Mumbai (Maharashtra) [India], May 7 (ANI/NewsVoir): Since the dawn of the 2000s, Artificial Intelligence (AI) has been making waves through its penetration into various sectors. While AI helps increase efficiency and speed in a system, the lack of feedback when faced with errors has been a glaring concern.
Recently developed Explainable Artificial Intelligence (XAI) technology tackles this issue by analyzing data to provide users with explanations for given issues and activities. Utilizing this technology to create investment strategies, Elystar aims to increase net returns by reducing machine/AI-made errors and thereby successfully leveraging the superior insights provided by AI. Artificial Intelligence in finance is a relatively new concept that is still being explored and experimented upon. While few of the firms experimenting are sparingly using it for short-term trading, we have spent the past 15 months developing models to use it for long-term investments. One simple way to
Elystar redefines Public Securities Investment with explainable Artificial Intelligence - Founder, Dr Satya Gautam Vadlamudi ANI | Updated: May 07, 2021 17:55 IST
Mumbai (Maharashtra) [India], May 7 (ANI/NewsVoir): Since the dawn of the 2000s, Artificial Intelligence (AI) has been making waves through its penetration into various sectors. While AI helps increase efficiency and speed in a system, the lack of feedback when faced with errors has been a glaring concern.
Recently developed Explainable Artificial Intelligence (XAI) technology tackles this issue by analyzing data to provide users with explanations for given issues and activities. Utilizing this technology to create investment strategies, Elystar aims to increase net returns by reducing machine/AI-made errors and thereby successfully leveraging the superior insights provided by AI.
Elystar redefines Public Securities Investment
07 May 2021, 22:56 GMT+10
Mumbai (Maharashtra) [India], May 7 (ANI/NewsVoir): Since the dawn of the 2000s, Artificial Intelligence (AI) has been making waves through its penetration into various sectors. While AI helps increase efficiency and speed in a system, the lack of feedback when faced with errors has been a glaring concern.
Recently developed Explainable Artificial Intelligence (XAI) technology tackles this issue by analyzing data to provide users with explanations for given issues and activities. Utilizing this technology to create investment strategies, Elystar aims to increase net returns by reducing machine/AI-made errors and thereby successfully leveraging the superior insights provided by AI.
Explanation Processes can Make Artificial Intelligence Understandable
Written by AZoRoboticsApr 12 2021
Studying X-ray images, sifting through job applications and indicating new track list human-machine interaction has become an important part of contemporary life.
Image Credit: Peshkova/shutterstock.com
Algorithmic decision-making is the basis for such artificial intelligence (AI) processes. But since these processes are usually hard to interpret, they generally prove less useful than expected.
Now, scientists from Paderborn University and Bielefeld University are planning to change this and are debating how the explainability of AI can be enhanced and adapted to the requirements of human users.
The researchers’ study was recently published in the renowned journal
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