Amazing Science

Important ocean currents that redistribute heat, cold and precipitation between the tropics and the northernmost parts of the Atlantic region will shut down around the year 2060 if current greenhouse gas emissions persist. This is the conclusion based on new calculations from the University of Copenhagen that contradict the latest report from the IPCC.

A recent study has highlighted under-prepared regions across the world most at risk of the devastating effects of scorching temperatures.

The University of Bristol-led research, published in Nature Communications, shows that unprecedented heat extremes combined with socioeconomic vulnerability puts certain regions, such as Afghanistan, Papua New Guinea, and Central America,most in peril.

Countries yet to experience the most intense heatwaves are often especially susceptible, as adaptation measures are often only introduced after the event. A high chance of record-breaking temperatures, growing populations, and limited healthcare and energy provision, increase the risks.

Beijing and Central Europe are also on the list of hotspots, as if record-breaking heatwaves occurred in these densely populated regions millions of people would be adversely affected. In light of the findings, the researchers are calling for policy makers in hotspot regions to consider relevant action plans to reduce the risk of deaths and associated harms from climate extremes.

AI may not have any motives against humans, “but a machine that thinks that humans are the root cause of certain problems may think of it that way.”

ChatGPT and other artificial intelligence programs have been red-hot topics in the news lately, simultaneously wracking nerves and exciting us with new possibilities in medicine, linguistics, and even autonomous driving. There are a ton of “what ifs” in this connected future, causing us to rethink everything from killer robots to our own job security.

So should we take a step back from this kind of turbocharged AI to assuage our fears? That depends on who you ask, but it all boils down to the idea of singularity—an “event horizon” in which machine intelligence surpasses our own intelligence. By one measure, technological singularity could be as few as seven years away. That prompted us to reach out to subject-matter experts to find out more about what exactly singularity is, how close we are, and if we should start taking the early 2010s Doomsday Preppers reality show more seriously.

How do we define a singularity?

Singularity is the moment when machine intelligence becomes equal to or surpasses human intelligence—a concept that visionaries like Stephen Hawking and Bill Gates have believed in for quite a long time. Machine intelligence might sound complicated, but is simply defined as advanced computing that allows a device to interact (through a computer, phone, or even an algorithm) and communicate with its environment intelligently.

The concept of singularity has been around for decades. English mathematician Alan Turing—widely regarded as the father of theoretical computer science and artificial intelligence—experimented with the possibility of such a thing in the 1950s. He came up with his famed Turing test to find out whether machines could think for themselves; the evaluation pits a human against a computer, challenging the system to fool us into thinking it’s actually human itself. The recent advent of highly advanced AI chatbots like ChatGPT have brought Turing’s litmus test back into the spotlight. Spoiler alert: it’s passed it already.

“The difference between machine intelligence and human intelligence is that our intelligence is fixed but that is not the case for machines,” Ishaani Priyadarshini, a postdoctoral scholar at UC Berkeley with expertise in applied artificial intelligence and technological singularity, tells Popular Mechanics. “In the cases of machines, there is no end to it, you can always increase it, which is not the case for humans.” Unlike our brains, AI systems can be expanded many times over; the real limitation is space to house all of the computing power.

When Will We Reach Singularity?

While claims that we’ll reach singularity within the next decade are all over the internet, they are, at best, speculative. Priyadarshini believes that singularity already exists in bits and pieces—almost like a puzzle that we’ve yet to complete. She supports estimates claiming we can reach singularity sometime after 2030, adding that it’s hard to be absolutely certain with technology that we know so little about. There’s a very real possibility that it could take much longer than that to reach singularity’s “event horizon”—the point of no return when we unleash superintelligent computer systems.

Having said that, we’ve already seen signs of singularity in our lifetime. “There are games which humans can never win from machines, and that is a sure sign of singularity,” says Priyadarshini. To offer some perspective, IBM’s 1997 “Deep Blue” supercomputer was the first AI to defeat a human chess player. And they didn’t just put Joe Shmoe up to bat: Deep Blue went up against Garry Kasparov, who was the World Chess Champion at the time.

Singularity is still a notoriously difficult concept to measure. Even today, we’re struggling to find markers of our progression toward it. Many experts claim that language translation is the Rosetta Stone for gauging our progress; for instance, when AI is able translate speech at the same level or better than a human, that would be a good sign that we’ve gotten a step closer to singularity. However, Priyadarshini reckons that memes, of all things, could be another marker of our progression toward singularity, as AI is notoriously bad at understanding them.

What will happen when AI reaches singularity?

We have no idea what a superintelligent system would be capable of, it is out of our control at that point. “We would need to be superintelligent ourselves,” Roman Yampolskiy, an associate professor in computer engineering and computer science at the University of Louisville, tells Popular Mechanics. "We are only able to speculate using our current level of intelligence", Yampolskiy wrote in a recent paper.

