AI
We are in the fourth generation of AI. Do we know what that means?

What's next in AI

What we have now is narrow artificial intelligence (AI) — machines that can be trained to perform only one task at a time. What we need is AI that can mirror the human instinct. Yes, you heard that right: we’re talking about general artificial intelligence. 

But first, an introduction to the current scenario of where AI is at. AI is the newest kid on the block. It is a new-age tech that is impacting our lives in a myriad of ways. It is empowering individuals to re-evaluate how we use and analyze information to draw insights that inform our decision making. AI is getting into the realms of policymakers, opinion leaders, and interested observers. We are a witness to how AI is changing the world.

AI algorithms are intended to help us make decisions, most often using real-time information. They are different from passive machines in the sense that they are competent just for predetermined reactions — something like a logic tree. With the tremendous enhancements in storage systems, processing speeds, and analytic procedures, AI is becoming fit for huge advancement in analysis and decision making.

  • The first generation of AI was ‘descriptive analytics,’ which responds to the inquiry.
  • The second generation of AI was, ‘diagnostic analytics,’  which responds to reason.
  • The third generation of AI is ‘predictive analytics,’ which predicts what could probably occur.

A decade ago, AI was seens as incomprehensible. From tech giants to SaaS startups, companies of all sizes are trying to figure out how to make it usable. Algorithms assess relations in data instead of data properties, which is essentially how AI works. These algorithms are able to recognize new and undetected patterns, for example, cybercrime in what is by all accounts innocent transactions.

AI can be implemented in pretty much every industry. That said, substantial advancement in AI in being done in financial services. Banks and financial institutions are continuously utilizing AI to identify complex emerging cybercrimes. Suspicious financial activities are normally hidden in the piles of transaction data that have their own collection of related criteria.

While predictive analytics is useful and can save time for data scientists, it is still completely subjected to historic data. Hence, data scientists are left defenseless when confronted with new situations. To address this, we need machines that can think and respond intuitively when presented with a new circumstance. We need AI that can examine the data it is shown, yet demonstrate an intuitive behavior when something doesn’t make any sense. We need AI that can mirror the human instinct. 

Luckily, we have it.

“I predict that AI will finally move toward its fourth generation, in which computers will be trained to do things that historically only human beings could do. They will display common sense, gut feelings, and Artificial Intuition: the ability to make deductions based on very partial information. We at ThetaRay are at the forefront of this new development”, says Mark Gazit, CEO of ThetaRay.

“I believe that one of the most promising areas for AI will be fintech applications, especially during the current global health crisis. The ability of financial institutions to know and identify their customers has become more difficult. It has become incredibly challenging to create rules and build automation-based systems when customer behavior has changed so drastically. Banks now require computers that can take the place of very senior, experienced bankers and investigators. Criminals are increasingly using AI to commit financial cybercrime, so banks need an advanced level of artificial intelligence and intuition to detect and defeat them.”

The fourth generation of AI is ‘artificial intuition,’.

This kind of AI will empower machines to recognize threats and opportunities without being predefined about what to search for. Just as our instincts permit us to make decisions without explicitly being told to, or being made to choose a specific response. 

Think of it like a seasoned detective who sees a crime scene and instinctively realizes the missing pieces in the puzzle or can detect a pattern before anyone else does. 

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