Mark Zuckerberg’s company wants to take the AI fight to tech giants and has the monetary backing to fuel it for years.
Meta is willing to spent an additional $9 billion a year to train AI models that beat Google, Microsoft and integrate into existing products like Instagram.
OpenAI notes that information related to bioterrorism is easily accessible to anybody, even without AI, as there is dangerous content in online resources and databases.
Explore OpenAI’s study that reveals how AI could inadvertently assist in creating biological threats.
Photonic integrated circuits are an important next-wave technology. These sophisticated microchips hold the potential to substantially decrease costs and increase speed and efficiency for electronic devices across a wide range of application areas, including automotive technology, communications, health care, data storage, and computing for artificial intelligence.
Photonic circuits use photons, fundamental particles of light, to move, store, and access information in much the same way that conventional electronic circuits use electrons for this purpose. Photonic chips are already in use today in advanced fiber-optic communication systems, and they are being developed for implementation in a broad spectrum of near-future technologies, including light detection and ranging, or LiDAR, for autonomous vehicles; light-based sensors for medical devices; 5G and 6G communication networks; and optical and quantum computing.
Given the broad range of existing and future uses for photonic integrated circuits, access to equipment that can fabricate chip designs for study, research and industrial applications is also important. However, today’s nanofabrication facilities cost millions of dollars to construct and are well beyond the reach of many colleges, universities, and research labs.
A renowned Chinese scholar has unveiled what he’s calling the world’s first AI child — and she might bring the technology into a new age.
In a groundbreaking study published in the journal Science, researchers have developed a machine learning model that mimics the way children learn language, offering new insights into early language acquisition. Using video and audio recordings from a young child’s perspective, the model successfully learned to associate words with visual objects, a feat that sheds light on the mysterious process of how children begin to understand and use language.
Understanding how children learn language has long been a fascinating subject for scientists and educators alike. At the heart of this is the phenomenon of connecting words to their meanings – a process seemingly simple yet incredibly complex. This study sought to demystify this process using the latest advancements in artificial intelligence.
The motivation behind this research lies in the need for a deeper understanding of early language acquisition. Traditionally, studies in this field have been conducted in controlled laboratory settings, which may not accurately reflect the natural environment in which children learn language.
On Apple’s earnings call, CEO Tim Cook said the company continues to work and invest in artificial intelligence.
What sets Tong Tong apart from other models is that she can assign herself tasks.
Chinese scientists have unveiled what they are calling the world’s first artificial intelligence (AI) child.
Developed by the Beijing Institute for General Artificial Intelligence (BIGAI), Tong Tong or Little Girl’s virtual AI avatar was recently introduced for the first time in Beijing.
BIGAI sees Tong Tong as a giant step toward achieving a general artificial intelligence (AGI) agent when a machine can think and reason like a human being.
Dive into the world of advanced robotics as Carnegie Mellon University pioneers a modular robotic system for inspecting and repairing natural gas pipelines.
See how CMU’s wheeled robot helps gas pipeline maintenance, from mapping the hidden pipelines to on-the-spot repairs.
Mastercard has announced that it has developed an in-house generative AI to help combat fraud on its payment processing network.
Instead of relying on textual inputs, Mastercard’s algorithm uses a cardholder’s merchant visit history as a prompt to determine whether a transaction involves a business that the customer would likely visit. The algorithm generates pathways through Mastercard’s network, akin to heat-sensing radar, to provide a score as an answer.
A lower score indicates a behavior that deviates from the cardholder’s usual pattern, while a higher score reflects typical behavior. Mastercard claims that this entire process takes only 50 milliseconds. And, it turns out, the AI appears to be very good at its job.
NASA has set its sights on sending human crews back to the moon and establishing a permanent base on the lunar surface. The agency wants to return to the moon, build a lunar outpost, and eventually send humans to Mars. But these missions come with risks and challenges.
As humans venture deeper into space and explore other worlds, they face daunting challenges.
How will they survive the harsh and unpredictable environments they encounter? What if meteorites, radiation, or other hazards damage their habitats? Delegating routine tasks to machines could save them time and resources, but how will they make sure these machines are reliable? These are just some pressing questions that must be answered to travel safely and sustainably beyond Earth’s orbit.