Mind uploading is a hypothetical process of digitally emulating a brain, allowing for the transfer of an individual's consciousness into a computer system. This technology could potentially allow humans to live forever in digital form, as their memories and personalities would be stored on computers. While this concept has been explored in science fiction for decades, recent advances in artificial intelligence and neuroscience have made it more plausible than ever before. However, there are still many ethical and technical issues that need to be addressed before mind uploading can become reality.

Top Facts about Mind Uploading:

1. Mind uploading is a hypothetical process of transferring a conscious mind from a biological brain to an artificial substrate.
2. It could potentially allow humans to achieve immortality by preserving their consciousness in digital form.
3. The concept has been explored in science fiction and philosophy since the 1970s, but no technology currently exists that can successfully upload a human mind into a computer system.
4. Scientists have made progress in understanding how the brain works and developing technologies that could enable mind uploading, such as neural networks and quantum computing, but these are still far from being able to replicate the complexity of the human brain. 5. Some experts believe that it may be possible to achieve mind uploading within the next few decades, while others think it is impossible or at least many centuries away from becoming reality.

Variety of singularity videos: http://tinyurl.com/7y6mb83

Human and mouse neurons in a dish learned to play the video game Pong, researchers report October 12, 2022 in the journal Neuron. The experiments are evidence that even brain cells in a dish can exhibit inherent intelligence, modifying their behavior over time.

"From worms to flies to humans, neurons are the starting block for generalized intelligence," says first author Brett Kagan (@ANeuroExplorer), chief scientific officer at Cortical Labs in Melbourne, Australia. "So, the question was, can we interact with neurons in a way to harness that inherent intelligence?"

To start, the researchers connected the neurons to a computer in such a way where the neurons received feedback on whether their in-game paddle was hitting the ball. They monitored the neuron's activity and responses to this feedback using electric probes that recorded "spikes" on a grid.

The spikes got stronger the more a neuron moved its paddle and hit the ball. When neurons missed, their playstyle was critiqued by a software program created by Cortical Labs. This demonstrated that the neurons could adapt activity to a changing environment, in a goal-oriented way, in real time.

"We chose Pong due to its simplicity and familiarity, but, also, it was one of the first games used in machine learning, so we wanted to recognize that," says Kagan, who worked with collaborators from 10 other institutions on the project.

"An unpredictable stimulus was applied to the cells, and the system as a whole would reorganize its activity to better play the game and to minimize having a random response," he says. "You can also think that just playing the game, hitting the ball and getting predictable stimulation, is inherently creating more predictable environments."

The theory behind this learning is rooted in the free-energy principle. Simply put, the brain adapts to its environment by changing either its world view or its actions to better fit the world around it.

Pong wasn't the only game the research team tested. "You know when the Google Chrome browser crashes and you get that dinosaur that you can make jump over obstacles (Project Bolan). We've done that and we've seen some nice preliminary results, but we still have more work to do building new environments for custom purposes," says Kagan.

Future directions of this work have potential in disease modeling, drug discoveries, and expanding the current understanding of how the brain works and how intelligence arises.

Supernal has given passengers a first look at what the cabin of its flying taxi may look like – and there are clearly some influences from parent company Hyundai Motor Group. The eVTOL (electric vertical take-off and landing) concept was revealed at the Farnborough International Airshow, in Hampshire, England, and it illustrates how the Advance Air Mobility (AAM) sector can take inspiration from the automotive market. Supernal says it teamed up with Hyundai’s design studios to create the cabin concept as it works to certify its eVTOL vehicle for commercial use in the United States in 2028, with the United Kingdom and European Union expected to follow shortly after.

In addition, it is collaborating with Hyundai’s external partners and more than 50 affiliates – spanning automobiles, automotive parts, construction, robotics and autonomous driving – to co-create the AAM value chain. The five-seat cabin concept strikes a fine balance between using automotive design processes and materials while meeting the safety standards of commercial aviation.

Constructed of lightweight forged carbon fiber, it features ergonomically contoured seats with seat consoles, similar to automobile center consoles, that provide a charging station and stowage compartment for passengers’ personal items.  The mood of the cabin can be adjusted for different stages of flight via a combination of illumination options, including overhead lights inspired by automobile sunroofs.

The flying taxi is intended to be used for journeys within a city and, Jaiwon Shin, president of Hyundai Motor Group and CEO of Supernal, said it was imperative that it afforded the same level of reassurance provided by the company’s passenger cars. “Supernal is partnering with Hyundai Motor Group’s top automotive designers to develop our eVTOL vehicle for manufacturability and widespread public acceptance,” Shin said. “We are taking the time to create a safe, lightweight commercial eVTOL that provides our future passengers with the security and comfort they find in their own cars.”

As well as developing cutting-edge AAM transport, Supernal is also committed to developing the infrastructure to support it. The company provided $1.64 million toward Air-One, the world’s first airport for flying taxis in Coventry in the English Midlands. The facility opened its doors for the first time earlier this year.

