I explain what time dilation is with examples and evidence based experiments. Time slowing down is an actual thing that we experience and use in our technologies.
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REFERENCES
The Tempest by Peter Cawdron: https://tinyurl.com/2ep4uzvs.
Inside Black Holes: https://youtu.be/iUr8Obv_DeA
How Black Holes form: https://youtu.be/7xCgnMqIgPI
How Stable orbits form around Black Holes: https://tinyurl.com/2klz9mfd.
CHAPTERS
0:00 Karl Schwarzschild theorizes black holes.
1:58 Inspiration for this video.
3:16 How black holes form.
5:28 What is the Event Horizon?
7:25 How Time flows near & inside a black hole.
9:57 How can Black Holes be so bright if no light escapes?
11:34 How do we detect black holes if we can’t see them?
12:29 Can life form on a planet orbiting a black hole?
14:59 How long do black holes last?
SUMMARY
Karl Schwarzschild crafted the first exact solution to Einstein’s equations of general relativity. He found that as gravity increased around an object, there must be a point where even light could not escape. He theorized black holes.
Stars are in a balance between gravity trying to collapse it inward, and energy of fusion in its core which pushes outward. But when large stars run out of fuel, gravity causes it to collapse. If the star is massive enough, this results in a supernova. A black hole remains in the center of the debris, if the collapsed core has a mass of 2 to 3 times the mass of our sun.
In a Black Hole, General relativity says all its mass is collapsed into an infinitesimally small volume, called a singularity. A singularity has all its mass in zero volume of space, thus it has infinite density. But infinities usually mean errors in math, so singularities may not be real.
This is a recording of the SingularityNET Ecosystem leaders meeting, which was recorded on Monday, October 31st, 2022, including updates on projects progress, exciting news, and discussions around key initiatives.
SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol.
We gathered the leading minds in machine learning and blockchain to democratize access to AI technology. Now anyone can take advantage of a global network of AI algorithms, services, and agents.
Website: https://singularitynet.io.
Discord: https://discord.gg/snet.
Forum: https://community.singularitynet.io.
Telegram: https://t.me/singularitynet.
Twitter: https://twitter.com/singularity_net.
Facebook: https://facebook.com/singularitynet.io.
Instagram: https://instagram.com/singularitynet.io.
Github: https://github.com/singnet.
Linkedin: https://www.linkedin.com/company/singularitynet
This sounds a lot like cryptomining but it also doesn’t. Cryptomining has nothing to do with machine learning algorithms and, unlike machine learning, cryptomining’s only value is producing a highly speculative digital commodity called a token that some people think is worth something and so are willing to spend real money on it.
This gave rise to a cryptobubble that drove a shortage of GPUs over the past two years when cryptominers bought up all the Nvidia Ampere graphics cards from 2020 through 2022, leaving gamers out in the cold. That bubble has now popped, and GPU stock has now stabilized.
But with the rise of ChatGPT, are we about to see a repeat of the past two years? It’s unlikely, but it’s also not out of the question either.
The opening keynote for the AGI-22 conference by Dr. Ben Goertzel, titled “Open-ended Motivations for AGI”, recorded on August 20th, 2022.
SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol.
We gathered the leading minds in machine learning and blockchain to democratize access to AI technology. Now anyone can take advantage of a global network of AI algorithms, services, and agents.
Website: https://singularitynet.io.
Discord: https://discord.gg/snet.
Forum: https://community.singularitynet.io.
Telegram: https://t.me/singularitynet.
Twitter: https://twitter.com/singularity_net.
Facebook: https://facebook.com/singularitynet.io.
Instagram: https://instagram.com/singularitynet.io.
Github: https://github.com/singnet.
Linkedin: https://www.linkedin.com/company/singularitynet
In an interview with EE Times, Classiq CEO Nir Minerbi said Classiq’s academic program is an essential part of its broader strategy to expand the platform’s reach and promote the quantum computing business.
