AI: a modern “Deus ex Machina” by Niki Kouri Maglaras

Highlighting the pioneering work of Frank Rosenblatt, Kouri-Maglaras observes, “Frank Rosenblatt is sometimes called the father of deep learning for his pioneering work on artificial neural networks and the invention of perception in 1958.”

This first neural network could learn new skills through trial and error, simulating human thought processes. However, time constraints led to the first “AI winter,” with progress stalled due to challenges in handling unstructured data and insufficient computing power.

The resurgence of artificial intelligence research in the 1980s marks a historic moment for the technology.

Kouri-Maglaras explains: “Neural network research came back into prominence in the 1980s, and new researchers began studying Rosenblatt’s work again.”

The development of backpropagation algorithms, which allow neural networks to make adjustments based on errors, has been a significant advance. “Backpropagation is a simple way of using computation to train a multilayer neural network by propagating the effect of an error backwards.”

The turning point came with advances in hardware, particularly the development of GPUs by companies like NVIDIA.

“NVIDIA GPUs were invented for graphics processing, which became widely used in gaming and general graphics rendering in the late 1990s,” says Kouri-Maglaras. Unlike CPUs, which handle tasks in series, GPUs perform parallel processing, which is essential for the massive computations required in modern AI models like GPT-4, which boasts a whopping 1 trillion parameters.

As we enter the new millennium, the convergence of hardware innovation and the explosion of digital data have catalyzed the exponential growth of AI. Kouri-Maglaras quotes Ernest Hemingway to illustrate this phenomenon: “Gradually, then suddenly, which is exactly how exponential functions work.”

He points out that venture capital investment in AI began to increase around 2014, further accelerating development.

The impact of AI on computing power has been staggering. According to Moore’s Lawthe number of transistors on integrated circuits doubles about every 18 months, leading to a billion-fold improvement in processing efficiency over the past 30 years. “Our cars haven’t even gotten ten times more efficient in that same time frame,” says Kouri-Maglaras.

This exponential growth in processing power, coupled with the enormous amounts of data generated by digital communications, has been instrumental in training increasingly sophisticated artificial intelligence models.

In the insurance industry, AI is revolutionizing operations and customer interactions. Prudential Financial, under Kouri-Maglaras, is leveraging AI for customer service, product recommendations, and financial wellness optimization.

“We can take care of all the requests, like giving me the status of my claim, getting me my personal contract, getting me my premium paid,” he explains. AI-powered chatbots and virtual assistants improve customer service by providing immediate and accurate responses.

The potential of AI extends to loss prevention and promoting health and financial well-being. Kouri-Maglaras highlights the use of AI-powered wellness apps to track physical activity, measure health metrics, and incentivize healthier behaviors.

“The idea is to use a total wellness app to track physical activity, measure steps and heart rate via smartwatches and smartphone apps, and modify behavior through incentives and goals,” he said. Similar principles apply to financial health, where advanced optimization algorithms offer dynamic, personalized financial planning and recommendations.

However, the rapid pace of AI progress requires responsible and ethical use. Kouri-Maglaras stresses the need for proper governance and protections, saying, “AI is only as good as our data, only as good as we are.” He drew a parallel with ancient Greek drama, where characters such as Euripides, Aeschylus, and Sophocles represented different worldviews, reflecting the ethical considerations needed in AI today.

Kouri-Maglaras echoed Bill Gates’ sentiment: “Sometimes we overestimate the impact of AI in the short term and underestimate it in the long term.” He emphasized that while current AI applications are transformative, the future holds even greater potential as computing power continues to grow exponentially.

“We’re definitely scratching the surface.”

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