Computers can now beat the best human minds in the most intellectually challenging games — like chess. They can also perform tasks that are difficult for adult humans to learn — like driving cars. Yet autonomous machines have difficulty learning to cooperate, something even young children do.

Human cooperation appears easy — but it’s very difficult to emulate because it relies on cultural norms, deeply rooted instincts, and social mechanisms that express disapproval of non-cooperative behavior.

Such common sense mechanisms aren’t easily built into machines. In fact, the same AI software programs that effectively play the board games of chess +  checkers, Atari video games, and the card game of poker — often fail to consistently cooperate when cooperation is necessary.

Other AI software often takes 100s of rounds of experience to learn to cooperate with each other, if they cooperate at all.  Can we build computers that cooperate with humans — the way humans cooperate with each other? Building on decades of research in AI, we built a new software program that learns to cooperate with other machines — simply by trying to maximize its own world.

We ran experiments that paired the AI with people in various social scenarios — including a “prisoner’s dilemma” challenge and a sophisticated block-sharing game. While the program consistently learns to cooperate with another computer — it doesn’t cooperate very well with people. But people didn’t cooperate much with each other either.

As we all know: humans can cooperate better if they can communicate their intentions through words + body language. So in hopes of creating an program that consistently learns to cooperate with people — we gave our AI a way to listen to people, and to talk to them.

We did that in a way that lets the AI play in previously unanticipated scenarios. The resulting algorithm achieved our goal. It consistently learns to cooperate with people as well as people do. Our results show that 2 computers make a much better team — better than 2 humans, and better than a human + a computer.

But the program isn’t a blind cooperator. In fact, the AI can get pretty angry if people don’t behave well. The historic computer scientist Alan Turing PhD believed machines could potentially demonstrate human-like intelligence. Since then, AI has been regularly portrayed as a threat to humanity or human jobs.

To protect people, programmers have tried to code AI to follow legal + ethical principles — like the 3 Laws of Robotics written by Isaac Asimov PhD. Our research demonstrates that a new path is possible.

Machines designed to selfishly maximize their pay-offs can — and should — make an autonomous choice to cooperate with humans across a wide range of situations. 2 humans — if they were honest with each other + loyal — would have done as well as 2 machines. About half of the humans lied at some point. So the AI is learning that moral characteristics are better — since it’s programmed to not lie — and it also learns to maintain cooperation once it emerges.

The goal is we need to understand the math behind cooperating with people — what attributes does AI need so it can develop social skills. AI must be able to respond to us — and articulate what it’s doing. It must interact with other people. This research could help humans with their relationships. In society, relationships break-down all the time. People that were friends for years all-of-a-sudden become enemies. Because the AI is often better at reaching these compromises than we are, it could teach us how to get-along better.

Elon Musk's startup company Neuralink has shown off the latest version of its brain-machine interface, which a monkey uses to wirelessly play Pong with its mind. The demonstration is both another step forward for the ambitious company and a fascinating look at the current state of the technology, which, amongst other things, could offer sufferers of paralysis a way to regain control of their limbs.

The last time we heard from Neuralink, it had implanted one of its computer chips into the brains of pigs to demonstrate how they can record neural activity as the animals sniff around a pen. These chips consists of arrays of electrodes that record patterns of neuron activity, which can then be decoded and converted into input commands for various devices.

Previous research in this field has shown how these brain-machine interfaces can be used to control drones, prosthetic limbs and computer tablets, just by recording and relaying the user's brain activity that signals their intentions. The most impressive feats, however, have required that these brain implants be tethered to computer systems to provide the necessary bandwidth for the signals to be transmitted.

The goal for Neuralink, and many researchers in the field, is to develop a completely wireless version, which would allow sufferers of paralysis far greater freedom and quality of life. A consortium of scientists working on this problem, known as BrainGate, earlier this week revealed it had developed the first wireless system to transmit neural signals at a similar bandwidth to wired systems. It uses arrays of 200 electrodes to gather the full spectrum of signals from the brain's motor cortex and pass them along to a connected wireless transmitter on the user's head.

In ten years artificially intelligent robots will be living and working with us, according to Dr. Mark Sagar, CEO of Soul Machines, an Auckland, New Zealand-based company that develops intelligent, emotionally responsive avatars.

Sagar, an AI engineer, is the inventor of a virtual nervous system that powers autonomous animated avatars like Baby X — a virtual infant that learns through experience and can “feel” emotions.

“We are creating realistic adult avatars serving as virtual assistants. You can use them to plug into existing systems like IBM Watson or Cortana — putting a face on a chatbot,” said Sagar. Within a decade humans will be interacting with lifelike emotionally-responsive AI robots, very similar to the premise of the the HBO hit series Westworld, said Sagar.

But before that scenario becomes a reality robotics will have to catch up to AI technology. “Robotics technology is not really at the level of control that’s required,” he said.

