GARMI will also serve meals, open a bottle of water and place emergency calls.
Robots are gradually making their way into a variety of industries, from restaurant service to healthcare. Scientists have been working hard to rapidly expand robot capabilities, and it is clear that robotics will shape our daily lives in the near future.
Now, it’s time to meet “GARMI”. This white-colored humanoid which has come to the aid of doctors, nurses, and elderly citizens in need.
CHRISTOF STACHE — AFP/Getty Images.
Medicine and elderly healthcare could benefit the most from robotics advancements.
Using AI, Ting Xu and her colleagues designed polymer mixtures that mimic the natural proteins in biological fluids. The technique could improve the design of biocompatible materials.
Last week saw a plethora of new advances in AI, including the much-anticipated release of GPT-4.
Rarely, if ever, has more progress been witnessed in AI than what we are currently seeing. This is clearly an exceptional time for the field, with much hype and speculation around what the near future may bring.
If it’s always been your dream to have the ability to live forever, you may be in luck as scientists believe we are just seven years away from achieving immortality. Futurist and computer scientist Ray Kurzweil has made predictions on when the human race will be able to live forever and when artificial intelligence (AI) will reach the singularity, and he believes it could be possible as early as 2030.
One of the oldest tools in computational physics — a 200-year-old mathematical technique known as Fourier analysis — can reveal crucial information about how a form of artificial intelligence called a deep neural network learns to perform tasks involving complex physics like climate and turbulence modeling, according to a new study.
The discovery by mechanical engineering researchers at Rice University is described in an open-access study published in the journal PNAS Nexus, a sister publication of the Proceedings of the National Academy of Sciences.
“This is the first rigorous framework to explain and guide the use of deep neural networks for complex dynamical systems such as climate,” said study corresponding author Pedram Hassanzadeh. “It could substantially accelerate the use of scientific deep learning in climate science, and lead to much more reliable climate change projections.”
In 1997, IBM’s Deep Blue defeated the reigning world champion chess player, Garry Kasparov. In 2016, Google’s AlphaGo defeated one of the worlds top Go players in a five-game match. Today, OpenAI released GPT-4, which it claims beats 90% of humans who take the bar to become a lawyer, and 99% of students who compete in the Biology Olympiad, an international competition that tests the knowledge and skills of high school students in the field of biology.
In fact, it scores in the top ranks for at least 34 different tests of ability in fields as diverse as macroeconomics, writing, math, and — yes — vinology.
“GPT-4 exhibits human-level performance on the majority of these professional and academic exams,” says OpenAI.
Studying Our Ocean’s History To Understanding Its Future — Dr. Emily Osborne, PhD, Ocean Chemistry & Ecosystems Division, National Oceanic and Atmospheric Administration (NOAA)
Dr Emily Osborne, Ph.D. (https://www.aoml.noaa.gov/people/emily-osborne/) is a Research Scientist, in the Ocean Chemistry and Ecosystems Division, at the Atlantic Oceanographic and Meteorological Laboratory.
The Atlantic Oceanographic and Meteorological Laboratory (AOML), a federal research laboratory, is part of the National Oceanic and Atmospheric Administration’s (NOAA) Office of Oceanic and Atmospheric Research (OAR), located in Miami in the United States. AOML’s research spans tropical cyclone and hurricanes, coastal ecosystems, oceans and human health, climate studies, global carbon systems, and ocean observations. It is one of ten NOAA Research Laboratories.
With a B.S. in Geology from the College of Charleston and a Ph.D. in Marine Science from University of South Carolina, Dr. Osborne is currently involved in investigating regional and global biogeochemical issues related to ocean health and climate through the use of a combination of paleoceanographic approaches, new autonomous sensors, and conventional measurements on large multi-disciplinary oceanographic cruises.
Paleoceanography is the study of the history of the oceans in the geologic past with regard to circulation, chemistry, biology, geology and patterns of sedimentation and biological productivity. Paleoceanographic studies using environment models and different proxies enable the scientific community to assess the role of the oceanic processes in the global climate by the re-construction of past climate at various intervals.
😗 I am actually pretty happy about this because full automation will simply life rather than needing as much education the AI can do most of the work much like the star trek computer. Full automation will allow for more freedom even from common tasks allowing the AI to most of the thinking and tasks.
A senior developer tested GPT4 for programming. GPT4 gave the Terraform script code for a single instance of the Fargate API. GPT4 knows that the code will not scale to 10,000 requests per second. It then describes how to create an auto-scaling group and make the modifications to scale the code with AWS and configure the application load balancer.
NOTE: his prompt was way more detailed than an ordinary person would produce. An ordinary person would not be able to verify the results either. You can make the case for 10x or 100x programmer productivity. A senior developer can become a programming lead or manager guiding the AI prompt requests from the equivalent of multiple programming teams.
The advantage will not be to let people who do not know a topic to play with powerful tools. The advantage is to increase the productivity and capacity of competent people to do more in areas that they understand. The AI tools will uplevel the productivity in areas where you know what can and should be done. You do not want someone who does not know how to drive behind the wheel of a Formula One race car.
