A robotic gripper made from flexible ribbons can pick up objects as delicate as a dandelion to something 16,000 times heavier than itself. Most robotic grippers are specialised to perform a narrow set of tasks, but performing well in one domain often entails a trade-off. A tool well suited to picking up heavy objects, for example, normally struggles to manipulate much lighter, intricate objects.

Get ready, San Francisco: The state government on Thursday approved a major expansion of driverless robotaxi service throughout the city. And get ready, Los Angeles: The industry is planning to push for driverless rides here as soon as it gets permits to do so. The state's green light, on a 3-1 vote by the California Public Utilities Commission, signals a historic turning point for the robotaxi business as it evolves from fascinating experiment to commercial reality. It also marks the beginning of a grand experiment in public safety as thousands of multi-ton vehicles operated via artificial intelligence attempt to safely negotiate the hills and narrow streets of San Francisco. It highlights California's messy multiagency regulation of new automobile technology: Two agencies are in charge of the robotaxi business, the CPUC and the California Department of Motor Vehicles.

Traditional machine learning models often yield biased results, favouring groups with large populations or being influenced by unknown factors, and take extensive effort to identify from instances containing patterns and sub-patterns coming from different classes or primary sources. The medical field is one area where there are severe implications for biased machine learning results. Hospital staff and medical professionals rely on datasets containing thousands of medical records and complex computer algorithms to make critical decisions about patient care. Machine learning is used to sort the data, which saves time. However, specific patient groups with rare symptomatic patterns may go undetected, and mislabeled patients and anomalies could impact diagnostic outcomes.

The researchers, from the University of Cambridge, studied industry data from the UK and 24 other European countries between 1995 and 2017, and found that at low levels of adoption, robots have a negative effect on profit margins. But at higher levels of adoption, robots can help increase profits. According to the researchers, this U-shaped phenomenon is due to the relationship between reducing costs, developing new processes and innovating new products. While many companies first adopt robotic technologies to decrease costs, this'process innovation' can be easily copied by competitors, so at low levels of robot adoption, companies are focused on their competitors rather than on developing new products. However, as levels of adoption increase and robots are fully integrated into a company's processes, the technologies can be used to increase revenue by innovating new products.

As a child-size mannequin stands in a traffic lane on a rural two-lane road, a Tesla in Full Self-Driving mode barrels toward it. And the car drives on, as if nothing happened. It's the latest salvo from activist organization the Dawn Project, which publishes videos aimed at showing how badly Tesla's automated driving technology can behave. Dan O'Dowd, the wealthy, tech-savvy activist who founded and self-funds the Dawn Project, said he wants to ensure that "the safety-critical systems that everyone's life depends on are fail-safe and can't be hacked." While O'Dowd's stated goal is brand-agnostic, his main target since launching the Dawn Project in 2021 has been Tesla and its controversial Autopilot and Full Self-Driving systems.

Artificial intelligence is transforming many aspects of the practice of medicine, and some medical professionals are using these tools to help them with diagnosis. Doctors at Beth Israel Deaconess, a teaching hospital affiliated with Harvard Medical School, decided to explore how chatbots could be used -- and misused -- in training future doctors. Instructors like Dr. Rodman hope that medical students can turn to GPT-4 and other chatbots for something similar to what doctors call a curbside consult -- when they pull a colleague aside and ask for an opinion about a difficult case. The idea is to use a chatbot in the same way that doctors turn to each other for suggestions and insights. For more than a century, doctors have been portrayed like detectives who gather clues and use them to find the culprit.

Bloomberg reported yesterday that Apple has been working on its own AI-powered chatbot, internally known as "Apple GPT." While the company hasn't revealed concrete plans for public release, its engineers have reportedly been actively using the chatbot, which uses a large language model (LLM) framework named "Ajax." Running on Google Cloud and built with Google JAX, Ajax serves to unify machine learning development.

Artificial intelligence is the ability of machines to carry out intelligent tasks typically performed by humans. It involves the use of computers to reproduce or undertake such actions, often at a higher speed and accuracy than previously achieved. AI typically combines computer science with data to solve problems or make predictions. Its processes involve algorithms, which are a series of rules written into computer code. Historically, AI has been used to carry out complex mathematical tasks, or to play strategy games such as chess, often beating human competitors.

Apple has created its own generative artificial intelligence tools to compete with ChatGPT, according to a Bloomberg report Wednesday. Apple built its own framework that can create large language models, called "Ajax," as well as a chatbot service that internal engineers are calling Apple GPT, according to Bloomberg citing unnamed sources. It's part of the iPhone giant's bid to compete in the AI space, the report said. Apple didn't immediately respond to a request for comment. Large language models are what power generative artificial intelligence chatbots, like OpenAI's ChatGPT and Google's Bard.

A congressional committee focused on national security threats from China said it had "grave concerns" about a research partnership between the University of California, Berkeley, and several Chinese entities, claiming that the collaboration's advanced research could help the Chinese government gain an economic, technological or military advantage. In a letter sent last week to Berkeley's president and chancellor, the House Select Committee on the Chinese Communist Party requested extensive information about the Tsinghua-Berkeley Shenzhen Institute, a collaboration set up in 2014 with China's prestigious Tsinghua University and the Chinese city of Shenzhen. The letter pointed to the institute's research into certain "dual-use technologies" that are employed by both civilian and military institutions, like advanced semiconductors and imaging technology used for mapping terrain or driving autonomous cars. The committee also questioned whether Berkeley had properly disclosed Chinese funding for the institute, and cited its collaborations with Chinese universities and companies that have been the subjects of sanctions by the United States in recent years, like the National University of Defense Technology, the telecom firm Huawei and the Chinese drone maker DJI.