Elon Musk has been promising the world a humanoid robot called Optimus for more than a year, but the two prototypes unveiled last week did not exactly dazzle with agility. The company's most advanced robot--made with all Tesla components and close to production-ready, according to Musk--waved unsteadily before being shoved across the stage by three human helpers. "This means a future of abundance, a future where there is no poverty, where you can have whatever you want," Musk said of the machine, which was mounted on a stand and cannot yet walk on its own. "It really is a fundamental transformation of civilization." A second humanoid robot, described by Musk as for "rough development" and made from a mixture of Tesla and off-the-shelf parts, was able to walk forward--very unsteadily.

For a decade now, many of the most impressive artificial intelligence systems have been taught using a huge inventory of labeled data. An image might be labeled "tabby cat" or "tiger cat," for example, to "train" an artificial neural network to correctly distinguish a tabby from a tiger. The strategy has been both spectacularly successful and woefully deficient. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences. Such "supervised" training requires data laboriously labeled by humans, and the neural networks often take shortcuts, learning to associate the labels with minimal and sometimes superficial information.

State and local officials need to act proactively to make sure that widespread use of self-driving vehicles doesn't leave out historically disadvantaged communities, a team of researchers from the Urban Institute warned in a new report. The researchers said a broad shift from human drivers to software-piloted vehicles could help poor people and non-white communities, if the technology can reduce the number of traffic deaths and cut down on the air pollution that disproportionately affects those residents. Autonomous vehicles could also increase transportation options for older people or people with disabilities, the Urban analysts said. But none of those advantages are guaranteed, they cautioned. "The degree to which [autonomous vehicles] change the transportation system and society overall will be mediated by regulatory choices at the local, state and federal levels," the researchers wrote in their report. "If [autonomous vehicles] ultimately reinforce inequitable access to transportation, reduce public transit use, increase [the amount of driving], increase congestion and exacerbate the causes of climate change, this technological advancement may ultimately fall short of its full promise--or even worsen the existing problems endemic to the automobile-dominated US transportation system," they added.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! For years, U.S. defense officials and Washington think-tankers alike have debated whether the future of our military could -- or should -- look a little less human. Already, the U.S. military has started to rely on technology that employs machine learning, artificial intelligence (AI), and big data -- raising ethical questions along the way. While these technologies have countless beneficial applications, ranging from threat assessment to preparing troops for battle, they rightfully evoke concerns about a future in which Terminator-like machines take over.

Text-to-image art generators work through a process called deep learning, in which algorithms make predictions and complete tasks in a process that mimics the human brain's neurons. In the case of AI-generated art, the generators pull from a database of existing pictures and illustrations to put together a discrete piece based on a user's prompt. Pinkney explained that his own creation is adapted from an open-source deep-learning model called Stable Diffusion, which already has vast data sets of information. Text-to-Pokémon works by matching Stable Diffusion's data sets to a data set of 850 Pokémon images from a previous university-run research project, which Pinkney filed using an automated caption system to categorize each image with a text description.

Electronic design automation (EDA) or computer-aided design (CAD) is a category of software tools for designing electronic systems, such as integrated circuits (ICs). With EDA tools, designers can finish the design flow of very large scale integrated (VLSI) chips with billions of transistors. EDA tools are essential to modern VLSI design due to the large scale and high complexity of electronic systems. Recently, with the boom of artificial intelligence (AI) algorithms, the EDA community is actively exploring AI for IC techniques for the design of advanced chips. Many studies have explored machine learning (ML) based techniques for cross-stage prediction tasks in the design flow to achieve faster design convergence.

Jeff Bezos has wanted a home robot for a long time. By 2017, Amazon's founder, an avid sci-fi fan, had repeatedly asked the company's engineers and executives about the feasibility of such a project, says Ken Kiraly, a vice president who helped create the Kindle ebook reader. That was the year Amazon's special projects team judged that it was finally the right time to begin building a home robot, due to the maturity of artificial intelligence and robotics, falling cost of sensors and computer chips, and risk that competitors had similar plans. They got started despite one big unknown: what Amazon's home robot would be good for. "Robots are hard," says Kiraly, who put together the team on the project.

But the drive also showed that the technology is not yet ready to realize its potential. Each day, Kodiak rotated a new team of specialists into the cab of its truck, so that someone could take control of the vehicle if anything went wrong. These "safety drivers" grabbed the wheel multiple times. Tech start-ups like Kodiak have spent years building and testing self-driving trucks, and companies across the trucking industry are keen to reap the benefits. At a time when the global supply chain is struggling to deliver goods as efficiently as businesses and consumers now demand, autonomous trucks could alleviate bottlenecks and reduce costs.

There are huge volumes of child sexual abuse photos and videos online--millions of pieces are removed from the web every year. These illegal images are often found on social media websites, image hosting services, dark web forums, and legal pornography websites. Now a new tool on one of the biggest pornography websites is trying to interrupt people as they search for child sexual abuse material and redirect them to a service where they can get help. Since March this year, each time someone has searched for a word or phrase that could be related to child sexual abuse material (also known as CSAM) on Pornhub's UK website, a chatbot has appeared and interrupted their attempted search, asking them whether they want to get help with the behavior they're showing. During the first 30 days of the system's trial, users triggered the chatbot 173,904 times.

From reminding potty-training toddlers to go to the loo to telling bedtime stories and being used as a "conversation partner", voice-activated smart devices are being used to help rear children almost from the day they are born. But the rapid rise in voice assistants, including Google Home, Amazon Alexa and Apple's Siri could, researchers suggest, have a long-term impact on children's social and cognitive development, specifically their empathy, compassion and critical thinking skills. "The multiple impacts on children include inappropriate responses, impeding social development and hindering learning opportunities," said Anmol Arora, co-author of an article published in the journal Archives of Disease in Childhood. A key concern is that children attribute human characteristics and behaviour to devices that are, said Arora, "essentially a list of trained words and sounds mashed together to make a sentence." The children anthropomorphise and then emulate the devices, copying their failure to alter their tone, volume, emphasis or intonation.