Industries can rethink how work gets done, raising the bar for productivity and workplace safety. Unitree just dropped its latest creation, the R1 humanoid robot, and people are talking. At only 5,900, it's the most affordable bipedal robot we've seen so far. The low price has taken the tech world by surprise and kicked off a wave of excitement. Sign up for my FREE CyberGuy Report Get my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox.

"The model is innately more capable," Sundar Pichai, the CEO of Google and its parent company Alphabet, told MIT Technology Review. AI is a profound platform shift, bigger than web or mobile. And so it represents a big step for us." Google DeepMind claims that Gemini outmatches GPT-4 on 30 out of 32 standard measures of performance. And yet the margins between them are thin. What Google DeepMind has done is pull AI's best current capabilities into one powerful package. To judge from demos, it does many things very well--but few things that we haven't seen before. For all the buzz about the next big thing, Gemini could be a sign that we've reached peak AI hype. Chirag Shah, a professor at the University of Washington who specializes in online search, compares the launch to Apple's introduction of a new iPhone every year. "Maybe we just have risen to a different threshold now, where this doesn't impress us as much because we've just seen so much," he says. Like GPT-4, Gemini is multimodal, meaning it is trained to handle multiple kinds of input: text, images, audio. It can combine these different formats to answer questions about everything from household chores to college math to economics. In a demo for journalists yesterday, Google showed Gemini's ability to take an existing screenshot of a chart, analyze hundreds of pages of research with new data, and then update the chart with that new information. In another example, Gemini is shown pictures of an omelet cooking in a pan and asked (using speech, not text) if the omelet is cooked yet. "It's not ready because the eggs are still runny," it replies. Most people will have to wait for the full experience, however. The version launched today is a back end to Bard, Google's text-based search chatbot, which the company says will give it more advanced reasoning, planning, and understanding capabilities. Gemini's full release will be staggered over the coming months. The new Gemini-boosted Bard will initially be available in English in more than 170 countries, not including the EU and the UK. This is to let the company "engage" with local regulators, says Sissie Hsiao, a Google vice president in charge of Bard. Gemini also comes in three sizes: Ultra, Pro and Nano. Ultra is the full-powered version; Pro and Nano are tailored to applications that run with more limited computing resources. Nano is designed to run on devices, such as Google's new Pixel phones. Developers and businesses will be able to access Gemini Pro starting December 13. Gemini Ultra, the most powerful model, will be available "early next year" following "extensive trust and safety checks," Google executives told reporters on a press call. "I think of it as the Gemini era of models," Pichai told us. "This is how Google DeepMind is going to build and make progress on AI.

Are AI Assistants the Next Big Step for Autonomous Vehicles? The concept of self driving cars has been around for a long time, but in spite of the fact that this is the case these types of autonomous vehicles have faced a few hurdles when it comes to being implemented in real world settings. The rise of ChatGPT has made a lot of people wonder how AI assistants could factor into the equation, with many stating that they could make these cars safer than might have been the case otherwise. The trend of integrating various functions into the central display is already ongoing. With all of that having been said and now out of the way, it is important to note that AI assistants could be added to the mix as well.

Scientists have developed a theory that can explain how flying insects determine the gravity direction without using accelerometers. It also forms a substantial step in the creation of tiny, autonomous drones. Scientists have discovered a novel manner for flying drones and insects to estimate the gravity direction. Whereas drones typically use accelerometers to this end, the way in which flying insects do this has until now been shrouded in mystery, since they lack a specific sense for acceleration. In an article published in Nature, scientists from TU Delft and Aix Marseille Université / CNRS in France have shown that drones can estimate the gravity direction by combining visual motion sensing with a model of how they move.

A research group from the Graduate School of Informatics, Nagoya University, has taken a big step towards creating a neural network with metamemory through a computer-based evolution experiment. Their paper appears in Scientific Reports. In recent years, there has been rapid progress in designing artificial intelligence technology using neural networks that imitate brain circuits. One goal of this field of research is understanding the evolution of metamemory to use it to create artificial intelligence with a human-like mind. Metamemory is the process by which we ask ourselves whether we remember what we had for dinner yesterday and then use that memory to decide whether to eat something different tonight.

A research group from the Graduate School of Informatics, Nagoya University, has taken a big step towards creating a neural network with metamemory through a computer-based evolution experiment. In recent years, there has been rapid progress in designing artificial intelligence technology using neural networks that imitate brain circuits. One goal of this field of research is understanding the evolution of metamemory to use it to create artificial intelligence with a human-like mind. Metamemory is the process by which we ask ourselves whether we remember what we had for dinner yesterday and then use that memory to decide whether to eat something different tonight. While this may seem like a simple question, answering it involves a complex process.

I explain Artificial Intelligence terms and news to non-experts. BlobGAN allows for unreal manipulation of images, made super easily controlling simple blobs. All these small blobs represent an object, and you can move them around or make them bigger, smaller, or even remove them, and it will have the same effect on the object it represents in the image. As the authors shared in their results, you can even create novel images by duplicating blobs, creating unseen images in the dataset like a room with two ceiling fans! Correct me if I'm wrong, but I believe it is one of, if not the first, paper to make the modification of images as simple as moving blobs around and allowing for edits that were unseen in the training dataset.

This is the web version of Eye on A.I., Fortune's weekly newsletter covering artificial intelligence and business. To get it delivered weekly to your in-box, sign up here. In January 2020, in a Fortune magazine cover story, I chronicled the corporate race for artificial general intelligence, a kind of human-like or even superhuman A.I. that is the staple of science fiction. The pursuit of AGI, as it's more commonly called, has led to many of the machine learning innovations that underpin the current A.I. boom. But that boom is centered around narrow A.I--software that can perform one, specific task well.

All the sessions from Transform 2021 are available on-demand now. Thanks to AI advancements and applications, edge computing is already seeing widespread interest from industries ranging from manufacturing to healthcare and retail. Leveraging the growing power and ubiquity of CPUs and neural processing units, edge AI can process growing haystacks of data right where they're being created, finding their needles quickly for local or remote processing. Edge AI is an enabler for early networked autonomous cars -- instantly recognizing and sharing details on accidents, weather conditions, and traffic from vehicle sensors and smart infrastructures in real-time. Similarly, edge AI has empowered wearables to actively monitor seniors for chronic health conditions, alerting remote caregivers within seconds of detecting abnormalities in their biometric data. It's clear that edge AI has the ability to open up a whole new world of insights and opportunities across multiple industries, but connecting the distributed data processors to usefully aggregate their discoveries is a higher-level task.

This makes data integration expensive and reduces the ability of companies, factories, cities, etc., to build optimal machine learning models that can …