Since the release of ChatGPT last year, I've heard some version of the same thing over and over again: What is going on? The rush of chatbots and endless "AI-powered" apps has made starkly clear that this technology is poised to upend everything--or, at least, something. Yet even the AI experts are struggling with a dizzying feeling that for all the talk of its transformative potential, so much about this technology is veiled in secrecy. More and more of this technology, once developed through open research, has become almost completely hidden within corporations that are opaque about what their AI models are capable of and how they are made. Transparency isn't legally required, and the secrecy is causing problems: Earlier this year, The Atlantic revealed that Meta and others had used nearly 200,000 books to train their AI models without the compensation or consent of the authors.

Erik Brynjolfsson is in great demand. The US professor whose research focuses on the relationship between digital tech and human productivity is nearing the end of a European speaking tour that's lasted nearly a month. Speaking via Zoom as he prepares for his imminent lecture in Oxford, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI is enthused by recent "seminal breakthroughs" in the field. Brynjolfsson's tour – which has included appearances at the World Economic Forum in Davos and the Institute for the Future of Work in London – is neatly timed, because the recent arrival of ChatGPT on the scene has been capturing human minds, if not yet hearts. The large-scale language model, fed 300 billion words by developer OpenAI, caused a sensation with its powerful capabilities, attracting 1 million users within five days of its release in late November 2022.

For much of the last decade or more, it's rare that AI has been discussed without making comparisons with human abilities. For many, as AI advances, it produces an existential threat to humanity, whether in terms of our employability or even our very existence. Research from Stanford argues that such comparisons are unhelpful and that the reality is more likely to see man and machine working together in ways that compliment each other's strengths. What's more, if we can shift our mindset in such a way, it could unlock a wave of innovation and productivity improvements that benefit us all. For much of the development of AI, the vision has been to replicate human intelligence.

It has come to a point where artificial intelligence is also being used to enhance creativity. You give a phrase or two written by a human to a language model based on an AI and it can add on more phrases that sound uncannily human-like. They can be great collaborators for anyone trying to write a novel or a poem. Newsletter Click to get the day's best explainers in your inbox However, things aren't as simple as it seems. And the complexity rises owing to biases that come with artificial intelligence.

Last month, Stanford researchers declared that a new era of artificial intelligence had arrived, one built atop colossal neural networks and oceans of data. They said a new research center at Stanford would build--and study--these "foundational models" of AI. Critics of the idea surfaced quickly--including at the workshop organized to mark the launch of the new center. Some object to the limited capabilities and sometimes freakish behavior of these models; others warn of focusing too heavily on one way of making machines smarter. "I think the term'foundation' is horribly wrong," Jitendra Malik, a professor at UC Berkeley who studies AI, told workshop attendees in a video discussion.

Like superheroes capable of seeing through obstacles, environmental regulators may soon wield the power of all-seeing eyes that can identify violators anywhere at any time, according to a new Stanford University-led study. The paper, published the week of April 19 in Proceedings of the National Academy of Sciences (PNAS), demonstrates how artificial intelligence combined with satellite imagery can provide a low-cost, scalable method for locating and monitoring otherwise hard-to-regulate industries. Go to the web site to view the video. Brick production, a major industry in South Asia, is a source of pollution that threatens health. Regulating brick kilns is difficult because there is no database of kiln locations.

Nvidia Chief Executive Jen-Hsun Huang, intoduces new graphics processing products and advances based ... [ ] on their Kepler GPU computing architecture technology. Huang demonstrated how GPU's operating in cloud servers can now be used to work, play games or render video, during his keynote at the GPU Technology Conference in San Jose, California. "Within 20 years, machines will be capable of doing anything man can do." Take a stab at when this quote is from. You've surely heard about Artificial Intelligence (AI) before. "AI" often conjures up images of intelligent robots taking over the world.

Speech recognition systems are deep-rooted with bias toward people of color, a new study reveals. Stanford researchers found these technologies from Amazon, Apple, Google, IBM and Microsoft make twice as many errors when interpreting language from black people than words spoken by whites. The team fed systems with nearly 2,000 speech samples from 115 individuals, 42 whites and 73 blacks, and found the average error rate for whites was 19 percent and 35 percent for blacks. Apple was found to perform the worst out of the group with a 45 percent error rate for black speakers and 23 percent for white speakers. Those involved with the study believed the inaccuracies are due to data sets used to train the systems are designed predominately by white people.

As a Stanford alum, I am excited to announce that IBM Research is the first founding corporate partner of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Building on decades of research collaboration across computer and materials science, IBM is committed to joining HAI to advance AI research, education, policy and practice that improve how we live, work, play and learn. In this new role, IBM will work closely with fellow AI thought leaders, researchers and innovators at Stanford and through participation on the HAI Corporate Advisory Committee. IBM researchers will also work alongside Stanford researchers as part of the Visiting Scholars program. Across departments and with other academic, industry and government leaders, IBM will work with HAI to collaborate to advance the state of the art in AI research and to understand the multi-dimensional impact of AI as it transforms economies, business, legal and political norms, societies and cultures.

The health care industry is in the business of performing miracles. Whether giving sight to the blind, helping the paralyzed walk or sequencing genes to stave off disease, today's doctors and surgeons are saving and improving lives in new ways. Society is blessed to have geniuses wearing stethoscopes and lab coats. Despite immense progress, the health care industry still struggles to answer its most pressing questions. How do we help more people live longer, healthier lives?