Any nation invested on this will be able to create its own trillionares!
There’s been a lot of fuss of late about asteroid mining and what it could mean for us Earthlings. But what will it take to make this happen, and should we even be doing it?
Health Magazine Issue February 2020
Posted in health
Chinese health officials have already been administering the HIV and flu drugs to fight the coronavirus. The use of the three together in a cocktail seemed to improve the treatment, the Thai doctors said.
Another doctor said that a similar approach in two other patients resulted in one displaying some allergic reaction but the other showed improvement.
“We have been following international practices, but the doctor increased the dosage of one of the drugs,” said Somsak Akkslim, director-general of the Medical Services Department, referring to the flu medicine Oseltamivir.
Steam’s concurrent user count passed 18.8 million earlier today, peaking at 18,801,944 according to tracker SteamDB. The previous record was 18.5 million just about two years ago on January 6, 2018. As noted by SteamDB, this concurrent user record did not coincide with a record number of players in game, with only 5.8 million today against 7 million two years ago, about 1.2 million fewer. The previous record was boosted by the huge number of players in Playerunknown’s Battlegrounds. It’s not known what caused the current peak, though the time of the peak coincides with peak playtimes for all of Steam’s top games.
.@Steam has broken its record for most concurrently online users that was held for two years. Previous record was 18,537,490 users. It’s still increasing!But there’s about 1 million less players actually in-game (≈5.8mil vs ≈7mil two years ago). https://steamdb.info/app/753/graphs/ February 2, 2020
A compound found in sharks, known as Squalamine, is beleived to have potential as an antiviral medicine for humans. How will this affect sharks?
Why could the mongoose Rikki Tikki Tavi attack deadly snakes with impunity in Kipling’s “Jungle Book?” Because he has a uniquely mutated receptor for a brain neurotransmitter called acetylcholine, researchers at the Weizmann Institute of Science report in the Proceedings of the National Academy of Sciences.
The toxins in many snake venoms, including that of cobras, bind to the acetylcholine receptors of their victims, blocking nerve-muscle communications. Molecular biologist Sara Fuchs and her colleagues found that the acetylcholine receptor in mongooses—like that in the snakes themselves—is slightly mutated so that the venom simply bounces off the muscle cells, causing them no harm.
Circa 2018
Stem cells have been a source of much excitement in the medical community for years, as if they could be properly developed for use in humans doctors could theoretically use them to regrow missing body parts.
While the techniques have seen some success in the lab, the processes involved are complex and it will likely be some time before they become widely used in clinical practice.
The hidden secret of artificial intelligence is that much of it is actually powered by humans. Well, to be specific, the supervised learning algorithms that have gained much of the attention recently are dependent on humans to provide well-labeled training data that can be used to train machine learning algorithms. Since machines have to first be taught, they can’t teach themselves (yet), so it falls upon the capabilities of humans to do this training. This is the secret achilles heel of AI: the need for humans to teach machines the things that they are not yet able to do on their own.
Machine learning is what powers today’s AI systems. Organizations are implementing one or more of the seven patterns of AI, including computer vision, natural language processing, predictive analytics, autonomous systems, pattern and anomaly detection, goal-driven systems, and hyperpersonalization across a wide range of applications. However, in order for these systems to be able to create accurate generalizations, these machine learning systems must be trained on data. The more advanced forms of machine learning, especially deep learning neural networks, require significant volumes of data to be able to create models with desired levels of accuracy. It goes without saying then, that the machine learning data needs to be clean, accurate, complete, and well-labeled so the resulting machine learning models are accurate. Whereas it has always been the case that garbage in is garbage out in computing, it is especially the case with regards to machine learning data.
According to analyst firm Cognilytica, over 80% of AI project time is spent preparing and labeling data for use in machine learning projects:
When doctors in a Washington hospital sought to treat the first confirmed case of the Wuhan coronavirus in the United States on Wednesday, they tapped a device called Vici that allowed them to interact with their patient not in person, but through a screen.
The telehealth device, which looks like a tablet on wheels that doctors can use to talk to patients and perform basic diagnostic functions, like taking their temperature, is one of a handful of high-tech machines that doctors, airport workers, and hotel staff are using to help contain the outbreak that has been sweeping the world since it was discovered in Wuhan, China in late December.
“Caregivers provide care within the isolation unit, but technology is allowing us to reduce the number of up-close interactions,” says Dr. Amy Compton-Phillips, chief clinical officer at Providence Regional Medical Center in Everett, Washington, where the patient is being treated. Vici, made by Santa Barbara, California-based InTouch Health, resembles a tablet on wheels, and can protect caregivers from infection.
There’s no two-ways about it, the Universe is an extremely big place! And thanks to the limitations placed upon us by Special Relativity, traveling to even the closest star systems could take millennia. As we addressed in a previous article, the estimated travel time to the nearest star system (Alpha Centauri) could take anywhere from 19,000 to 81,000 years using conventional methods.
For this reason, many theorists have recommended that humanity should rely on generation ships to spread the seed of humanity among the stars. Naturally, such a project presents many challenges, not the least of which is how large a spacecraft would need to be to sustain a multi-generational crew. In a new study, a team of international scientists addressed this very question and determined that a lot of interior space would be needed!