Elon Musk demonstrated a working Neuralink brain-machine interface device implanted on a pig during a live broadcast.  He said the purpose of the presentation was to recruit employees that would like to help develop the system. – “We’re not trying to raise money or do anything else, but the main purpose is to convince great people to come work at Neuralink, and help us bring the product to fruition; make it affordable and reliable and such that anyone who wants one can have one,” he said. Neuralink aims to solve brain-related issues with the brain chip called ‘Link’. Musk said the device could help solve memory loss, strokes, addiction, depression, anxiety, even monitor a users’ health to warn if they are about to have a heart attack. The interface could also help return mobility to paralyzed individuals through artificial limbs. The user would be able to move prosthetics with their thoughts via the Link brain-machine interface.

Ultimately, Musk's vision for Neuralink is for humans to merge with Artificial Intelligence (AI) – “Such that the future of the world is controlled by the combined will of the people of Earth … I think that that’s obviously gonna’ be the future that we want,” he stated.

The Neuralink device is currently in its initial phase of development. The design has changed since it was unveiled in 2019. Before, the device would sit behind a user’s ear and it was visible, now the design looks like a small coin, that will be placed above the skull. It’s “like a Fitbit in your skull with tiny wires,” Musk said a couple of times during the presentation, adding that Neuralink aims to connect humans to the device using Bluetooth to pair with an app on a cell phone. 

The Link chip features 1,024 tiny electrode threads that are threaded by a surgical robot inside the brain to stimulate neurons. “For the initial device, it’s read/write in every channel with about 1024 channels, all-day battery life that recharges overnight and has quite a long-range, so you can have the range being to your phone,” Musk said. “I should say that’s kind of an important thing, because this would connect to your phone, and so the application would be on your phone, and the Link communicating, by essentially Bluetooth low energy to the device in your head.” The Link device will be capable of inductive charging (wirelessly).

A 50-year-old theory that began as speculation about how an alien civilization could use a black hole to generate energy has been experimentally verified for the first time in a Glasgow research lab.

In 1969, British physicist Roger Penrose suggested that energy could be generated by lowering an object into the black hole’s ergosphere – the outer layer of the black hole’s event horizon, where an object would have to move faster than the speed of light in order to remain still.

Penrose predicted that the object would acquire a negative energy in this unusual area of space. By dropping the object and splitting it in two so that one half falls into the black hole while the other is recovered, the recoil action would measure a loss of negative energy – effectively, the recovered half would gain energy extracted from the black hole’s rotation.

The scale of the engineering challenge the process would require is so great, however, that Penrose suggested only a very advanced, perhaps earthbound experiment. He proposed that ’twisted’ light waves, hitting the surface of a rotating metal cylinder turning at just the right speed, would end up being reflected with additional energy extracted from the cylinder’s rotation thanks to a quirk of the rotational Doppler effect.

But Zel’dovich’s idea has remained solely in the realm of theory since 1971 because, for the experiment to work, his proposed metal cylinder would need to rotate at least a billion times a second – another insurmountable challenge for the current limits of human engineering. 

Now, researchers from the University of Glasgow’s School of Physics and Astronomy have finally found a way to experimentally demonstrate the effect that Penrose and Zel’dovich proposed by twisting sound instead of light – a much lower frequency source, and thus much more practical to demonstrate in the lab.

Are we on the brink of an AI apocalypse? According to a recent survey, most U.S. citizens share Elon Musk’s concerns about the potential threat artificial intelligence poses to humanity’s future. 

What a poll shows: A majority of Americans, 61% to be exact, believe that the fast-paced growth of AI could endanger the future of humanity and over two-thirds expressed concerns about its potential negative impacts, reported Reuters, citing a survey conducted by Ipsos.  As per the findings, the proportion of U.S. citizens who anticipate negative consequences from AI is three times higher than those who don’t, with 61% of the 4,415 adults surveyed expressing concerns over the potential hazard of AI and only 22% disagreeing. Rest 17% of the people were uncertain. 

The aforementioned online survey included 4,415 U.S. adults and has a credible interval with a margin of error of plus or minus two percentage points, the report stated. 

Why It’s Important: Landon Klein, director of U.S. policy of the Future of Life Institute, which is behind the “open letter” demanding a six-month pause in AI research “more powerful” than OpenAI’s GPT-4, said that the poll’s findings show that “a broad swath of Americans worry about the negative effects of AI,” the report noted.  “We view the current moment similar to the beginning of the nuclear era, and we have the benefit of public perception that is consistent with the need to take action.”

Musk, who co-founded OpenAI in 2015, along with Apple co-founder Steve Wozniak and over 1000 others, signed an open letter. Although Musk’s intention behind signing the letter has been questioned, considering the tech billionaire’s plans to launch his own chatGPT-rival called “TruthGPT.” 

Benzinga research has found that the exponential growth of OpenAI’s chatGPT has made AI a ubiquitous part of everyday life, leading to a surge of interest in the field and sparking an AI arms race between tech giants like Microsoft Corporation and Alphabet Inc., eager to showcase their own AI breakthroughs. 

