AI chipsets market is likely to show positive growth attributed to the amalgamation of high processing hardware with various AI technologies such as digital personal assistants, deep learning, robotics, natural language processing (NLP), context-aware processing and querying to develop the AI-featured products. The robotics industry is rapidly increasing and is anticipated to exhibit considerably to the artificial intelligence (AI) chipsets industry during the forecast period. The robots have been largely adopted in various sectors such as healthcare, retail, and industrial applications. As per the International Federation of Robotics, the annual sales of robots from 2013 to 2017 grew by 114% and in 2018 the sales value of $16.5 billion, an increase of 6% compared to the previous year. Due to this, there is a substantial growth rate in the market.
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The robotics process automation is anticipated to show a positive growth due to attractive characteristics of AI robots includes low technical barriers, improved accuracy, enhanced productivity, consistency, and reliability. Additionally, robotics process automation technology is applicable to processes that are consistent, routine and prone to human error. The robots are capable of simplifying daily tasks. For instance, Amazon Alexa uses NLP to offer virtual assistance using voice commands. The robotics is being used for managing tasks such as assessing X-rays, CT scans, and data entries and among others. Many key vendors are developing superior robot brains that would aids machines to operate autonomously by developing, for instance, Rethink Robotics Baxter is a research robot that is trained accordingly. Likely, human-like robots are invented by Hanson robotics that is capable to carry a conversation and recall personal history. Hence, increasing the adoption of AI-based robots will create opportunities for the AI chipset market.
Recent Activity
- In May 2018, Google introduced a new generation for its TPU (Tensor Processing Units) machine learning hardware and it is the third version of its AI chips. The TPU would enable Google enhanced applications that use AI to do things such as voice recognition, pick up underlying emotions in written text and spot objects in photos and videos. The new TPU pod is eight times more powerful with up to 100 petaflops in performance.
- In December 2017, IBM Corp. and Nvidia come into a partnership to produce new chips for AI and machine learning. IBM’s new Power9 lines up of chips for servers are faster connections that enable the processor to work closely with graphic processing chips from Nvidia.
Global Artificial Intelligence Chipsets Market- Segmentation
By Technology
- Machine Learning
- Natural Language processing
- Context-aware Computing
- Computer Vision
By End-User
- Consumer Electronics
- Retail
- IT & Telecom
- Healthcare
- Automotive
- Agriculture
- Other
(This release has been published on Global Market Post. Global Market Post is not responsible for any content included in this release.)
