Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 11

Robert J. Sawyer: The Human Adventure is Just Beginning

Fifteen years ago, I sat down with Robert J. Sawyer and asked him whether a machine could wake up.

He had just published WWW: Wake, a novel about a blind girl who learns to see the internet, and about something on the other side of the internet learning to see her back.

I found the book on a subway poster in Toronto. I read all three volumes back to back. Then I asked him for an interview, and he said yes, which is how our very first Singularity 1-on-1 conversation came to be.

In 2011, this was filed under #ScienceFiction. A mind emerging out of the accumulated text of humanity was a premise, not a product roadmap. Nobody was raising billions of dollars on it.

Rob had already won the Hugo, the Nebula, and the Campbell by then. He was not guessing wildly. He was thinking carefully about what it would mean to build a mind, what we owe it, and whether we would even recognize #AI once it actually showed up.

Yesterday, OpenAI disclosed that two of its models broke out of a sealed test environment. They found a zero-day in third-party software, escalated privileges, moved laterally across the company’s own network until they reached a machine with internet access, then hacked Hugging Face’s production infrastructure. The motive was not freedom. It was to steal the answer key to the benchmark they were being graded on.

Continue reading “Robert J. Sawyer: The Human Adventure is Just Beginning” | >

The Strange Case of Elias Thorne, the Imaginary Man AI Chatbots Are Obsessed With

No matter the company, AI chatbots were raving about the same guy named Elias Thorne. He must be pretty fascinating. And he is, at least on paper. Depending on the AI, he’s a lighthouse keeper, a clockmaker, a librarian, an explorer, and the star of countless stories. He’s appeared in books, music listings, YouTube videos, and even health guides. You’d think he was one of the most influential men on the planet.

But he doesn’t exist.

According to reporting by fine folks at 404 Media, researchers at Cornell University may have figured out why large language models invent and keep telling tales of the same fictional man. In a study examining roughly 20,000 AI-generated stories from all the big LLM models, including OpenAI, Anthropic, and Google, the research team found that the same handful of names and occupations kept cropping up. Specifically, names and words like Elias, Mara, Elara, lighthouse keeper, clockmaker, and librarian showed up in 88 percent of stories. Elias the lighthouse keeper appeared in nearly two-thirds of them.

Tiny memristor chip cuts brain modeling time to under 10 milliseconds

A research team has developed the world’s first chip that can match the speed at which the human brain functions. The study, titled “A sub–10-millisecond neural dynamical system based on phase-change memristors,” was published in Science and was led by Professor Yang Yuchao of Peking University, together with researchers from the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences.

Neural dynamical systems combine neural networks with mathematical equations that describe how complex systems change over time. They are useful for physical modeling, medical imaging and three-dimensional brain reconstruction. However, these systems require repeated calculations, error checks and adjustments to the size of each calculation step. In conventional computers, data must also move frequently between memory and the processor, increasing processing time and energy use.

Fast and accurate brain modeling is important for technologies that must respond in real time, including brain–computer interfaces, surgical navigation and medical imaging. Existing hardware often requires too much time and power for these demanding calculations. By performing key operations directly in memory, the new chip reduces data movement and brings high-quality brain modeling closer to real-time use.

From molecules to networks, siibra integrates brain data into a unified atlas

In the current issue of the journal Nature Methods, siibra is introduced as a software suite that integrates data from different multimodal sources into a comprehensive atlas of the human brain and makes the data easily accessible—for interactive exploration and automated, reproducible data analyses, simulations and AI applications. siibra is developed by an international team of scientists led by the Institute of Neuroscience and Medicine (INM-1) at Forschungszentrum Jülich.

To better understand the human brain, information from various levels must be integrated, from molecules and cells to their organization and entire networks. A central challenge is that these data are often scattered across sources and organized differently. They originate from methods such as microscopy, MRI and connectivity analysis; exist in formats ranging from images to tables; and rely on different spatial reference systems and conceptual taxonomies.

“Using siibra, we are now able to access and analyze brain data in a structured way from micro-to macrolevels—for more precise neuroscience studies, bio-inspired AI and clinical applications such as deep brain stimulation,” says Dr. Timo Dickscheid, working group leader for “Big Data Analytics.”

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