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A new AI system will enable multiple robots to recognize people. A Japanese company has developed an AI system that makes it possible for multiple moving robots to identify people whose images have been uploaded in advance.

This new ability was examined during a pilot test in which images sent from robots in various locations within an event space were analyzed and compiled in the cloud using an AI engine. By utilizing the AI system, robots could identify specific people from camera images sent by various types of robots and to perform cloud-based confirmation. According to eenewseurope.com, The test also demonstrated that people’s locations could be pinpointed by using the positions of the robots.

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ChatGPT from Open AI has shocked many users as it is able to complete programming tasks from natural language descriptions, create legal contracts, automate tasks, translate languages, write articles, answer questions, make video games, carry out customer service tasks, and much more — all at the level of human intelligence with 99% percent of its outputs. PAL Robotics has taught its humanoid AI robots to use objects in the environment to avoid falling when losing balance.

AI News Timestamps:
0:00 Why OpenAI’s ChatGPT Has People Panicking.
3:29 New Humanoid AI Robots Technology.
8:20 Coursera Deep Learning AI

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GUEST BIO:
Noam Brown is a research scientist at FAIR, Meta AI, co-creator of AI that achieved superhuman level performance in games of No-Limit Texas Hold’em and Diplomacy.

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We evaluate davinci-003 across a range of classification, summarization, and generation tasks. Using Scale Spellbook, the platform for large language model apps, we show where davinci-003 significantly outperforms the prior version and where it still has room to improve.

Character is a full stack Artificial General Intelligence (AGI) company.

What if you could create your own AI, and it was always available to help you with anything?

Imagine everything it could do for you, from being your own personal teacher, assistant or even friend. Two months after launching in September, our beta generates 1 billion words per day. Get a glimpse of the future at character.ai.

Researchers at Worcester Polytechnic Institute recently created OmniWheg, a robotic system that can adapt its configuration while navigating its surrounding environment, seamlessly changing from a wheeled to a legged robot. This robot, introduced in an IEEE IROS 2022 paper, pre-published on arXiv, is based on an updated version of the so-called “whegs,” a series of mechanisms design to transform a robot’s wheels or wings into legs.

“Quadruped and biped robots have been growing in popularity, and the reason for that might be the search for ‘anthropomorphization’ that the general audience commonly engages in,” Prof. Andre Rosendo, one of the researchers who developed the robot, told TechXplore. “While ‘being capable of going everywhere we go’ sounds like an exciting appeal, the energetic cost of legs is very high. We humans have legs because that is what evolution gave us, but we wouldn’t dare to create a ‘legged car,’ as we know that this ride wouldn’t be as comfortable or energy efficient as a wheeled car ride.”

Continue reading “A transformable robot with an omnidirectional wheel-leg” »

Researchers at Tohoku University, the University of Messina, and the University of California, Santa Barbara (UCSB) have developed a scaled-up version of a probabilistic computer (p-computer) with stochastic spintronic devices that is suitable for hard computational problems like combinatorial optimization and machine learning.

Moore’s law predicts that computers get faster every two years because of the evolution of semiconductor chips. While this is what has historically happened, the continued evolution is starting to lag. The revolutions in machine learning and artificial intelligence means much higher computational ability is required. Quantum computing is one way of meeting these challenges, but significant hurdles to the practical realization of scalable quantum computers remain.

A p-computer harnesses naturally stochastic building blocks called probabilistic bits (p-bits). Unlike bits in traditional computers, p-bits oscillate between states. A p-computer can operate at room-temperature and acts as a domain-specific computer for a wide variety of applications in machine learning and artificial intelligence. Just like quantum computers try to solve inherently quantum problems in quantum chemistry, p-computers attempt to tackle probabilistic algorithms, widely used for complicated computational problems in combinatorial optimization and sampling.

Researchers have used a quantum processor to make microwave photons uncharacteristically sticky. They coaxed them to clump together into bound states, then found that these photon clusters survived in a regime where they were expected to dissolve into their usual, solitary states. The discovery was first made on a quantum processor, marking the growing role that these platforms are playing in studying quantum dynamics.

Photons—quantum packets of electromagnetic radiation like light or microwaves—typically don’t interact with one another. Two crossed flashlight beams, for example, pass through one another undisturbed. But in an array of superconducting qubits, microwave photons can be made to interact.

In “Formation of robust bound states of interacting photons,” published today in Nature, researchers at Google Quantum AI describe how they engineered this unusual situation. They studied a ring of 24 superconducting qubits that could host microwave photons. By applying quantum gates to pairs of neighboring qubits, photons could travel around by hopping between neighboring sites and interacting with nearby photons.

Good Morning, 2033 — A Sci-Fi Short Film.

What will your average morning look like in 2033? And who hacked us?

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