Artificial intelligence (AI)-driven chatbot ChatGPT has made headlines in recent weeks. It has been in the news for writing academic pieces, cracking exams, and even producing news stories. In fact, the journey of AI-driven tools dates back to 1950s and '60s when first such tools was built. From ELIZA in 1966 to ChatGPT, AI researchers covered a long road to produce tools that could potentially mimic human resposes. However, even though ChatGPT appears to be able to do just about anything, it has its limitations.

In the very near future, Amazon's famed voice assistant, Alexa, may sound quite different from the dutiful (and impersonal) voice you've grown accustomed to since it rolled out in 2014. At least, that's what Rohit Prasad, Amazon's senior vice president and head scientist for Alexa, announced at Amazon's re:MARS conference, a global artificial intelligence (AI) event that Amazon founder and executive chair Jeff Bezos hosted over the summer. With just a one-minute audio sample, the technology could bring a loved one's voice bounding through an Echo device's speakers. Prasad used a short presentation to show the audience how the new speech-synthesizer technology could help us forge lasting memories of our deceased relatives. "Alexa, can grandma finish reading me The Wizard of Oz?" A young boy asked a cute Echo speaker with big Panda eyes.

During the 20th century, researchers pushed the frontiers of science further than ever before with great strides made in two very distinct fields. While physicists discovered the strange counter-intuitive rules that govern the subatomic world, our understanding of how the mind works burgeoned. Yet, in the newly-created fields of quantum physics and cognitive science, difficult and troubling mysteries still linger, and occasionally entwine. Why do quantum states suddenly resolve when they're measured, making it at least superficially appear that observation by a conscious mind has the capacity to change the physical world? What does that tell us about consciousness?

Several prominent academic mathematicians want to sever ties with police departments across the U.S., according to a letter submitted to Notices of the American Mathematical Society on June 15. The letter arrived weeks after widespread protests against police brutality, and has inspired over 1,500 other researchers to join the boycott. These mathematicians are urging fellow researchers to stop all work related to predictive policing software, which broadly includes any data analytics tools that use historical data to help forecast future crime, potential offenders, and victims. The technology is supposed to use probability to help police departments tailor their neighborhood coverage so it puts officers in the right place at the right time. Dive deeper.Read the most in-depth science, math, and tech features, solve life's biggest mysteries, and get unlimited access to all things Pop Mech--starting now. "Given the structural racism and brutality in U.S. policing, we do not believe that mathematicians should be collaborating with police departments in this manner," the authors write in the letter.

In July 1848, L'illustration, a French weekly, printed the first photo to appear alongside a story. It depicted Parisian barricades set up during the city's June Days uprising. Nearly two centuries later, photojournalism has bestowed libraries with legions of archival pictures that tell stories of our past. But without a methodical approach to curate them, these historical images could get lost in endless mounds of data. That's why the Library of Congress in Washington, D.C. is undergoing an experiment. Researchers are using specialized algorithms to extract historic images from newspapers.

To prevent the United States from falling behind competitor nations like China, when it comes to the development of artificial intelligence-based technologies, the Trump administration has proposed vague regulatory guidelines that would limit potentially innovation-stifling governmental "overreach." The news comes amid the Consumer Electronics Show (CES) in Las Vegas, the largest annual trade show for the technology industry. That makes sense, given that each year, CES includes a slew of vendors that demonstrate AI-based tech. In a blog posted to the White House website and shared as a Bloomberg op-ed, Michael Kratsios, chief technology officer of the U.S., wrote that it's a "false choice" to have to choose between moral values and advancing emerging AI technology. "As part of the Trump Administration's national AI strategy--the American AI Initiative--the White House is today proposing a first-of-its-kind set of regulatory principles to govern AI development in the private sector," he wrote.

If today's college students could find a way to get their hands on a copy of Facebook's latest neural network, they could cheat all the way through Calc 3. They could even solve the differential equation pictured above in under 30 seconds. Okay, so maybe this isn't going to be a replacement for Wolfram Alpha anytime soon, but Facebook really did build a neural net that can complete complex mathematical problems for the first time, rather than the plain old arithmetic in which these AI models usually wheel and deal. The work represents a huge leap forward in computers' abilities to understand mathematical logic. The research is outlined in a new paper, "Deep Learning for Symbolic Mathematics," published in arXiv, a repository of scientific research in areas like math, computer science, and physics, run by Cornell University.

Researchers in Switzerland have figured out how to use AI to predict when and where lightning will strike. Researchers from École Polytechnique Fédérale de Lausanne used standard meteorological data and machine learning to build a simple system that can predict lightning strike to the nearest 10 to 30 minutes inside a radius of about 18.6 miles, according to an account in Popular Mechanics. "We have used machine learning techniques to successfully hindcast nearby and distant lightning hazards by looking at single-site observations of meteorological parameters," wrote the authors in a new paper published recently in the journal Climate and Atmospheric Science. The researchers used data about past lightning strikes to build an algorithm that can make predictions about new lightning strikes, in a process called hindcasting, as opposed for forecasting. Estimates based on past events are fed into a model to see how well the output matches known results.

A new generation of dexterous robots are making strides faster than ever before - literally. Advances in both mechanics and intelligent software designed after members of the animal kingdom - including humans - are pushing an increasing number of robotics companies closer to parity with the fastest members of their kind. As reported by Popular Mechanics, organizations like the Institute for Human & Machine Cognition (IHMC) have been plucking away at making a robot called the Planar Elliptical Runner (PER) - a bipedal bot that relies mostly on mechanics. A motor on PER drives the bots propulsion and moves its legs in an oval motion that help to balance weight and prevent it from tipping over. As The Verge notes, that locomotion is achieved without the use of sophisticated machine-vision that has found its way into other mobile robots.

In the future, will self-driving cars be our designated drivers? To those of us who enjoy a spirited spin along a twisty back road, an off-road adventure in a 4x4, or even a good old-fashioned stoplight drag race, a self-driving car has all the appeal of a self-eating cheeseburger. Unless, of course, we're able to throw a rolling interstate cocktail party, simultaneously toasting the marvels of technology and lamenting the obsolescence of the human race. Or at least peacefully sleep it off on the way home from Cousin Jethro's bachelor bash. All joking aside, Popular Mechanics does not advocate, condone, or encourage drinking and driving of any kind, at any time.