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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In the ever-evolving landscape of artificial intelligence (AI) and machine learning (ML), one of the most intriguing advancements is the emergence of General AI (Gen AI). To grasp its significance, it's essential to first distinguish between these interconnected but distinct technologies. AI, ML, and Deep Learning: The Building Blocks Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Machine Learning, a subset of AI, empowers machines to learn from data and improve over time without explicit programming. Deep Learning, a specialized subset of ML, involves neural networks with many layers (hence "deep"), capable of learning intricate patterns from vast amounts of data. Enter General AI (Gen AI): Unraveling the Next Frontier Unlike traditional AI systems that excel in specific tasks (narrow AI), General AI aims to replicate human cognitive abilities across various domains. I...
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