Sam Altman is leaving no room for doubt about his views on an Elon Musk-led bid to take control of OpenAI. In a letter to OpenAI staff Monday, the CEO put the words "bid" and "deal" in scare quotes and said the startup's board has no interest in the offer. "Our structure exists to ensure that no individual can take control of OpenAI," Altman wrote, according to two sources with knowledge of the letter. "Elon runs a competitive AI company, and his actions are not about OpenAI's mission or values." Altman has also told employees that OpenAI's board, which he sits on, has yet to receive an official offer from Musk and the other investors.

An elderly grandmother who chats about knitting patterns, recipes for scones and the blackness of the night sky to anyone who will listen has become an unlikely tool in combatting scammers. Like many people, "Daisy" is beset with countless calls from fraudsters, who often try to take control of her computer after claiming she has been hacked. But because of her dithering and inquiries about whether they like cups of tea, the criminals end up furious and frustrated rather than successful. Daisy is, of course, not a real grandmother but an AI bot created by computer scientists to combat fraud. Her task is simply to waste the time of the people who are trying to scam her.

Jensen Huang and Lisa Su -- both born in Taiwan and now local celebrities for leading U.S. tech powerhouses -- employed different tacks in conveying their expertise during back-to-back shows at the world's largest computing conference in Taipei. Nvidia's CEO repeatedly voiced his 2.8 trillion company's dominance in the accelerators that OpenAI and Microsoft rely on to build generative AI services such as ChatGPT. Huang went as far as to tease a chip envisioned for 2026 he dubbed Rubin -- after Vera Rubin, the American woman who helped discover dark matter. The chip, which will succeed the Blackwell family, will be key to sustaining its runaway leadership.

On the busy streets of suburban Berlin, just south of Tempelhofer Feld, a white Kia is skillfully navigating double-parked cars, roadworks, cyclists, and pedestrians. The company kits its cars out with radar, GPS, ultrasound, and an array of other sensors to allow drivers like Dan to control the vehicles remotely from a purpose-built station equipped with a driver's seat, steering wheel, pedals, and three monitors providing visibility in front of the car and to its side. Vay's approach, which it calls teledriving, is pitched as an alternative to fully autonomous driving, which is proving much harder to achieve than first thought--as the likes of Waymo, Cruise, and Tesla are discovering. At Zoox, remote driving was used as a failsafe for driverless cars. If a self-driving car came across an unexpected obstacle, teleguidance would allow a human operator to take control of the vehicle remotely and steer it around the obstruction. But von der Ohe was frustrated by the industry's slow progress.

Software frameworks for behaviour are critical in robotics as they enable the correct and efficient execution of functions. While modern behaviour systems have improved their composability, they do not focus on smooth transitions and often lack functionality. In this work, we present the Director, a novel behaviour framework and algorithm that addresses these problems. It has functionality for soft transitions, multiple implementations of the same action chosen based on conditionals, and strict resource control. This system has shown success in the Humanoid Kid Size 2022/2023 Virtual Season and the Humanoid Kid Size RoboCup 2023 Bordeaux competition.

CEO and founder Michael Seifert creates a new marketplace for businesses that respect'fundamental' American values. Let's face it, there's data online about us everywhere. From our social media profiles to our online shopping habits, it seems like there's no escaping the collection of our personal information. And while some of this data is necessary for certain services, such as online shopping with Amazon, it's important to know what information is being collected and how it's being used. The good news is that you have some level of control over the data you're giving to Amazon.

Are you ready to experiment with using AI to take control of your workday? We all know that technology is constantly evolving and AI is no exception. In this essay collection, we're going to explore the potential of using AI to reduce your workload and increase your productivity. But keep in mind, this is an experiment, and we can't guarantee that it will work for everyone. We'll take you through the process of finding the right tasks to assign to AI, and explore the ethical considerations of reducing your work hours.

We present Learned Risk Metric Maps (LRMM) for real-time estimation of coherent risk metrics of high dimensional dynamical systems operating in unstructured, partially observed environments. LRMM models are simple to design and train -- requiring only procedural generation of obstacle sets, state and control sampling, and supervised training of a function approximator -- which makes them broadly applicable to arbitrary system dynamics and obstacle sets. In a parallel autonomy setting, we demonstrate the model's ability to rapidly infer collision probabilities of a fast-moving car-like robot driving recklessly in an obstructed environment; allowing the LRMM agent to intervene, take control of the vehicle, and avoid collisions. In this time-critical scenario, we show that LRMMs can evaluate risk metrics 20-100x times faster than alternative safety algorithms based on control barrier functions (CBFs) and Hamilton-Jacobi reachability (HJ-reach), leading to 5-15\% fewer obstacle collisions by the LRMM agent than CBFs and HJ-reach. This performance improvement comes in spite of the fact that the LRMM model only has access to local/partial observation of obstacles, whereas the CBF and HJ-reach agents are granted privileged/global information. We also show that our model can be equally well trained on a 12-dimensional quadrotor system operating in an obstructed indoor environment. The LRMM codebase is provided at https://github.com/mit-drl/pyrmm.

Artificial intelligence (AI) has the potential to revolutionize the way we drive and transport goods and people. Self-driving cars, also known as autonomous vehicles, are a type of vehicle that use AI and other advanced technologies to navigate roads and highways without the need for a human driver. There are several benefits to self-driving cars. For one, they have the potential to significantly reduce the number of accidents caused by human error. This could lead to fewer deaths and injuries on the road.

Are you tired of the same old 9–5 grind, struggling to make ends meet and looking for a way to take control of your financial future? Look no further -- Chat-GPT is here to change your life forever. But what is Chat-GPT, you might ask? Chat-GPT, or Generative Pre-trained Transformer, is a revolutionary artificial intelligence technology that allows users to have natural conversations with a virtual assistant. It has the ability to understand and respond to complex questions and requests, making it a valuable tool for businesses and individuals alike.