Is generative AI the beginning of the end for humans… or the end of the beginning?
And, did you know generative AI has been around since 1972?
Continue reading “Chat GPT is NOT generative AI: Intel scientist” »
Summary: Humans and computers can interact via multiple modes and channels to respectively gain wisdom and deepen intelligence.
Source: Intelligent Computing.
Deyi Li from the Chinese Association for Artificial Intelligence believes that humans and machines have a mutually beneficial relationship.
Summary: Using a highly versatile form of CRISPR gene editing, researchers successfully restored vision in mice with retinitis pigmentosa.
Source: Rockefeller University Press.
Researchers in China have successfully restored the vision of mice with retinitis pigmentosa, one of the major causes of blindness in humans.
Progress in biomimetics allows for the fabrication of man-made materials and surfaces with properties similar to biological ones. These advancements enable the development of a new generation of building materials for architecture that have remarkable properties typically unachievable with a traditional approach.
Summary: Our native language may affect the way in which our brains are wired and underlie the way we think, a new study reports. Using neuroimaging to analyze neural connectivity in native German and native Arabic speakers, researchers found stronger connectivity between the right and left hemispheres in Arabic speakers, and stronger connectivity in the left hemisphere language area in German speakers.
Source: Max Planck Institute.
Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig have found evidence that the language we speak shapes the connectivity in our brains that may underlie the way we think.
Tens of thousands of living brain cells have been used to build a simple computer that can recognise patterns of light and electricity. It could eventually be used in robotics.
A team of physicists and material scientists at the University of Colorado has developed a way to better insulate double-paned glass used for windows by adding a transparent aerogel. In their paper published in the journal Nature Energy the group describes how their aerogel is made and how much of a boost in energy efficiency can be expected from windows using the material. Nature Energy has also published a Research Briefing in the same journal issue that outlines the work done by the team.
Since most homeowners prefer to have windows that allow them to see outside, heat loss is inevitable. Over the past several decades, heat loss from windows has been improved by adding a second pane of glass —the two panes are typically separated by a gap of insulating air. Still, such windows do not provide nearly the same degree of insulation as insulated walls. In this new approach, the team in Colorado has come up with a way to improve the insulation properties of double-paned glass.
To make the aerogel (a gel with pockets of air in it), the research team soaked nanofibers of cellulose extracted from wood in water. Next, the wood nanofibers were removed and were then dunked in an ethanol solution. Once saturated, the nanofibers were heated in a pressurized oven—this forced the ethanol pockets to be replaced with air. Next, the nanofibers, which were transparent, were coated with a water-repellent material to prevent condensation when situated between panes of glass.
Researchers have found that an activated form of the hunger hormone ghrelin can help people with heart failure by increasing the heart’s pump capacity.
8 years of cost reduction in 5 weeks: how Stanford’s Alpaca model changes everything, including the economics of OpenAI and GPT 4. The breakthrough, using self-instruct, has big implications for Apple’s secret large language model, Baidu’s ErnieBot, Amazon’s attempts and even governmental efforts, like the newly announced BritGPT.
I will go through how Stanford put the model together, why it costs so little, and demonstrate in action versus Chatgpt and GPT 4. And what are the implications of short-circuiting human annotation like this? With analysis of a tweet by Eliezer Yudkowsky, I delve into the workings of the model and the questions it rises.