In May 2023, Geoffrey Hinton, who recently left his job at Google citing the need to talk more freely about the risks posed by AI, stated that risks posed by AI to humanity could be more pressing than those of climate change. However, others like the godfather of virtual reality, Jaron Lanier, Bill Gates and Jürgen Schmidhuber have a different view and disagree with the sentiment.  

The Singularity, often referred to as the Technological Singularity, is a hypothetical point in the near future at which artificial intelligence (AI) becomes so incredibly advanced that it surpasses human intelligence, leading to rapid, unforeseeable changes in society and technology, life as we know it. The term was popularized by mathematician and computer scientist Vernor Vinge and futurist Ray Kurzweil.

At the Singularity, AI systems would possess the ability to autonomously learn, self-improve, and create new AI systems with very advanced capabilities and more intelligent than themselves, resulting in an exponential increase in intelligence. This self-improvement cycle could lead to AI systems that are vastly more capable and sophisticated than human minds and anything humans can even imagine.

The Singularity is often associated with the development of artificial general intelligence (AGI), which is an AI system that can perform any intellectual task that a human being can do. AGI is distinct from narrow AI, which is designed for specific tasks and lacks the broad cognitive abilities and adaptability of human intelligence.

The implications of the Singularity are the subject of much speculation and debate today. Most people who have thought about it agree that the Singularity would be a decisive turning point in human history. Some view this with awe and trepidation, almost like a religious event that will lead to everlasting life and happiness. Many believe it will bring about tremendous breakthroughs in medicine, energy, and space exploration. Others are more cautious, expressing concerns about the ethical, societal, and existential risks associated with super-intelligent AI systems. Some predict doom and gloom. Others think it is all but impossible.

Predicting the Singularity Start Date

The general caveat to this question given by all experts is that predicting when the Singularity might occur is highly uncertain, as it depends on the pace of AI research, breakthroughs in understanding human cognition, and the development of advanced hardware and software systems. Still, ChatGPT-4 has predicted a 5%-10% chance that the singularity will happen within five years, 2028.  Chat GPT-4 did so without knowledge of what has happened since September 2021, when it was last fed data.

We know what has happened since September 2021, we know the pace of change, even though the ChatGPT model does not. We know that when ChatGPT-3.5 was released in November 2022, it scored in the bottom 10% of the multi-state Bar exam. But just five months later, when 4.0 was released in March 2023, it scored in the top 10%. Let that sink in and remember no new data was provided. There was only improvement in reasoning ability. As lawyers who have all taken this test, we know better than anyone the significance of a jump from the bottom to the top 10% of this challenging test. Yes, it is getting pretty smart, fast. How much longer until its intelligence exceeds our own?

Opportunities and Challenges Presented by the Singularity

The three opportunities listed here, all good, are generally thought to be possible in a time of technological Singularity, a time where AI intelligence and capacities accelerate at an exponential rate.

1. Accelerated Technological Progress: The Singularity could lead to rapid advancements in various fields, as super-intelligent AI systems develop new technologies and solve complex problems that were previously beyond human reach.
2. Economic Growth: With Ai systems handling tasks more efficiently and effectively than humans, productivity and economic growth could increase dramatically, potentially leading to higher standards of living and reduced global inequality.
3. Scientific Discoveries: The Singularity might enable breakthroughs in areas such as healthcare, environmental sustainability, and space exploration, as Ai systems analyze vast amounts of data, simulate complex phenomena, and generate innovative solutions to pressing challenges.

Conversely, as usual, their is a flip side to opportunities, the generally accepted challenges, some might say threats, presented by the Singularity:

1. Ethical Concerns: As Ai systems surpass human intelligence, ethical considerations become paramount. Ensuring that Ai systems behave ethically, adhere to human values, and respect individual rights will be crucial.
2. Job Displacement: The widespread adoption of super-intelligent Ai systems could result in job displacement across various industries, as human workers are replaced by more efficient Ai. This raises concerns about unemployment, workforce retraining, and social safety nets.
3. Existential Risks: The Singularity poses potential existential risks, as super-intelligent Ai might act in ways that are harmful to humanity, either intentionally or unintentionally. Ensuring Ai safety and robustness is essential to mitigate these risks.

Futurists have long speculated that upon the arrival of AGI, the first sperintelligence will quickly follow. From I. J. Good, writing in 1965,

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.

Nick Bostrom wrote in his book Superintelligence (2014),

Note that one could think that it will take quite a long time until machines reach the human baseline, or one might be agnostic about how long that will take, and yet have a strong view that once this happens, the further ascent into strong superintelligence will be very rapid.

and categorized takeoff durations into three types:

• "A slow takeoff is one that occurs over some long temporal interval, such as decades or centuries."

• "A fast takeoff occurs over some short temporal interval, such as minutes, hours, or days."

• "A moderate takeoff is one that occurs over some intermediary temporal interval, such as months or years."

