The #AIEye: GBT Technologies (OTC: $GTCH) Begins Development of Graph Neural Network Algorithms to Enhance Avant! AI and IBM (NYSE: $IBM) Launches #AI-Powered Maximo Asset Monitor
Global Edge AI Software Market to Reach $1.668 Billion USD by 2026
Point Roberts WA, Vancouver BC – November 6, 2019 – 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) (NYSE:IBM)
GBT Technologies Inc. (OTCPINK:GTCH) has begun development of Graph Neural Network (GNN) based autonomous machine algorithms as part of the research to enhance its Avant! AI. According to the press release, GNN is “a type of Neural Network which directly operates on the Graph structure, modeling the dependencies between nodes in a graph and enabling advanced algorithms in a supervised manner”. Danny Rittman, GBT's CTO, explained:
"We develop advanced AI technology to solve problems that only humans could have solved in the past. Through our development projects, we are seeking to implement our deep learning technology specifically for conditions including autonomous cars. Avant! already includes advanced pattern recognition, sequence learning, and neural network graphs, and now our goal is to expand into supervised, dynamic GNN based algorithms to sharpen its learning curve and decision making.
Avant!'s new class of neural networks – the GNNs – will capture the dependence of vast amounts of nodes, each node representing a condition/situation, and will build a dependency tree in order to create reasoning models. The outcome of this development is a sophisticated AI system which is a perfect match for safe autonomous vehicles.
Besides the complex task of getting constant inputs about the vehicle and its surroundings conditions, analyzing it and making decisions in real time, we also target Avant! to become personalized to the user, learning his or her habits and life style, advising about anything from what type of coffee to buy or keeping them on schedule for an appointment."
IBM (NYSE:IBM) has launched a new AI-powered monitoring solution called Maximo Asset Monitor, aimed at improving asset management capabilities. Leveraging predictive analytics and AI-powered pattern recognition and anomaly detection, Maximo Asset Monitor will “help teams respond quickly to the most critical anomalies and gain greater insights into root cause variables that lead to asset failure”. Kareem Yusuf, Ph.D., general manager, IBM IoT, commented:
"With the launch of the new Maximo Asset Monitor solution, IBM is helping organizations better understand their data and automate workflows with preventative, predictive and prescriptive maintenance actions to help extend asset life and improve operations. According to IDC, monitoring performance and scheduling repairs with predictive maintenance can reduce maintenance costs by 15-20%, improve asset availability by 20%, and extend the lives of machines by years."
Global Edge AI Software Market to Reach $1.668 Billion USD by 2026
Research from Market Insights Reports finds that the global Edge AI Software market will grow from $354.2 million in 2018 to $1.668 billion by the end of 2025 with a compound annual growth rate (CAGR) of 24.8 percent. An excerpt from the report description defines the market:
Edge AI software enables aggregation, processing, computation, and analysis of data present near or on the edge devices by leveraging AI and IoT technologies. The software helps to process data on edge nodes even in remote and decentralized networks, without cloud connectivity.
Integrating AI with IoT in edge devices helps enterprises to minimize latency, reduce bandwidth, lessen threats, avoid duplication, improve reliability, and maintain compliance. Moreover, edge AI software solutions enable an organization to utilize the computing resources in an optimal manner, minimize the bandwidth required to execute the solution, and lower the latency in particular response time.
Sam Mowers, Investorideas.com
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