 1.5 million in 2030.
In its new whitepaper, “68 Technology Trends That Will Shape 2021,” ABI Research’s analysts identify 37 trends that will shape the technology market and 31 others that, although attracting huge amounts of speculation and commentary, are less likely to move the needle over the next twelve months.
“For success in 2021, especially after a very challenging 2020, one must understand fundamental trends early, and take a view on those trends that are buoyed by hyperbole and those that are sure to be uncomfortable realities. Now is the time to double down on the right technology investment,” says Stuart Carlaw, chief research officer at ABI Research.
“While distributed intelligence has greatly benefited from the design and implementation of various systems, such as cloud computing clusters, warehouse robots, and smart home systems, these systems are often limited by geographical factors, connectivity options, and the processing capabilities in end nodes,” said Lian Jye Su, AI and Machine Learning Principal Analyst at ABI Research. “The emergence of 5G and AI is set to change these. Combining the high throughput, low latency, and massive IoT connectivity of 5G, with on-device inferencing capabilities of AI, 5G-enabled edge AI devices will have the flexibility to centralize all their workloads in the cloud or perform time-, latency-, and security-sensitive workloads at the edge.”
This development will remove data privacy, safety, and security concerns while allowing the overall system to update and optimize itself.
“Expect major webscalers and chipset suppliers to align their products and solutions in 2021 to address demand for more distributed intelligence across both the consumer and the enterprise markets,” Su adds.
Edge AI deployment has been a challenge as there is a diverse range of edge AI chipsets, frameworks, and toolkits. Some players in the market are coming up with a zero- or low-code deployment platform. These platforms support zero-code web user interface-based deployment, cloud-based device monitoring, orchestration and management, alert management, and ML model performance monitoring and retraining.
“Deep learning-based AI remains a black box. Although cloud AI players, such as Google, H2O, and Element AI, have offered development tools and frameworks around explainable AI, AI built based on these solutions is not mature enough for mass commercialization. At the moment, most AI models are not designed for transparency, let alone explainability. Hence, do not expect explainable AI to become mainstream in 2021. Also, do not expect massive migration or switching either, because switching away from non-transparent deep learning models may not be an option for many companies,” Su said.