💡Has IBM Solved the AI Chip Problem?🤖 Meet the AI Mastermind Teaching Robots + Meta’s mind-reading tool.
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Eureka, The AI Mastermind Teaching RobotsRecent hype surrounds AI autonomous agents working round-the-clock. Nvidia Research's new agent, Eureka, powered by OpenAI's GPT-4, autonomously teaches robots complex skills, advancing robotics rapidly.
Through self-generating reward algorithms, Eureka has trained robots in nearly 30 tasks like rapid pen-spinning. Available for experimentation on Nvidia's Isaac Gym, Eureka, merging generative and reinforcement learning, outperforms human-engineered rewards in 83% of tasks, showcasing a 52% average improvement, indicating the potential for enhanced robotic control and realistic animations. Billionaires wanted it, but 54,578 everyday investors got it first…and profited, but you can too.
When precious assets come up for sale, it's typically the wealthiest who take home an amazing investment. But not always… One platform is taking on the billionaires at their own game, buying up and securitizing some of history’s most prized blue-chip artworks for its investors. In just the last few years, its investors have realized annualized net returns of 17.8%, 21.5%, 35%, and more from these opportunities. It's called Masterworks. Their nearly $1 billion collection includes works by greats like Banksy, Picasso, and Basquiat, all collectively owned by everyday investors. When Masterworks sells a painting – like the 16 it's already sold – investors reap their portion of the net proceeds.
Has IBM Solved the AI Chip Problem?IBM has developed an AI chip that can perform tasks faster and utilize less energy. NorthPole processor boosts AI performance by merging memory and processing, reducing external memory access and saving energy.
The chip, composed of 256 cores, excels in image recognition tasks, outperforming existing AI chips while consuming only one-fifth of their energy. Although its 224MB of RAM is inadequate for large language models, its design could benefit latency-sensitive applications like self-driving cars, representing a notable advancement in overcoming traditional computational bottlenecks. IBM will continue working and improving this chip which soon may be able to handle large language models appetite. Meta’s mind-reading tool is used to train their AIMeta has developed an AI system that decodes visual representations in the brain in real-time from magnetoencephalography (MEG) recordings, which are better and faster than fMRI. The system reconstructs images being perceived by capturing brain activity thousands of times per second.
While image reconstructions are imperfect, the system preserves high-level features like object categories. This research helps Meta understand how the brain forms image representations and provides a step towards brain-computer interfaces. Overall, the fast MEG decoding grants millisecond insight into the rise of complex visual representations in the brain, bringing Meta closer to developing AI that learns like humans. 📝 Cheat SheetAI for Education (By Educase)
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Masterworks Disclaimer: Past performance is not indicative of future returns, Investing involves risk. See disclosures masterworks.com/cd 🚀 Showcase Your Innovation in the Premier Tech and AI Newsletter (link) As a vanguard in the realm of technology and artificial intelligence, we pride ourselves in delivering cutting-edge insights, AI tools, and in-depth coverage of emerging technologies to over 55,000+ tech CEOs, managers, programmers, entrepreneurs, and enthusiasts. Our readers represent the brightest minds from industry giants such as Tesla, OpenAI, Samsung, IBM, NVIDIA, and countless others. Explore sponsorship possibilities and elevate your brand's presence in the world of tech and AI. Learn more about partnering with us. You’re a free subscriber to Yaro’s Newsletter. For the full experience, become a paying subscriber. Disclaimer: We do not give financial advice. Everything we share is the result of our research and our opinions. Please do your own research and make conscious decisions.
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Monday, October 23, 2023
💡Has IBM Solved the AI Chip Problem?
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