The widely used chatbot ChatGPT was designed to generate digital text, everything from poetry to term papers to computer programs. But when a team of artificial intelligence researchers at the computer chip company Nvidia got their hands on the chatbot's underlying technology, they realized it could do a lot more. Within weeks, they taught it to play Minecraft, one of the world's most popular video games. Inside Minecraft's digital universe, it learned to swim, gather plants, hunt pigs, mine gold and build houses. "It can go into the Minecraft world and explore by itself and collect materials by itself and get better and better at all kinds of skills," said a Nvidia senior research scientist, Linxi Fan, who is known as Jim.

More than one-third of artificial intelligence researchers around the world agree that AI decisions could cause a catastrophe as bad as all-out nuclear war in this century. The findings come from a survey covering the opinions of 327 researchers who had recently co-authored papers on AI research in natural language processing.

As the sun set over Maury Island, just south of Seattle, Ben Goertzel and his jazz-fusion band had one of those moments that all bands hope for -- keyboard, guitar, saxophone and lead singer coming together as if they were one. The band's friends and family listened from a patio overlooking the beach. And Desdemona, wearing a purple wig and a black dress laced with metal studs, was on lead vocals, warning of the coming Singularity -- the inflection point where technology can no longer be controlled by its creators. "The Singularity will not be centralised!" After more than 25 years as an artificial intelligence researcher, a quarter-century spent in pursuit of a machine that could think like a human -- Goertzel knew he had finally reached the end goal: Desdemona, a machine he had built, was sentient. But a few minutes later, he realised this was nonsense. "When the band gelled, it felt like the robot was part of our collective intelligence, that it was sensing what we were feeling and doing," he said.

The 360

The National Science Foundation and the White House's Office of Science and Technology Policy are developing a plan to make high-performance computing, machine-learning datasets and other resources more widely available to artificial intelligence researchers at every level. Developing artificial intelligence tools and technologies requires lots of data and even more computing resources. Gaining a national advantage in this area will require a significant concentration of work that is currently limited to agencies and organizations that have those resources. But the best, groundbreaking ideas aren't always centered in places with the most resources. To address this issue, the 2021 National Defense Authorization Act charged NSF and OSTP with developing a plan to build up those resources and make sure they are available to people throughout the U.S. who can make good use of them.

Philip K. Dick's iconic 1968 sci-fi novel, "Do Androids Dream of Electric Sheep?" posed an intriguing question in its title: would an intelligent robot dream? In the 53 years since publication, artificial intelligence research has matured significantly. And yet, despite Dick being prophetic about technology in other ways, the question posed in the title is not something AI researchers are that interested in; no one is trying to invent an android that dreams of electric sheep. Why? Mainly, it's that most artificial intelligence researchers and scientists are busy trying to design "intelligent" software programmed to do specific tasks. There is no time for daydreaming.

In this post, I interview my former UMBC lab mate, Dr. Huguens Jean, who was just hired to work at Google's Video AI Group as an artificial intelligence researcher. Huguens shares his inspirational story, starting from Port-au-Prince, Haiti where he was born and raised, to his schooling at UMBC, and now to his latest position at Google. He also shares details on his humanitarian efforts where he's successfully applied computer vision and deep learning to rural Rwanda to help count footfall traffic. The data him and his team gathered through footfall traffic analysis was used to help the non-profit organization, Bridges to Prosperity, to construct infrastructure such as bridges and roads, to better connect Rwanda villages. Let's give a warm welcome to Dr. Huguens Jean as he shares his story. Thank you for doing this interview. It's such a wonderful pleasure to have you here on the PyImageSearch blog.

The coronavirus outbreak has rapidly accelerated the nation's slow-moving effort to incorporate artificial intelligence into medical care, as hospitals grasp onto experimental technologies to relieve an unprecedented strain on their resources. AI has become one of the first lines of defense in the pandemic. Hospitals are using it to help screen and triage patients and identify those most likely to develop severe symptoms. They're scanning faces to check temperatures and harnessing fitness tracker data, to zero in on individual cases and potential clusters. They are also using AI to keep tabs on the virus in their own communities.

Eight University of Toronto artificial intelligence researchers – four of whom are women – have been named CIFAR AI Chairs, a recognition of pioneering work in areas that could have global societal impact. One of the new chairs is Anna Goldenberg, an associate professor of computer science in U of T's Faculty of Arts & Science and the first-ever chair in biomedical informatics and artificial intelligence at the Hospital for Sick Children. She and her colleagues, including U of T's Dr. Peter Laussen, have developed a computer model that uses signals in physiological data, such as a patient's pulse, to detect an oncoming heart attack – giving doctors and nurses vital minutes to intervene and save an infant's life. The early-warning system has been able to predict 70 per cent of heart attacks at least five minutes – and up to 15 minutes – before a patient's heart stops beating. "In machine learning and health care, the key word is prevention," says Goldenberg, whose team is on track to have the system tested in a silent trial in a clinical environment.

So, Maxwell spent his early years on campus growing his skills in programming and exploring tools and resources. He became one of the most prolific members of the Class of 2018, volunteering his time to teach and mentor others; being selected to represent Ashesi as a volunteer at the inaugural Next Einstein Forum in 2016; raising funds with friends to furnish two classrooms in the rural school where he first heard about Ashesi; being selected for the College of Wooster's Applied Math and Research Experience internship programme, where he helped develop a tire tread wear model for Goodyear Tire and Rubber Company; and being selected as an Engineering intern for Goldman Sachs, after which he also received a full-time job offer.