By now, I'm sure you've heard the term Machine Learning thrown a lot. Since most big companies and financial institutions rely on data to operate at such a large scale, it's no wonder that fields in data science are taking off. But what exactly is Machine Learning and how can we use it in a practical sense? Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed. The quote above is in my opinion the best general definition of what machine learning does.

Is that really Tom Cruise about to wrestle an alligator? Keanu Reeves dancing like nobody is watching? Deepfake technology is advanced artificial intelligence that replaces actual video and audio with video and audio that was artificially created from other sources. While it may look like harmless fun on TikTok, it's also becoming a huge security risk for businesses of all sizes. According to a just released report from the cloud service firm VMware, deepfake attacks are on the rise.

A new research project has found that the discretionary decisions made by human bank managers can be replicated by machine learning systems to an accuracy of more than 95%. Using the same data available to bank managers in a privileged dataset, the best-performing algorithm in the test was a Random Forest implementation – a fairly simple approach that's twenty years old, but which still outperformed a neural network when attempting to mimic the behavior of human bank managers formulating final decisions about loans. The Random Forest algorithm, one of four put through their paces for the project, achieves high human-equivalent scoring vs. performance of bank managers, despite the relative simplicity of the algorithm. The researchers, who had access to a proprietary dataset of 37,449 loan ratings across 4,414 unique customers at'a large commercial bank', suggest at various points in the preprint paper that the automated data analysis that managers are given to make their decision has now become so accurate that bank managers rarely deviate from it, potentially signifying that bank managers' part in the loan approval process chiefly consists of retaining someone to fire in the event of a loan default. 'From a practical perspective it is worth noting that our results may indicate that the bank could process loans faster and cheaper in the absence of human loan managers with very comparable results.

It's not just your face that can be convincingly replicated by a deepfake. It's also your voice -- quite easily as journalist Chloe Beltman found: Given the complexities of speech synthesis, it's quite a shock to find out just how easy it is to order one up. For a basic conversational build, all a customer has to do is record themselves saying a bunch of scripted lines for roughly an hour. "We extract 10 to 15 minutes of net recordings for a basic build," says Speech Morphing founder and CEO Fathy Yassa. The hundreds of phrases I record so that Speech Morphing can build my digital voice double seem very random: "Here the explosion of mirth drowned him out."

A new research project has found that the discretionary decisions made by human bank managers can be replicated by machine learning systems to an accuracy of more than 95%. Using the same data available to bank managers in a privileged dataset, the best-performing algorithm in the test was a Random Forest implementation – a fairly simple approach that's twenty years old, but which still outperformed a neural network when attempting to mimic the behavior of human bank managers formulating final decisions about loans. The Random Forest algorithm, one of four put through their paces for the project, achieves high human-equivalent scoring vs. performance of bank managers, despite the relative simplicity of the algorithm. The researchers, who had access to a proprietary dataset of 37,449 loan ratings across 4,414 unique customers at'a large commercial bank', suggest at various points in the preprint paper that the automated data analysis that managers are given to make their decision has now become so accurate that bank managers rarely deviate from it, potentially signifying that bank managers' part in the loan approval process chiefly consists of retaining someone to fire in the event of a loan default. 'From a practical perspective it is worth noting that our results may indicate that the bank could process loans faster and cheaper in the absence of human loan managers with very comparable results.

Cybercriminals cloned the voice of a company director in the U.A.E. to steal as much as $35 million in a huge and complex heist. In early 2020, a bank manager in the United Arab Emirates received a call from a man whose voice he recognized--a director at a company with whom he'd spoken before. The director had good news: His company was about to make an acquisition, so he needed the bank to authorize some transfers to the tune of $35 million. A lawyer named Martin Zelner had been hired to coordinate the procedures and the bank manager could see in his inbox emails from the director and Zelner, confirming what money needed to move where. The bank manager, believing everything appeared legitimate, began making the transfers.

Nisheeth K Vishnoi teaches computer science at Yale University. Sharing his perspective with Times Evoke, he discusses biases that could tilt AI, how algorithms are changing humans -- and whether technology can eventually make music like Ravi Shankar My work in AI explores models and algorithms that can mitigate biases -- recently, a lot of AI-based technology has been shown to be even more biased than human judgement. This poses a serious challenge if decisions on the distribution of social resources or citizens' rights are made by such algorithms. If these include human biases in them, in situations where they're often used, like a judge relying on AI to decide whom to give bail to or not, the algorithms could treat different sections of society very differently. Great art comes from absorbed human attention -- but this ability is now being changed by AI. (Picture courtesy: Getty Images) Our real intelligence One way AI algorithms work is'learning' -- this involves accessing data and training models on that data.

Digital transformation is redefining banking sector. The industry is adopting artificial intelligence and other disruptive technology to create value for their tech-savvy customers. Adoption of Artificial intelligence in banking sector enabling to deliver a seamless experience. But expectations are high and challenges are higher. We spoke to Raj Nair, President of IMC Chamber of Commerce and Industry to understand the development in the segment and the impact of AI in banking.

Empirical studies with humans and agents demonstrate that the nature and forms of information required by the human differ depending on the design of the relationship between the participants — a relationship that is sometimes characterised using the concept of levels of autonomy, though the usefulness of that characterisation has recently been questioned. Therefore, understanding how people work with automation and how to design automated systems to better support people, is a field long studied, but of growing importance. Our current work seeks to contribute to the design of representations and algorithms that can be deployed in such contexts.