“We believe that offering this program will give students the tools and knowledge they need to learn practical quantum software-development skills while also providing researchers with a streamlined means of developing advanced quantum computing algorithms capable of taking advantage of ever more powerful quantum hardware,” he said. “In addition, our program enables students and researchers to test, validate and run their quantum programs on real hardware, providing valuable real-world experience. Ultimately, we think that our academic program will have a significant impact on the quantum computing community by promoting education and research in the field—and helping to drive innovation and progress in the industry.”
Classiq and Microsoft are among the top companies developing quantum computing software. The quantum stack developed by the firms advances Microsoft’s vision for quantum programming languages, which was published in the 2020 issue of Nature.
Will a machine learning AI be the way we find out we are not alone in the Universe?
In a January 2023 published paper in Nature Astronomy, a collaboration by authors from universities in Toronto, Canada, Berkeley in California, Manchester in the United Kingdom, Malta, Queensland and Western Australia, and the SETI Institute, created a machine learning algorithm variational autoencoder, a type of neural network that learns through the unsupervised study of unlabelled data. They used it to try and find technosignatures contained within 150 Terabytes of radio traffic from 820 nearby stars. The data source came from the Green Bank Telescope in West Virginia, the world’s largest steerable radio telescope. This data had previously been searched in 2017 using traditional techniques.
Radio signals are abundant throughout the Universe and they represent the most effective way for us to find out if we are a solo act or one of many technical civilizations. Our contribution to radio traffic has been going on for more than a century which means an alien civilization within a hundred light-years from us with technology similar to ours can now detect us.
SETI (Search for Extraterrestrial Intelligence) has been using radio telescopes and receiving antennae since 1960 in a search to detect signals coming from space in patterns similar to what we produce. So far, however, it has proven to be harder than finding the proverbial needle in a haystack. That’s why the application of AI to the vast amounts of radio traffic coming from space is seen as a step up in our efforts to detect alien intelligence. It seems ironic that an AI may be the way we first discover alien intelligence originating from distant solar systems. And it may be that those alien species are using their own AIs to be doing the same.
OAKLAND, Calif. Feb 28 (Reuters) — Intel Corp (INTC.O) on Tuesday released a software platform for developers to build quantum algorithms that can eventually run on a quantum computer that the chip giant is trying to build.
The platform, called Intel Quantum SDK, would for now allow those algorithms to run on a simulated quantum computing system, said Anne Matsuura, Intel Labs’ head of quantum applications and architecture.
Quantum computing is based on quantum physics and in theory can perform calculations quicker than conventional computers.
As chatbot responses begin to proliferate throughout the Internet, they will, in turn, impact future machine learning algorithms that mine the Internet for information, thus perpetuating and amplifying the impact of the current programming biases evident in ChatGPT.
ChatGPT is admittedly a work in progress, but how the issues of censorship and offense ultimately play out will be important. The last thing anyone should want in the future is a medical diagnostic chatbot that refrains from providing a true diagnosis that may cause pain or anxiety to the receiver. Providing information guaranteed not to disturb is a sure way to squash knowledge and progress. It is also a clear example of the fallacy of attempting to input “universal human values” into AI systems, because one can bet that the choice of which values to input will be subjective.
If the future of AI follows the current trend apparent in ChatGPT, a more dangerous, dystopic machine-based future might not be the one portrayed in the Terminator films but, rather, a future populated by AI versions of Fahrenheit 451 firemen.
The development of artificial intelligence (AI) algorithms has permeated the medical field with great success. The widespread use of AI technology in diagnosing and treating several types of cancer, especially colorectal cancer (CRC), is now attracting substantial attention. CRC, which represents the third most commonly diagnosed malignancy in both men and women, is considered a leading cause of cancer-related deaths globally. Our review herein aims to provide in-depth knowledge and analysis of the AI applications in CRC screening, diagnosis, and treatment based on current literature. We also explore the role of recent advances in AI systems regarding medical diagnosis and therapy, with several promising results. CRC is a highly preventable disease, and AI-assisted techniques in routine screening represent a pivotal step in declining incidence rates of this malignancy.
