ChatGPT may do an impressive job at correctly answering complex questions, but a new study suggests it may be absurdly easy to convince the AI chatbot that it’s in the wrong.

A team at Ohio State University challenged large language models (LLMs) like ChatGPT to a variety of debate-like conversations in which a user pushed back when the chatbot presented a correct answer.

Through experimenting with a broad range of reasoning puzzles, including math, common sense, and logic, the study found that when presented with a challenge, the model was often unable to defend its correct beliefs and instead blindly believed invalid arguments made by the user.

There is no computer even remotely as powerful and complex as the human brain. The lumps of tissue ensconced in our skulls can process information at quantities and speeds that computing technology can barely touch.

Key to the brain’s success is the neuron’s efficiency in serving as both a processor and memory device, in contrast to the physically separated units in most modern computing devices.

There have been many attempts to make computing more brain-like, but a new effort takes it all a step further – by integrating real, actual, human brain tissue with electronics.

Researchers at Tufts University and Harvard University’s Wyss Institute have created tiny biological robots that they call Anthrobots from human tracheal cells that can move across a surface and have been found to encourage the growth of neurons across a region of damage in a lab dish.

The multicellular robots, ranging in size from the width of a human hair to the point of a sharpened pencil, were made to self-assemble and shown to have a remarkable healing effect on other cells. The discovery is a starting point for the researchers’ vision to use patient-derived biobots as new therapeutic tools for regeneration, healing, and treatment of disease.

The work follows from earlier research in the laboratories of Michael Levin, Vannevar Bush Professor of Biology at Tufts University School of Arts & Sciences, and Josh Bongard at the University of Vermont in which they created multicellular biological robots from frog embryo cells called Xenobots, capable of navigating passageways, collecting material, recording information, healing themselves from injury, and even replicating for a few cycles on their own.

A team of AI researchers from EquiLibre Technologies, Sony AI, Amii and Midjourney, working with Google’s DeepMind project, has developed an AI system called Student of Games (SoG) that is capable of both beating humans at a variety of games and learning to play new ones. In their paper published in the journal Science Advances, the group describes the new system and its capabilities.

Over the past half-century, computer scientists and engineers have developed the idea of machine learning and artificial intelligence, in which human-generated data is used to train computer systems. The technology has applications in a variety of scenarios, one of which is playing board and/or parlor games.

Teaching a computer to play a board game and then improving its capabilities to the degree that it can beat humans has become a milestone of sorts, demonstrating how far artificial intelligence has developed. In this new study, the research team has taken another step toward artificial general intelligence—in which a computer can carry out tasks deemed superhuman.

Radioisotope Thermoelectric Generators (RTGs) have a long history of service in space exploration. Since the first was tested in space in 1961, RTGs have gone on to be used by 31 NASA missions, including the Apollo Lunar Surface Experiments Packages (ALSEPs) delivered by the Apollo astronauts to the lunar surface. RTGs have also powered the Viking 1 and 2 missions to Mars, the Ulysses mission to the Sun, Galileo mission to Jupiter, and the Pioneer, Voyager, and New Horizons missions to the outer Solar System – which are currently in (or well on their way to) interstellar space.

In recent years, RTGs have allowed the Curiosity and Perseverance rovers to continue the search for evidence of past (and maybe present) life on Mars. In the coming years, these nuclear batteries will power more astrobiology missions, like the Dragonfly mission that will explore Saturn’s largest moon, Titan. In recent years, there has been concern that NASA was running low on Plutonium-238, the key component for RTGs. Luckily, the U.S. Department of Energy (DOE) recently delivered a large shipment of plutonium oxide, putting it on track to realize its goal of regular production of the radioisotopic material.

The recent shipment of 0.5 kg (over 1 lb) of plutonium oxide from the U.S. Department of Energy’s (DOE’s) Oak Ridge National Laboratory to its Los Alamos National Laboratory is critical to realize NASA’s planned future missions. It is also the largest shipment since the DOE issued its report to Congress in 2010 – “Startup Plan for Plutonium-238 Production for Radioisotope Power Systems.” As per this plan, this delivery is a significant step toward achieving the goal of a sustained annual production rate of 1.5 kg (3.3 lbs) by 2026.

One question has relentlessly followed ChatGPT in its trajectory to superstar status in the field of artificial intelligence: Has it met the Turing test of generating output indistinguishable from human response?

Two researchers at the University of California at San Diego say it comes close, but not quite.

ChatGPT may be smart, quick and impressive. It does a good job at exhibiting apparent intelligence. It sounds humanlike in conversations with people and can even display humor, emulate the phraseology of teenagers, and pass exams for law school.