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Artificial
Intelligence of Things (AIoT) is the use of artificial intelligence (AI)
technologies to enhance an Internet of Things (IoT) infrastructure. An
important goal of AIoT is to transform operational data into information that
can be used to make decisions in real time.
AIoT technologies
have the ability to capture streaming data, determine valuable attributes and
immediately make a decision without requiring human intervention. Currently,
AIoT can support freestanding hardware components such as Google Home, as
well as embedded hardware components such as AI chipsets. Application
programming interfaces (APIs) can be used to extend interoperability between
components at the device level, software level or platform level.
While the concept
of AIoT is still relatively new, real possibilities exist for AI to improve
industry verticals for industrial, consumer, business-to-business (B2B) and
service sectors. As applications for AI technologies grow, the unstructured
data generated from IoT-supported systems is expected to increase in value
correspondingly and the ability to use streaming data to make data-driven
decisions will add a new dimension to service logic. In some cases, experts
predict, the data itself will become the service because of its ability to
provide actionable information.
In addition to
becoming a viable solution for solving existing operational problems, AIoT is
also expected to reduce supply chain risk, which includes expenses associated
with human capital management (HCM). AIoT is also expected to create new
delivery models such as IoT Data as a Service (IoTDaaS).
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A graphics processing unit (GPU) is a computer chip that performs rapid mathematical calculations, primarily for the purpose of rendering images. A GPU may be found integrated with a central processing unit (CPU) on the same circuit, on a graphics card or in the motherboard of a personal computer or server. In the early days of computing, the CPU performed these calculations. As more graphics-intensive applications such as AutoCAD were developed; however, their demands put strain on the CPU and degraded performance. GPUs came about as a way to offload those tasks from CPUs, freeing up their processing power. NVIDIA, AMD, Intel and ARM are some of the major players in the GPU market. GPU vs. CPU A graphics processing unit is able to render images more quickly than a central processing unit because of its parallel processing architecture, which allows it to perform multiple calculations at the same time. A single CPU does not have this capability, although multi...
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