While it seems that most prominent thinkers are convinced that rapid technological and economic progress will follow the development of AGI (See Paul Christiano, Robin Hanson, Eliezer Yudkowsky, Ben Goertzel), most AI researchers surveyed are not convinced. In 2016, AI Impacts asked AI researchers,

Assume that HLMI will exist at some point. How likely do you then think it is that the rate of global technological improvement will dramatically increase (e.g. by a factor of ten) as a result of machine intelligence:

Within two years of that point? ___% chance

Within thirty years of that point? ___% chance

The median answer was 20% for the two year estimate and 80% for the thirty year estimate.

When the Sun and Moon act on the Earth, our planet bulges a little bit due to these tidal forces. And, when something gravitationally pulls on a spinning, bulging object, that external force acts the same way that lightly putting your finger up against a spinning top acts: as a frictional force, slowing the rotation down. Over time, this can really add up!

This “braking” effect takes angular momentum away from the spinning Earth, causing it to rotate slower and slower over time. But angular momentum is something that’s fundamentally conserved; it cannot be created or destroyed, only transferred from one object to another. If the Earth’s rotation is slowing down, that angular momentum must transfer elsewhere.

So where is that elsewhere? Into the Moon, which spirals away from the Earth as the Earth’s rotation slows down. With every year that passes, these tidal forces lengthen the amount of time it takes for Earth to complete a full 360° rotation by a tiny, but barely perceptible amount. Compared to precisely one year ago today, our planet takes an extra 14 microseconds to complete a full rotation. This extra 14 microseconds per day adds up over time, which is why — on average — we have to add a leap second to our clock to keep them where they ought to be every 18 months.

Of course, this effect accumulates over longer periods of time, but there are other effects working alongside it:

• radiation from the Sun, which pushes Earth slightly outward in its orbit around the Sun,
• the solar wind — particles from the Sun — which collide with Earth and slightly slow its motion down,
• and mass loss from the Sun, which emits particles and converts mass into energy (via Einstein’s E = mc2) through nuclear fusion in its core, causing Earth to slowly spiral outwards, away from the Sun.

While the effects of angular momentum loss cause Earth to spin at a slower rate, meaning that as time goes on, it takes fewer “days” to make up a year, these effects all do something else entirely. When you push Earth outwards, when you slow Earth’s motion down, or when you decrease the mass of the Sun, it causes the year to lengthen. The greatest effect, as it turns out, comes from mass loss, as the Sun a total of about 5.6 million tons of mass each second from nuclear fusion (4 million) and the solar wind (1.6 million) combined, or the equivalent of 177 trillion tons of mass per year.

With each year that goes by, this mass loss means that Earth spirals outwards at a rate of approximately 1.5 cm (about 0.6 inches) every year. Over the history of our Solar System, taking into account how our Sun has changed, we’re somewhere around 50,000 km farther from the Sun versus 4.5 billion years ago. And we’re orbiting around the Sun at a slightly slower speed — about 0.01 km/s slower — today than we were back when the Solar System first formed. Consider that at our fastest, Earth moves through space at 30.29 km/s (18.83 mi/s), while at our slowest, we move at 29.29 km/s (18.20 mi/s), this difference is very, very small, and the effect can be completely neglected without losing pretty much any accuracy. Similarly, effects like earthquakes, ice melting, core formation, and thermal expansion of the Earth all exist, but only dominate on very short timescales where changes are relatively rapid.

What does, then, on the long timescales we’re considering? The dominant effect in determining how the length of a Tropical Year changes relative to a calendar year is set by tidal braking of the Earth. And the longer we wait, the greater the discrepancy becomes. It won’t be, astronomically speaking, all that long before adding a second here or there becomes a wildly insufficient fix for our changing planet.

The way we’ll need to modify our calendar, as the Earth’s rotation slightly slows down, is by removing days, rather than adding them. As time goes on initially, we’ll want to begin reducing the frequency of leap years; we’ll be able to eliminate them entirely after another ~4 million years passes. At that point, Earth will rotate a little more slowly, and a calendar year will correspond to precisely 365.0000 days. Beyond that point, we’ll need to start having “reverse” leap years, where we remove a day every so often, before we eventually go down to ~364 day years some ~21 million years into the future. As these changes occur, the day will lengthen to greater than 24 hours. Eventually, we’ll even pass Mars, with a 24 hour, 37 minute day, to become the planet with the 3rd longest day in the Solar System, behind only Mercury and Venus.

Created by AI

https://twitter.com/debarghya_das/status/1610470866713972737

Smart summary:
The thread discusses the upcoming "Prompt Palettes" feature for ChatGPT, which will provide users with pre-written text prompts to help with tasks like formatting raw text, summarizing text, and serving as a programming assistant. The feature will use OpenAI's GPT-3 Codex models, and is similar to a "brushes" feature being developed by Github Copilot Labs.
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ChatGPT will soon drop a new feature – Prompt Palettes!

