Top 5 Artificial Intelligence Hardware Innovations

Artificial Intelligence is today the only eminent and prospering technology. AI technology and Artificial Intelligence hardware are improving and transforming in the areas of software and hardware.

The semiconductor industry and other electronics industry are very much gaining momentum with these AI-enabled hardware systems.

Furthermore, Trends suggest that Artificial Intelligence hardware will account for 40-50% of the total value in the AI establishments.

Today’s components and machinery use this Artificial Intelligence Progidy. Predominantly in Central Processing Units and Graphics Processing Units too in order to give a much advanced and more computed method of working.

Follow through these most valuable innovations in AI hardware:

Artificial Intelligence in Quantum Hardware

Quantum Computations are fast and efficient providing good yield. These operators are capable of computing resources and data beyond human capability. For example, IBM Q is the world’s first-ever quantum computer based on circuits. Similarly, Google has processors like Foxtail, Bristlecone and Sycamore for everyday needs.

Integrated Circuits that are Application Specific 

Ever wondered if circuit chips could do wonders. These type of ICs are purpose and motive oriented. Examples such as chip designed for Voice Analysis and Recording is typical integrated circuits which are application-specific.

Programmable Gate Array 

These are also integrated circuits for design configuration as well as customer needs in the manufacturing process. It works as a field-oriented mechanism and is identical to semiconductor devices based around a matrix of configurable logic books

Neuromorphic hardware

Neuromorphic chips are very efficient in problem solving and diagnosis with evaluating potential solutions. This hardware identifies the shortest route by performing approximate image searches and problem optimization in the real world.

Artificial Intelligence in Edge Computing Chips

Consider the example of an autonomous vehicle, the process of analysing should occur with no latency and interference in areas of braking and acceleration. Edge Computing chips play a major role in this achievement. Moreover, Edge computing is the favoured choice for applications, where privacy issues and data bandwidth are paramount like AI-enabled CT-scan diagnostics function.

By Mannu Mathew | Sub Editor | ELE Times