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Tesla’s potential market size for its humanoid robot, Optimus, presents a massive opportunity worth trillions of dollars, far surpassing the impact of their electric vehicles.

Questions to inspire discussion.

Continue reading “Tesla’s Optimus: $30 Trillion Market Potential” »

If you think Tesla’s next generation bot, TeslaBot, looks good for no reason, then think again! Dr. Scott Walter and I go into the reasons that the way the new Optimus robot looks matter so much to the way it functions—and it’s pretty cool! Plus, Scott rants about the fraudulent copyright claims Univision laid on all TeslaBot videos!

The digital twin system created by Zhang, Ji, and their colleagues creates a virtual replica of a scene in which a human and robot agent are collaborating.

Robotics systems have already been introduced in numerous real-world settings, including some industrial and manufacturing facilities. In these facilities, robots can assist human assembly line and warehouse workers, assembling some parts of products with high precision and then handing them to human agents tasked with performing additional actions.

In recent years, roboticists and computer scientists have been trying to develop increasingly advanced systems that could enhance these interactions between robots and humans in industrial settings. Some proposed solutions rely on so-called ‘digital twin’ systems, virtual models designed to accurately reproduce a physical object, such as specific products or components that are being manufactured.

Continue reading “A digital twin system that could enhance collaborative human-robot product assembly” »

We’ve long assumed that aliens will be like us, but there’s every reason to think they are instead a form of unfathomable AI, says the UK astronomer royal Lord Martin Rees.

Artificial intelligence researchers claim to have made the world’s first genuine scientific discovery using a large language model (LLM), which is behind ChatGPT and similar programs. This signals a major breakthrough.

The discovery was made by Google DeepMind, an AI research laboratory where scientists are investigating whether LLMs can do more than just repackage information learned in training and actually generate new insights.

Continue reading “Google researchers make AI tech solve math puzzles ‘beyond human knowledge’” »

Tesla has unveiled Gen 2 of it’s Optimus Robot… and WOW, the progress in the past year has been incredible. Tesla is well on their way to commercializing a humanoid robot later this decade. This represents the biggest change in Tesla’s addressable market ever, as the potential sales from a humanoid robot to replace manual labor could be $25T. For long-term Tesla investors this is a must watch project. People thought Elon Musk was crazy when he told the world about this AI project… but it’s getting closer to reality by the day. What do you think? Are you going to buy an Optimus robot? Why? Tesla Optimus Announcement on X:

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Unlike us, an algorithm selecting a most-likely next word or a program calculating the best move in a game of chess isn’t choosing and can’t feel regret.

A key aspect of how we think separates us from even the most advanced AI.

“The human brain has 100 billion neurons, each neuron connected to 10,000 other neurons. Sitting on your shoulders is the most complicated object in the known universe.” — Michio Kaku, PhD.

Since most examples of brain-inspired silicon chips are based on digital electronic principles, their capacity to fully imitate brain function is limited. Self-organizing brain organoids connected to microelectrode arrays (MEAs) can be changed in function to create neural networks. These networks, called organoid neural networks (ONNs), show the capacity for unsupervised learning, which is what artificial intelligence (AI) is based on. These mini-organs, when connected to the right hardware, can even be trained to recognize speech.

This brain-inspired computing hardware, or “Brainoware,” could overcome existing shortcomings in AI technologies, providing natural solutions to challenges regarding time and energy consumption and heat production of current AI hardware. These ONNs may also have the necessary complexity and diversity to mimic a human brain, which could inspire the development of more sophisticated and human-like AI systems.