They're pre-written text prompts to perform tasks like
- format raw text to markdown
- summarize text
- be a programming assistant
- add text from a link as context

How it works and EXACT prompts are pre-written bits of text that accentuate a user's input for a specific task.

It's like a magic button for text explained only by pre-written instructions. Here are the prompts to "format" and "summarize". You should be able to add your own too.

— ChatGPT Coding Assistant —

is slightly different from Prompt Palettes but seems like a pre-written addendum to a query to serve as a one-shot way to focus on a specific vertical task.

This might be forcing the use of GPT-3: Codex explicitly– https://t.co/GddMvqG3pU

Prompt palettes act on a specific message, and ChatGPT is adding a nifty "Add text from link" feature which will allow you to, say, summarize websites easily.

Prompt palettes aren't new! Github Copilot Labs has been working on a similar magic "brushes" feature that integrates directly into VS Code. They use OpenAI's GPT-3 Codex models too.

https://t.co/8gOp9L17Bx

Prompt Palettes will bring these powerful new LLM features to the mainstream of 1 million users! 2023 has just begun for AI.

https://t.co/04GwCmOQr8

Thanks to @eeeziii for the idea of reverse-engineering ChatGPT (he did this too)!

ChatGPT is a minified React app with chunked JS that uses Server Sent Events with /conversations to stream the meat of the output. It uses text-davinci-002-render with 4097 max tokens.

Moore’s Law predicts that the number of transistors per device will double every two years. Moore’s Law is and always has been driven by innovation. The above figure illustrates the number of transistors per device as we look to the past, the present and the future. For the first 40 years, the gains came primarily from innovations in our process. Going forward, gains will come from innovations in both process and packaging. INTEL's processes will continue to deliver historic density improvements, while its 2D and 3D stacking technologies give architects and designers more tools to increase the number of transistors per device. As the designers look forward to innovative technologies such as High NA, RibbonFET, PowerVia, Foveros Omni and Direct, and others, INTEL sees no end to innovation and therefore currently no end to Moore’s Law.

In summary, when we consider all the various process and advanced packaging innovations, there are numerous options available to continue to double the number of transistors per device at the cadence demanded by our customers. Moore’s Law only stops when innovation stops, and innovation continues unabated at Intel in process, packaging and architecture. We remain undeterred in our aspiration to deliver approximately 1 trillion transistors in a single device by 2030.

Synchron announced today that it completed the first-in-human brain-computer interface (BCI) implant in the U.S. The procedure, performed at Mount Sinai West in New York, represents the first such implant to occur in the U.S. using an endovascular BCI approach, which does not require invasive open-brain surgery.

Dr. Shahram Majidi, assistant professor of neurosurgery, neurology and radiology at the Icahn School of Medicine at Mount Sinai, led the procedure, which was performed in the angiography suite with a minimally invasive, endovascular approach. Earlier this year, Synchron’s neuroscience chief explained how this type of catheter delivery could enable better brain implants.

It was the first patient implant in Synchron’s Command trial, operating under FDA investigational device exemption to assess a permanently implanted BCI. Command will assess the safety and efficacy of the company’s motor BCI technology, including the Stentrode, in patients with severe paralysis, aiming to enable the patient to control digital devices hands-free. Study outcomes include the use of brain data to control digital devices and achieve improvements in functional independence, according to a news release.

“This is an incredibly exciting milestone for the field, because of its implications and huge potential,” Majidi said in the release. “The implantation procedure went extremely well, and the patient was able to go home 48 hours after the surgery.” Notably, the first-in-human implant pulls Synchron ahead of Elon Musk’s Neuralink, which is working to develop an implant placed in the brain through a robot-assisted procedure.

Neuralink requires implantation through the skull, and, while Musk and company officials said they planned to file for FDA approval for human trials in 2020, it has yet to receive such approval. Earlier this year, Neuralink and the University of California, Davis, were accused of “egregious violations of the Animal Welfare Act” by the Physicians Committee for Responsible Medicine (PCRM), citing documents obtained through a public records lawsuit. The allegations claimed that Neuralink caused extreme suffering in monkeys.

Synchron’s Stentrode is implanted within the major cortex through the jugular vein in a minimally invasive endovascular procedure. Once implanted, it detects and wirelessly transmits motor intent using a proprietary digital language to allow severely paralyzed patients to control personal devices with hands-free point-and-click.

The company intends to continue enrollment in the Command trial, while recently reported long-term safety results demonstrated the safe use of the device in four patients out to 12 months in an Australia-based trial. “The first-in-human implant of an endovascular BCI in the U.S. is a major clinical milestone that opens up new possibilities for patients with paralysis,” Synchron CEO and founder Dr. Tom Oxley said. “Our technology is for the millions of people who have lost the ability to use their hands to control digital devices. We’re excited to advance a scalable BCI solution to market, one that has the potential to transform so many lives.”

Researchers show how intelligent aliens might draw nearly-limitless power from a black hole using a Dyson sphere.

