Amazon’s smart home webcam can fly around to guard your house.
Ring Always Home Cam can fly around
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In recent years, researchers have been developing machine learning algorithms for an increasingly wide range of purposes. This includes algorithms that can be applied in healthcare settings, for instance helping clinicians to diagnose specific diseases or neuropsychiatric disorders or monitor the health of patients over time.
Researchers at Massachusetts Institute of Technology (MIT) and Massachusetts General Hospital have recently carried out a study investigating the possibility of using deep reinforcement learning to control the levels of unconsciousness of patients who require anesthesia for a medical procedure. Their paper, set to be published in the proceedings of the 2020 International Conference on Artificial Intelligence in Medicine, was voted the best paper presented at the conference.
“Our lab has made significant progress in understanding how anesthetic medications affect neural activity and now has a multidisciplinary team studying how to accurately determine anesthetic doses from neural recordings,” Gabriel Schamberg, one of the researchers who carried out the study, told TechXplore. “In our recent study, we trained a neural network using the cross-entropy method, by repeatedly letting it run on simulated patients and encouraging actions that led to good outcomes.”
The Always Home Cam foils a very sloppy burglar.
Ring has given a brief demo of its flying security camera drone in a new ad. The Always Home Cam will be available next year and can be controlled with your phone.
A recent international scientific study published in the journal PLOS ONE has shown that the way the brain stores temporary information is different depending on the use one might give to that information in the future.
The research analysed the brain activity of 14 participants through functional magnetic resonance imaging while they were performing simple visual memory tasks on a computer screen. Differences in their brain activity patterns were found between participants who had to answer by communicating verbally or by pressing a button.
The memory that is under study is designated “working memory” and is used at all times. It is the type of memory that allows us to memorise a phone number or a license plate and use that information after (or not). This information is used and processed and, if it proves to be important, stored in the long-term memory.
ESA Astronaut Pesquet revealed Crew-2 has been actively training for “Mission Alpha” aboard Crew Dragon. He shared photographs via Twitter of him training on SpaceX’s Crew Dragon simulator which involves learning how to control the spacecraft’s functions via a trio of touchscreen displays. – “Here’s the posse together, training on @SpaceX crew dragon. @Aki_Hoshide looking like a boss, and all of us wishing we had as cool socks as our awesome pilot @Astro_Megan. #MissionAlpha,” he wrote. During training, all astronauts are wearing face masks to protect each other from the coronavirus respiratory illness, pictured below.
Here’s the posse together, training on @SpaceX crew dragon. @Aki_Hoshide looking like a boss, and all of us wishing we had as cool socks as our awesome pilot @Astro_Megan. #MissionAlpha pic.twitter.com/UCDJvTcRgp— Thomas Pesquet (@Thom_astro) September 23, 2020
To familiarize with the spacecraft, the astronauts train with an interactive simulator and touchscreen interface that is a replica of Dragon’s cockpit. Earlier this year, SpaceX released an online game that allows players to try to dock the Crew Dragon spacecraft to the Space Station, using similar controls the astronauts will use during their voyage in space. You can play the online game on SpaceX’s website: Crew Dragon Simulator.
According to Blue Origin, the launch is now set for Friday, Sept. 25 at 10 a.m. central time. You can watch the launch live here.
Boeing to Face Independent Ethics Probe Over Lunar Lander Bid
According to a press release, the New Shepard will fly 12 commercial payloads to space and back, including a demonstration of a lunar landing sensor that will test technologies for future missions to the Moon in support of NASA’s Artemis program.
Researchers took a silica nanoparticle designated as ‘Generally Recognized As Safe’ by the US Food and Drug Administration and coated it with L-phenylalanine, and found that in lab tests with mice it killed cancer cells effectively and very specifically, by causing them to self-destruct.
Cancer cells are killed in lab experiments and tumor growth reduced in mice, using a new approach that turns a nanoparticle into a ‘Trojan horse’ that causes cancer cells to self-destruct, a research team at the Nanyang Technological University, Singapore (NTU Singapore) has found.
The researchers created their ‘Trojan horse’ nanoparticle by coating it with a specific amino acid — L-phenylalanine — that cancer cells rely on, along with other similar amino acids, to survive and grow. L-phenylalanine is known as an ‘essential’ amino acid as it cannot be made by the body and must be absorbed from food, typically from meat and dairy products.
Studies by other research teams have shown that cancer tumor growth can be slowed or prevented by ‘starving’ cancer cells of amino acids. Scientists believe that depriving cancer cells of amino acids, for example through fasting or through special diets lacking in protein, may be viable ways to treat cancer.
Of all the AI models in the world, OpenAI’s GPT-3 has most captured the public’s imagination. It can spew poems, short stories, and songs with little prompting, and has been demonstrated to fool people into thinking its outputs were written by a human. But its eloquence is more of a parlor trick, not to be confused with realintelligence.
Nonetheless, researchers believe that the techniques used to create GPT-3 could contain the secret to more advanced AI. GPT-3 trained on an enormous amount of text data. What if the same methods were trained on both text and images?
Now new research from the Allen Institute for Artificial Intelligence, AI2, has taken this idea to the next level. The researchers have developed a new text-and-image model, otherwise known as a visual-language model, that can generate images given a caption. The images look unsettling and freakish—nothing like the hyperrealistic deepfakes generated by GANs —but they might demonstrate a promising new direction for achieving more generalizable intelligence, and perhaps smarter robots as well.
Very interesting!
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“The plan was to scan patients’ genomes—in particular, a set of 13 genes involved in interferon immunity against influenza. In healthy people, interferon molecules act as the body’s security system. They detect invading viruses and bacteria and sound the alarm, which brings other immune defenders to the scene.
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Casanova’s team has previously discovered [genetic mutations](https://medicalxpress.com/tags/genetic+mutations/) that hinder interferon production and function. People with these mutations are more vulnerable to certain pathogens, including those that cause influenza. Finding similar mutations in people with COVID-19, the team thought, could help doctors identify patients at risk of developing severe forms of the disease. It could also point to new directions for treatment, he says.”
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“As the researchers began analyzing patient samples, they started to uncover harmful mutations, in people young and old. The team found that 23 out of 659 patients studied carried errors in genes involved in producing antiviral interferons.”
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“That thought sparked a new idea. Maybe other patients with severe COVID-19 also lacked interferons—but for a different reason. Maybe some patients’ bodies were harming these molecules themselves.”
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They’re not just for supervillains anymore.
Scientists in Japan and Germany have made a breakthrough in the field of solar lasers—and they’ve changed the game completely.
🤯 You like badass science. So do we. Let’s nerd out over it together.