Some modern image generators rely on the principles of diffusion to create images. Alternatives based on the process behind the distribution of charged particles may yield even better results.
Category: robotics/AI – Page 688
Aiming to be first in the world to have the most advanced forms of artificial intelligence while also maintaining control over more than a billion people, elite Chinese scientists and their government have turned to something new, and very old, for inspiration—the human brain.
Equipped with surveillance and visual processing capabilities modelled on human vision, the new “brain” will be more effective, less energy hungry, and will “improve governance,” its developers say. “We call it bionic retina computing,” Gao Wen, a leading artificial intelligence researcher, wrote in the paper “City Brain: Challenges and Solution.”
Have you ever talked to someone who is “into consciousness?” How did that conversation go? Did they make a vague gesture in the air with both hands? Did they reference the Tao Te Ching or Jean-Paul Sartre? Did they say that, actually, there’s nothing scientists can be sure about, and that reality is only as real as we make it out to be?
The fuzziness of consciousness, its imprecision, has made its study anathema in the natural sciences. At least until recently, the project was largely left to philosophers, who often were only marginally better than others at clarifying their object of study. Hod Lipson, a roboticist at Columbia University, said that some people in his field referred to consciousness as “the C-word.” Grace Lindsay, a neuroscientist at New York University, said, “There was this idea that you can’t study consciousness until you have tenure.”
Nonetheless, a few weeks ago, a group of philosophers, neuroscientists and computer scientists, Dr. Lindsay among them, proposed a rubric with which to determine whether an A.I. system like ChatGPT could be considered conscious. The report, which surveys what Dr. Lindsay calls the “brand-new” science of consciousness, pulls together elements from a half-dozen nascent empirical theories and proposes a list of measurable qualities that might suggest the presence of some presence in a machine.
At Science4Seniors we strive to take rigorous research published in Scientific Journals and make the core information accessible to all. If you want to support us please like and follow us on Facebook. In recent years, the intersection of medical science and technology has unfurled fascinating possibilities, especially in diagnostics. Among the many marvels we’ve been introduced to, medical artificial intelligence (AI) is reshaping how we detect and diagnose a plethora of health conditions. One area that stands out significantly in this transformation is the potential of AI in the analysis of retinal images.
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In this intriguing discussion, philosopher David Chalmers and his fellow experts explore the concepts of consciousness, intelligence, and the possibility that we are living in a simulated universe. They delve into the works of Douglas Hofstadter, the idea of an intelligence explosion, and the challenge of aligning artificial general intelligence with human goals. The conversation also touches on the limitations of intelligence, the relationship between complexity and consciousness, and the potential motivations behind simulating a universe.
Table of Contents:
[00:00:00] Introduction to David Chalmers and his work.
[00:01:17] The influence of Douglas Hofstadter on AI and philosophy.
[00:09:03] The concept of the intelligence explosion.
[00:15:30] Aligning artificial general intelligence with human goals.
[00:17:49] Consciousness, introspection, and the meta problem.
[00:24:19] The relationship between complexity and consciousness.
[00:29:43] What makes a simulation interesting?
Note: this was recorded in April 2022. We will release full version on audio podcast soon.
In response to the increasing demand for medical services amid labor shortages and a rapidly aging population, Shanghai-based Fourier Intelligence is developing an innovative humanoid robot. The GR-1, as it is called, promises to transform healthcare facilities and offer vital assistance to the elderly.
Like many countries, China is confronting the challenge of an aging population. The number of individuals aged 60 and over is projected to rise from 280 million to over 400 million by 2035, according to estimates from the country’s National Health Commission. That’s more than the entire population of the United States projected for that year.
It’s not the sheer number of the elderly that is a problem, but rather their share of the overall population. By 2040, nearly 30% of China’s population will be 60 or older.
Numerous natural language processing (NLP) applications have benefited greatly from using large language models (LLMs). While LLMs have improved in performance and gained additional capabilities due to being scaled, they still have a problem with “hallucinating” or producing information inconsistent with the real-world facts detected during pre-training. This represents a significant barrier to adoption for high-stakes applications (such as those found in clinical and legal settings), where the generation of trustworthy text is essential.
The maximum likelihood language modeling target, which seeks to minimize the forward KL divergence between the data and model distributions, may be to blame for LMs’ hallucinations. However, this is far from certain. The LM may assign a non-zero probability to phrases that are not fully consistent with the knowledge encoded in the training data if this goal is pursued.
From the perspective of the interpretability of the model, studies have shown that the earlier layers of transformer LMs encode “lower level” information (such as part-of-speech tags). In contrast, the later levels encode more “semantic” information.
Intel is trying to keep up with the exploding demand for new computing horsepower.
In what is being seen as a shift from silicon, Intel announced Monday their progress in commercializing glass substrates toward the end of the decade. The company said that glass substrates are an improvement in design, allowing more transistors to be connected in a package and will help overcome the limitations of organic materials.
As the world advances to incorporate developments in data-intensive workloads in artificial intelligence, glass substrates, in comparison to organic substrates,… More.
Intel.
The study will take six years and is looking for people with quadriplegia to test the whole Neuralink system.
A few months after getting FDA approval for human trials, Neuralink is looking for its first test subjects. The six-year initial trial, which the Elon Musk-owned company is calling “the PRIME Study,” is intended to test Neuralink tech designed to help those with paralysis control devices. The company is looking for people with quadriplegia due to vertical spinal cord injury or ALS who are over the age of 22 and have a “consistent and reliable caregiver” to be part of the study.
The PRIME Study (which apparently stands for Precise Robotically Implanted Brain-Computer Interface, even… More.
Neuralink plans for the study to take six years and wants to test every part of its system — including the robot used to implant it.
With just a few minutes of sample video and $1,000, brands never have to stop selling their products.
Scroll through the livestreaming videos at 4 a.m. on Taobao, China’s most popular e-commerce platform, and you’ll find it weirdly busy. While most people are fast asleep, there are still many diligent streamers presenting products to the cameras and offering discounts in the wee hours.
But if you take a closer look, you may notice that many of these livestream influencers seem slightly robotic. The movement of their lips largely matches what they are saying, but there are always moments when it looks unnatural.