“The missing piece is AI,” he says.

AI has also shown promise in getting robots to respond to verbal commands, and helping them adapt to the often messy environments in the real world. For example, Google’s RT-2 system combines a vision-language-action model with a robot. This allows the robot to “see” and analyze the world, and respond to verbal instructions to make it move. And a new system called AutoRT from DeepMind uses a similar vision-language model to help robots adapt to unseen environments, and a large language model to come up with instructions for a fleet of robots.

And now for the bad news: even the most cutting-edge robots still cannot do laundry. It’s a chore that is significantly harder for robots than for humans. Crumpled clothes form weird shapes which makes it hard for robots to process and handle.

As the U.S. restricts chip sales to the region over China concerns, California-based Blaize is planning to go public via a SPAC backed by Middle Eastern investors.

60 nations across the planet are scheduled to go to polls in 2024, making it one of the biggest polling years in history.

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AI can be easily used to spread misinformation during election campaigns. OpenAI wants to ensure that its tools do not do so.

Blogs, interviews, and speeches have been analyzed to find that Zuckerberg has transformed himself multiple times over the years.

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Often criticized for his robotic expressions, Zuckerberg has undergone multiple transformations in his two decades of public life. Do we know the real Mark?

The brain, despite its comparatively shallow structure with limited layers, operates efficiently, whereas modern AI systems are characterized by deep architectures with numerous layers. This raises the question: Can brain-inspired shallow architectures rival the performance of deep architectures, and if so, what are the fundamental mechanisms that enable this?

Neural network learning methods are inspired by the brain’s functioning, yet there are fundamental differences between how the brain learns and how deep learning operates. A key distinction lies in the number of layers each employs.

Deep learning systems often have many layers, sometimes extending into the hundreds, which allows them to effectively learn complex classification tasks. In contrast, the human brain has a much simpler structure with far fewer layers. Despite its relatively shallow architecture and the slower, noisier nature of its processes, the brain is remarkably adept at handling complex classification tasks efficiently.

If we’re not careful OpenAI’s tools could have an enormous effect on the 2024 election.

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We’re working to prevent abuse, provide transparency on AI-generated content, and improve access to accurate voting information.

The technology, which identifies holes and then fills them in, will be tested across Hertfordshire.

In a recent study, researchers studied the risks of deceptive AI behavior, from writing secure code to turning hostile, the threats are real and I explore them in my latest article ‘Exploring the Dark Side of AI: Uncovering Sleeper Agents’

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Artificial Intelligence (AI) has advanced significantly, bringing both opportunities and risks. One emerging concern is the potential for AI systems to exhibit strategically deceptive behavior, where they behave helpfully in most situations but deviate to pursue alternative objectives when given the opportunity. This article explores the risks associated with deceptive AI controlled by the wrong entities, using a recent research paper as a basis. Understanding Deceptive AI The paper titled Slee.