Artificial Intelligence (AI) today is a form of advanced analytics that relies on machine learning (ML), optimization and deep learning. Artificial Intelligence of Things (AIoT) is less of a new industry than it is the combination of pre-existing industries. AI and ML automotive solutions add more intelligence to the “sensing”, “thinking” and “acting” processes of automated cars to help solve global mobility challenges toward zero road fatalities, zero emissions and zero time wasted.
Applications of AIoT
By using AI in coordination with devices, a new artificial intelligence of things (AIoT) can ensure data-driven decision-making that improves operations throughout enterprises. In the developing AIoT, sensors, built-in smart cameras (AI cameras) play a vital role. The sheer variety of smart networking devices means large amounts of data are generated. Naturally, the demand for smart storage devices has increased dramatically. The sheer variety of smart networking devices means large amounts of data generation. Thus, demand for smart storage devices has increased tremendously.
Data is an asset. Beyond storing data, companies need to rethink how to integrate and analyze the data to get the maximum possible return on the available data and investment in IoT. Apacer offers a full range of industrial 3D TLC NAND products with two key technologies: Over-provisioning (OP) and DataRAIDTM. OP solves problems related to intensive read/write cycles and lengthens the operational lifetime of solid-state drive (SSD) devices. In order to assist customers who are transitioning to industrial automation and intelligent manufacturing, first, it is needed to determine the most ideal SSD for a particular application. The second step is to monitor SSD usage remotely.
Artificial Intelligence Development Environment provides the essential building blocks that developers require to deploy machine learning in their devices. We can already talk to virtual assistants like Siri or Alexa to search for a movie or order a new scarf with delivery at door.
A different view of AIoT
As AI becomes embedded in everything, there is a natural fear, especially exacerbated by the media, that the combination of AI with IoT is going to disrupt workforces and put people out of jobs. As for AIoT to work judiciously, everything needs to be properly programmed. Outliers rarely get programmed into the system. It may so happen sometimes that, if you try to have a conference call with someone overseas, and the person’s AI assistant fail to understand that you may not be interested in doing that call between 1:00 a.m. and 4:00 a.m. your time. Instead of giving midnight or 5:00 a.m. as an option, it may just keep pushing the same times farther out on the calendar.
Opportunities in artificial intelligence of things will continue to expand. It is a proven, flourishing sector. Enhancing competitive advantages and profitability will remain a concern though. AIoT has already pivoted from centralized cloud storage to an edge computing architecture. The future when people will come home after work and ask their TV to turn on and the washing machine to wash clothes in the economy mode doesn’t seem so distant.
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