Lifeboat Foundation

The breakthrough blends biological and mechanical elements, sparking ethical debates.

Sam Altman and Arianna Huffington told me that they believe generative AI can help millions of suffering people. I’m not so sure.

Researchers have devised a new model to predict human behavior taking into account our ‘sub-optimal’ decision-making.

It’s a mild bump from 6GB, but it is still good for consumers, at least.

WITH THE IDEA OF CONSCIOUS DIGITAL MINDS on the horizon, it could be that humans are the proverbial frog in a boiling pot of water, and it’s only been a few years since things have started to feel a bit steamy. But as Bostrom argues in his book, this might be a boiling pot we don’t want to jump out of.

“We need to rethink what it means to be human in such a world where AI has taken care of all the practical tasks and we have a kind of a solved world,” Bostrom says. “You might have a much more radical form of automation … where maybe working for money at all becomes completely unnecessary because AI and robots can do everything better than we can do.”

Continue reading “Humans Could Forge a Hybrid Consciousness by Merging With Artificial Life, Oxford Scientists Say” »

Xpeng looks to be following in Tesla’s footsteps for its upcoming vehicle release.

Elon Musk teased the next iteration of Tesla’s humanoid robot Optimus 2.0 on X recently.

“The new Optimus design, which will be complete later this year, is something special,” Musk replied to an X post.

In June, Tesla shared a few updates about Optimus and the milestones the humanoid robot has reached over the past year. According to Tesla, Optimus has already undergone three major design revisions. The humanoid robot’s hand were revised four times in the last two years.

The performance of artificial intelligence (AI) tools, including large computational models for natural language processing (NLP) and computer vision algorithms, has been rapidly improving over the past decades. One reason for this is that datasets to train these algorithms have exponentially grown, collecting hundreds of thousands of images and texts often collected from the internet.

Training data for robot control and planning algorithms, on the other hand, remains far less abundant, in part because acquiring it is not as straightforward. Some computer scientists have thus been trying to create larger datasets and platforms that could be used to train computational models for a wide range of robotics applications.

In a recent paper, pre-published on the server arXiv and set to be presented at the Robotics: Science and Systems 2024 conference, researchers at the University of Texas at Austin and NVIDIA Research introduced one of these platforms, called RoboCasa.

Quantum computing, which uses the laws of quantum mechanics, can solve pressing problems in a broad range of fields, from medicine to machine learning, that are too complex for classical computers.