Artificial Intelligence as a Service (AIaaS) is emerging along with other models of cloud computing such as SaaS, PaaS, IaaS, and FaaS. AIaaS helps healthcare providers and startups access AI tools. They can do this without spending money on expensive infrastructure. AIaaS is an emerging but important service model in healthcare, enabling advanced diagnostics, process automation, and improved patient care.
"Advancing creativity with artificial intelligence. Runway is an applied AI research company shaping the next era of art, entertainment and human creativity."
KnowledgeMiner is a great portal which is related to different types of computer resources. It covers mainly data mining, neural network, artificial intelligence, environments, bioinformatics, mobile, technology and more.
"Her makes the possibility of human-like artificial intelligence, or AI, feel all-too possible. But speech recognition, advanced linguistic processing and the wireless networks we'll need to deliver these always-on digital agents exist right now, and they're getting better."
Sir William Henry Perkin, a pioneering British chemist is considered the father of the chemical industry and known for the development of the first synthetic dye mauve, artificial colors, and synthetic fragrances.
Wearable devices are making increased use of artificial intelligence. Most wearable devices designed to track activities like users are exercising on a stationary bike or treadmill or when they are skiing.
In Fintech industry, artificial intelligence (AI) is continuously growing in the global scenario at a significant pace. The report deeply studies the current state of AI in Fintech industry.
"TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally devel"
Lera Technologies brings Intelligent Process Automation Services, Artificial Intelligence, Robotic Process Automation, and Smart Analytics Solutions together to automate business processes and drive innovation of the future.
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The growing demand for digital technology and shifting customer demands have resulted in the increased adoption of artificial intelligence (AI) solutions to manage financial assets and enhance the customer experience. AI solutions are predominantly dependent on machine data that are generated from multiple sources, including data collected from customers and processes. The financial institutions, especially investment banks, have started using AI based analytics solutions to analyze data and identify the correlation & patterns to improve the asset management capability. These technologies are among the prominent solutions to deal with ever-changing financial regulatory & compliance environment to face the associated market risk and understand both income tax & corporate tax laws in an efficient way. AI in financial asset management is also witnessing a strong presence in analyzing consumer behavior patterns to bring new offerings and is finding new distribution channels for the financial institutions that can create a competitive advantage with the use of these technologies.
As data-driven financial decision becomes a more prominent factor for increasing profitability, the market is expected to witness increased usage of AI solutions across banks, financial institutions, and insurance firms. Investment banks have been the primary users of the AI technology to improve risk assessment of the customer to optimize portfolios. Furthermore, IoT, cloud technology, edge computing, security-related technology (blockchain), etc. are supporting the market growth. This trend is expected to continue during the forecast period 2019-2025, fueling the market growth at a CAGR of 33.84% to reach revenue of $11.39 billion by 2025.
Internet of Things is used to collect the huge amount of data that is required by the AI algorithms. And, these algorithms convert the data into actionable results that can be implemented by the IoT devices. Why IoT needs AI, read this article.