Machine learning advancements have made predictions easier, … "Machines are good at prediction, but they depend on data and judgment, …

However, the ethics of machine learning remains blurry for many.

Artificial intelligence is integral to developments in healthcare, … A lot of the data analyzed is also driven by machine learning adoption, …

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 look at this concept is to compare it with Microsoft Excel. While Excel is used in different fields and by different people, it is used in various ways and forms. Similarly, AI has a number of variations in which it can be utilized, so no two approaches may be completely the same. AI not only helps us scale and analyze data rapidly, but the integration of Explainable AI allows us to understand and eliminate unwarranted biases to create a sound investment strategy," said Dr Satya Gautam Vadlamudi, Founder and CEO of Elystar.

New Delhi: In a bid to increase use of artificial intelligence in the military, the US Air force conducted a major exercise with robot dogs trained to scout for threats before their human counterparts enter the field. The four-legged, headless, mechanical creatures were made to exit an aircraft and look for signs of danger at the Nellis Air Force Base in the US state of Nevada last week. They are part of an Advanced Battle Management System (ABMS) that the US Air force is building, which will use artificial intelligence and data analytics to detect counter threats to the US military. "Valuing data as an essential war fighting resource, one no less vital than jet fuel or satellites, is the key to next-gen warfare," Will Roper, assistant secretary of the Air Force for acquisition, technology and logistics, told CNN. The dogs have been manufactured by Ghost Robotics, a company based in Philadelphia, and are called Vision 60 UGVs, or "autonomous unmanned ground vehicles".

We are living through one of the most challenging and devastating health crises in living memory. This year has brought untold loss of life and livelihoods, the true worldwide repercussions of which are still to be seen. The COVID-19 pandemic has also altered the global business landscape, accelerating the pace and volume of data created through increased remote working and digital transacting, and fast shifting the economic realities for all business leaders. Against this backdrop, technology – artificial intelligence (AI), in particular – now has an even bigger role to play in helping organizations and countries to adapt, keep us safe and improve how we live and work. But the thirst and drive to innovate with these new technologies at speed must be balanced with the need to carefully build consumer trust in those same innovations.

It should have been artificial intelligence's moment in the sun. With billions of dollars of investment in recent years, AI has been touted as a solution to every conceivable problem. So when the COVID-19 pandemic arrived, a multitude of AI models were immediately put to work. Some hunted for new compounds that could be used to develop a vaccine, or attempted to improve diagnosis. Some tracked the evolution of the disease, or generated predictions for patient outcomes.

Video-based interviews, either on Skype or Facetime or as recorded links, have been used for some years, but now a new and tricky feature has become popular: HR tech companies have begun to deploy artificial intelligence (AI) to assess candidates even as their skills are being tested on several parameters. Companies are using AI-based voice recognition and facial recognition software that reads the candidate in a way that no human can. When a candidate answers questions, AI software reads expressions and measures voice modulation to get into the mind of the candidate. Lying and misleading expressions can be caught. Candidates hear an automated voice and see no one at the other end as they get time to answer questions while looking into the camera.