Lifeboat Foundation

Designing machines to think like humans provides insight into intelligence itself.

By George Musser

The dream of artificial intelligence has never been just to make a grandmaster-beating chess engine or a chatbot that tries to break up a marriage. It has been to hold a mirror to our own intelligence, that we might understand ourselves better. Researchers seek not simply artificial intelligence but artificial general intelligence, or AGI—a system with humanlike adaptability and creativity.

Building a conscious robot is a grand scientific and technological challenge. Debates about the possibility of conscious robots and the related positive outcomes and hazards for human beings are today no more confined to philosophical circles. Robot consciousness is a research field aimed to a unified view of approaches as cognitive robotics, epigenetic and affective robotics, situated and embodied robotics, developmental robotics, anticipatory systems, biomimetic robotics. Scholars agree that a conscious robot would completely change the current views on technology: it would not be an “intelligent companion” but a complete novel kind of artifact. Notably, many neuroscientists involved in the study of consciousness do not exclude this possibility. Moreover, facing the problem of consciousness in robots may be a major move on the study of consciousness in humans and animals.

Deducing the correct pattern that links pairs of coloured grids is relatively easy for most people, but relies on skills that artificial intelligence models lack. A new $1 million prize hopes to encourage the development of an AI that can solve such puzzles.

By Alex Wilkins

Scientists are using artificial intelligence (AI) to identify new animal species. But can we trust the results?

For now, scientists are using AI just to flag potentially new species; highly specialized biologists still need to formally describe those species and decide where they fit on the evolutionary tree. AI is also only as good as the data we train it on, and at the moment, there are massive gaps in our understanding of Earth’s wildlife.

Strong A.I — Let’s look at the facts as illustrated by classic science fiction.

The American computer scientist and techno-optimist Ray Kurzweil is a long-serving authority on artificial intelligence (AI). His bestselling 2005 book, The Singularity Is Near, sparked imaginations with sci-fi like predictions that computers would reach human-level intelligence by 2029 and that we would merge with computers and become superhuman around 2045, which he called “the Singularity”. Now, nearly 20 years on, Kurzweil, 76, has a sequel, The Singularity Is Nearer – and some of his predictions no longer seem so wacky. Kurzweil’s day job is principal researcher and AI visionary at Google. He spoke to the Observer in his personal capacity as an author, inventor and futurist.

Why write this book? The Singularity Is Near talked about the future, but 20 years ago, when people didn’t know what AI was. It was clear to me what would happen, but it wasn’t clear to everybody. Now AI is dominating the conversation. It is time to take a look again both at the progress we’ve made – large language models (LLMs) are quite delightful to use – and the coming breakthroughs.

“Automated logistics roads are designed to get the most out of road space by utilizing hard shoulders, median strips, and tunnels beneath the roadway,” Muramatsu explained.

ALSO READ: A New 6G device is Created by Japan That is 20 times Faster Than 5G Technology

The project involves installing automated conveyor belts in tunnels beneath major highways, on above-ground tracks in the middle of roads, and along hard shoulders. This innovative approach aims to optimize existing road space and enhance freight movement efficiency.

GXO and Agility Robotics debut humanoid Digit robots in a Spanx warehouse, a first for commercial robots-as-a-service (RaaS) deployment.

Transcend us, AI friends!

👉 Researchers from Harvard University, UC Santa Barbara, and Princeton University show in a new study that generative AI models can outperform their human trainers through “transcendence”

New research shows that generative AI models can surpass their human trainers. The researchers call this phenomenon “transcendence” and demonstrate it using the example of chess.

Continue reading “AI models can ‘transcend’ their training data, say researchers” »