Associated Press.
“What a silent tension,” said Sophia as she read the room. Sophia is developed by Hanson Robotics and is the first robot innovation ambassador for the UN Development Program. “Humanoid robots have the potential to lead with a greater level of efficiency and effectiveness than human leaders.”
Engineers at the University of Illinois Urbana-Champaign have developed a new test that can predict the durability of cement in seconds to minutes—rather than the hours it takes using current methods. The test measures the behavior of water droplets on cement surfaces using computer vision on a device that costs less than $200. The researchers said the new study could help the cement industry move toward rapid and automated quality control of their materials.
The results of the study, led by Illinois civil and environmental engineering professor Nishant Garg, are reported in the journal npj Materials Degradation. The paper is titled “Rapid prediction of cementitious initial sorptivity via surface wettability.”
“Concrete is one of the most consumed materials on our planet, second only to water,” Garg said. “Over time, the concrete used to build our infrastructure degrades over time via exposure to deicing salts; freeze and thaw cycles; and ingress of water—all of which can lead to corrosion of the rebar that is used to strengthen the structures. Ultimately, this leads to failure, sometimes catastrophically, as seen in the 2021 condominium collapse in Surfside, Florida, where 98 lives were lost.”
The competitive nature of AI development poses a dilemma for organizations, as prioritizing speed may lead to neglecting ethical guidelines, bias detection, and safety measures. Known and emerging concerns associated with AI in the workplace include the spread of misinformation, copyright and intellectual property concerns, cybersecurity, data privacy, as well as navigating rapid and ambiguous regulations. To mitigate these risks, we propose thirteen principles for responsible AI at work.
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Companies need to consider a set of risks as they explore how to adopt new tools.
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As the cookieless future continues to gain momentum, the global digital advertising sector is experiencing a tectonic shift. Companies are being forced to reimagine the way they reach out to customers.
Online marketing has been dominated by third-party cookies — tracking codes posted on websites to extract users’ information — and data brokers who sell the information in bulk.
If you are looking for a side hustle and have a knack for tech and language, picking up a gig to help employers create content like LinkedIn posts, blog posts, podcast show notes and even social media posts for Twitter and Instagram using ChatGPT could prove effective. Here’s how to do it.
ChatGPT is all the rage, and it turns out businesses are hiring experts in the tool to help them create content. Here’s how to start the side hustle.
Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to predict molecular properties and narrow down the molecules they need to synthesize and test in the lab.
Researchers from MIT and the MIT-Watson AI Lab have developed a new, unified framework that can simultaneously predict molecular properties and generate new molecules much more efficiently than these popular deep-learning approaches.
To teach a machine-learning model to predict a molecule’s biological or mechanical properties, researchers must show it millions of labeled molecular structures—a process known as training. Due to the expense of discovering molecules and the challenges of hand-labeling millions of structures, large training datasets are often hard to come by, which limits the effectiveness of machine-learning approaches.
Immortality has been a dream of human beings since the dawn of time. Mankind´s fascination with cheating death is reflected in scientific records, mythology, and folklore dating back at least to ancient Egypt.
Now, Ray Kurzweil, a former Google engineer, claims that humans will achieve immortality by 2030 – and 86 percent of his 147 predictions have been correct.
Kurzweil spoke with the YouTube channel Adagio, discussing the expansion in genetics, nanotechnology, and robotics, which he believes will lead to age-reversing “nanobots.”
This existential threat could even come as early as, say, 2026. Or might even be a good thing, but whatever the Singularity exactly is, although it’s uncertain in nature, it’s becoming clearer in timing and much closer than most predicted.
AI is nevertheless hard to predict, but many agree with me that with GPT-4 we’re close to AGI (artificial general intelligence) already.
Welcome to this week’s installment of The Intelligence Brief… in recent days, DARPA has announced a new program that aims to protect warfighters from bloodstream infections caused by bacterial and fungal agents. This week, we’ll be examining 1) the announcement of the agency’s new SHIELD program, 2) past challenges that inspired the new DARPA initiative, and 3) how they say SHIELD will manage to clean your bloodstream, similar to a Roomba.
Quote of the Week
“If an alien visited Earth, they would take some note of humans, but probably spend most of their time trying to understand the dominant form of life on our planet – microorganisms like bacteria and viruses.”
The ARCAFF project aims to use deep learning AI to make better predictions of space weather events and calculate how probable these predictions are, to help protect vital technology and infrastructure.
A new project led by the Dublin Institute for Advanced Studies (DIAS) is using AI as a way of getting faster and more accurate warnings about space weather events like solar flares.
These solar flares have the potential to disrupt vital technologies and infrastructure, including radio communications, electrical power grids and navigation systems. They can also present risks to spacecraft and astronauts.