Thursday, January 09, 2020

The #AIEye: GBT Technologies (OTCPINK: $GTCH) to Develop LSTM RNN and Intel (Nasdaq: $INTC) Subsidiary Mobileye Secures Agreements with SAIC and Daegu Metropolitan City

The #AIEye: GBT Technologies (OTCPINK: $GTCH) to Develop LSTM RNN and Intel (Nasdaq: $INTC) Subsidiary Mobileye Secures Agreements with SAIC and Daegu Metropolitan City

Global #AI Chipset Market to Reach $38.46 Billion by 2023




Point Roberts WA, Vancouver BC – January 9, 2020  – Investorideas.com (www.investorideas.com), a global investor news source covering Artificial Intelligence (AI) brings you today’s edition of  The AI Eye-  watching stock news, deal tracker and advancements in artificial intelligence.

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Today’s Column- The AI Eye- Watching stock news, deal tracker and advancements in artificial intelligence

Stocks discussed: (OTCPINK:GTCH) (NasdaqGS:INTC)

GBT Technologies Inc. (OTCPINK:GTCH) is developing a new LSTM (Long/Short Term Memory) RNN (Recurrent Neural Network), which “will be based on GBT's upcoming communication IC patent (patent grant expected Q1 2020) with a goal of dramatically expanding its AI-controlled microchip technology platform.” Danny Rittman, GBT's CTO, explained:

"Our goal is for this new RNN to enable high-capacity, high-speed AI based analytics and data processing, which is crucial for advanced computing for use in autonomous vehicles and similar applications. As we evolve towards vast, ever-changing conditions, it becomes crucial to be able to build a fast, self-learning, self-training system that is capable of remembering past events for a long time. Decisions will have to be taken rapidly based on an event's point in time, importance and priority.

Imagine an autonomous vehicle with ever-changing events. We are developing our new RNN to learn on its own about these events, perform an analysis, evaluate a numerous amount of possible solutions, make an optimal decision and execute it. That is why we are creating a new architecture LSTM hierarchical algorithm in order to enable high-speed, high-capacity data input with point of time consideration. The world of computing has evolved dramatically over the past decade as we generate data at a faster rate than we can analyze it. The new RNN is targeted to be implemented within GBT's microchip's technologies. It's a powerful AI platform targeted to a wide variety of applications including autonomous vehicles, robotics, medicine and civil/military security systems. GBT foresee an on-going development for this new family of RNN algorithms with the goal of creating superior real-time, accurate decision making systems."

Mobileye, an Israel-based subsidiary of Intel Corporation (NasdaqGS:INTC), announced agreements with SAIC, a leading Chinese OEM, and the leaders of Daegu Metropolitan City, South Korea. According to the press release, SAIC “plans to use Mobileye’s REM mapping technology to map China for L2+ ADAS [advanced driver-assistance systems] deployment while paving the way for autonomous vehicles in the country,” while Daegu “agreed to establish a long-term cooperation to deploy MaaS based on Mobileye’s self-driving system.” Amnon Shashua, Mobileye president & CEO and Intel senior vice president, said:

"These two new agreements build our global footprint in both MaaS and ADAS and demonstrate our commitment to true global leadership toward full autonomy."

Global AI Chipset Market to Reach $38.46 Billion by 2023

A report from Market Research Future finds that the global AI Chipset market will grow from $4.29 billion in 2018 to $38.46 billion by 2023 with a compound annual growth rate (CAGR) of 39.18 percent in the forecast period. An excerpt from the report description defines and outline the market:

Artificial intelligence (AI) chipsets are silicon-based chips powered with AI technologies, such as machine learning, deep learning, natural language processing, and neural network processing. These chipsets are designed such that they consume low power and offer high computing capabilities to smart devices, such as smartphones, laptops, and smart wearables. These chipsets increase the operational performance of the device with advanced augment reality (AR), virtual reality (VR), and analytical functions and enhance the user experience.

The increasing number of AI-enabled applications, developments in big data analytics, and the use of AI-based products and services to improve consumer experience are factors expected to drive the artificial intelligence (AI) chipset market during the forecast period. However, the lack of technical expertise and AI standards are expected to restrain the market growth during the forecast period. Further, integration of AI with edge computing devices and development of human-aware AI systems are expected to act as an opportunity for the global artificial intelligence (AI) chipset market during the forecast period.

Sam Mowers, Investorideas.com

             
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