Aishe News

(toc) #title=(Table of Content) With the advent of cloud computing and big data, AI has become more accessible and affordable, leading to its increased adoption in various industries. The AI as a Service (AIaaS) market has emerged as a key growth area, providing businesses with access to AI technologies without the need for significant investment in infrastructure or expertise. AIaaS is a cloud-based service that enables businesses to access AI capabilities through APIs and other interfaces. The market for AIaaS is expected to grow significantly in the coming years, with increasing adoption across industries such as healthcare, finance, retail, and manufacturing. According to a report by MarketsandMarkets, the global AIaaS market is expected to grow at a Compound Annual Growth Rate (CAGR) of 56.7% from 2018 to 2025, reaching a market size of US$77.05 billion by 2025. Opportunities and Challenges 2023 to 2030 The increasing adoption of cloud-based AI solutions is a key trend in the ...

Artificial Intelligence as a Service (AIaaS) has been a game-changer for businesses across the globe. It is a third-party offering of out-of-the-box solutions that enable companies to implement and scale AI techniques at a fraction of the cost. One of the most notable examples of AIaaS is the AISHE System. The AISHE System is an AI-based autonomous trading system that uses sophisticated algorithms to make trading decisions in real-time. It is quick, transparent, flexible, simple to set up, cost-effective, prevents complex infrastructure, provides customization options, and is scalable. It makes AI technology accessible to everyone and helps improve user experiences, make data-driven decisions, and automate time-consuming tasks. The market for Artificial Intelligence as a Service (AIaaS) is expected to grow significantly in the coming years. One of the major factors driving the demand for AIaaS is the increasing number of traders who are rigorously looking to integ...

In today's fast-paced world of stock exchange, staying ahead of the game is crucial for traders and researchers alike. Artificial intelligence (AI) has the potential to revolutionize the industry, but its implementation has been hindered by a number of challenges, including data privacy and access to large and diverse datasets. However, a new technology called federated learning is poised to change all of that. Federated learning is a decentralized machine learning procedure that allows multiple data providers to train machine learning models without pooling their data. Instead, the data remains locked on servers and only the predictive models travel between the servers. This approach not only respects data ownership and privacy, but it also allows each participant to benefit from a larger pool of data, resulting in increased machine learning performance.   Federated Learning Brings AI to Stock Exchange The AISHE system is a prime example of how federated learning can be applied to...