The search for extraterrestrial intelligence (SETI) has been conducted for nearly 60 yr. A Dyson sphere, a spherical structure that surrounds a star and transports its radiative energy outwards as an energy source for an advanced civilization, is one of the main targets of SETI to identify intelligent aliens around galactic energy sources.

Recently, astronomers analyzed whether building a Dyson sphere around a black hole is effective. They considered six energy sources: (i) the cosmic microwave background, (ii) the Hawking radiation, (iii) an accretion disc, (iv) Bondi accretion, (v) a corona, and (vi) relativistic jets. To develop future civilizations (for example, a Type II civilization), 4×1026W(1L⊙)4×1026W(1L⊙) is expected to be needed. Among (iii) to (vi), the largest luminosity can be collected from an accretion disc, reaching 105L⊙105L⊙⁠, enough to maintain a Type II civilization. Moreover, if a Dyson sphere collects not only the electromagnetic radiation but also other types of energy (e.g. kinetic energy) from the jets, the total collected energy would be approximately 5 times larger.

Considering the emission from a Dyson sphere, their analysis shows that the Dyson sphere around a stellar-mass black hole in the Milky Way (⁠10kpc away from us) should be detectable in the ultraviolet (10−400nm)(10−400nm)⁠, optical (400−760nm)(400−760nm)⁠, near-infrared (⁠760nm−5μm760nm−5μm⁠), and mid-infrared (⁠5−40μm5−40μm⁠) wavelengths via the waste heat radiation using current telescopes such as Galaxy Evolution Explorer Ultraviolet Sky Surveys.

Performing model fitting to observed spectral energy distributions and measuring the variability of radial velocity may help astronomers to identify these possible artificial structures.

In a first-of-its-kind experiment, a team of Japanese researchers freeze-dried samples of mice sperm and sent them aboard the ISS to see how well this crucial element of human life (and, well, a lot of life on Earth) will fair against the harsh radiation of space. Even after six long years aboard the ISS, the team found that the mice’s space sperm sired equally healthy pups as its terrestrial control. An additional X-ray experiment predicts that this positive outcome could persist with up to 200 years of space radiation exposure.

Sayaka Wakayama, assistant professor of reproductive biology at the University Yamanashi and first author on the research, tells Inverse that these findings will help prepare humans for a new space age. Wakayama and colleagues’ findings were published recently in the journal Science Advances.

Gauging whether or not we dwell inside someone’s computer may come down to advanced AI research—or measurements at the frontiers of cosmology. If posthuman civilizations eventually have both the capability and desire to generate such highest level AI-like simulations, then the number of simulated realities would greatly exceed the one base reality, ostensibly indicating a high probability that we do not live in said base reality.

Recently, it has been argued that since the hypothesis that such simulations are technically possible remains unproven, statistical calculations need to consider not just the number of state spaces, but the intrinsic model uncertainty. This is achievable through a Bayesian treatment of the problem. Using Bayesian model averaging, it is shown that the probability that we are sims is in fact less than 50%, tending towards that value in the limit of an infinite number of simulations. This result is broadly indifferent as to whether one conditions upon the fact that humanity has not yet birthed such simulations, or ignore it. As argued elsewhere, it is found that if humanity does start producing such simulations, then this would radically shift the odds and make it very probably we are in fact indeed simulated.

What is it like for a person to live partly inside of the objective function of an AI program? Intel scientist Lama Nachman shares insights from her team’s work with Peter Scott-Morgan, a person willing to transform his body and his life to interact intimately with a machine.

Lama Nachman spent years helping the late Stephen Hawking through various upgrades of the computer technology that helped him to work and communicate. Hawking passed away in 2018.  Her team at Intel Labs is now working with Peter Scott-Morgan, a roboticist who has undergone several operations to head off the incapacity that comes from ALS, the same affliction as Hawking suffered. Working with a variety of technologies, including GPT-2, OpenAI's generative deep learning model for text, Nachman and team are pushing at the boundaries of how a person can exist in a give and take relationship with AI.  

Part ethnographer, Nachman shows great sensitivity to the nuances of how humans encounter technology. She explained to ZDNet the differences in temperament between her two very different collaborators, first Hawking, now Scott-Morgan.  Hawking was "the best validation engineer ever," says Nachman. He endured tons and tons of trial and error with new technology, and seemed to derive great satisfaction in finding bugs in the software. It was almost like man versus machine, to hear Nachman tell it, John Henry versus the pneumatic drill. 

Scott-Morgan, in contrast, sees himself as becoming one with the machine, both helping to train it, and at the same time learning a new mode of being from it in a symbiotic fashion.  "I think of myself as partly human and partly AI," is how Scott-Morgan views it, in Nachman's telling. "I am willing to be nudged by the AI system," Scott-Morgan has told her. British television is airing a program about Scott-Morgan's transformation, and you can see the trailer here. 

A new deepfake art installation reimagines the story of the moon landings, revealing threats to both democracy and history,