Category Archives: Singularity

Even as more offshore wind projects launch and the turbines they use get bigger, there are questions around offshore winds economic viability. Unsurprisingly, hauling huge equipment with multiple moving parts out to deep, windy sections of ocean, setting them up, and building lines to transmit the electricity they generate back to land is expensive. Really expensive. In our profit-driven capitalist economy, companies arent going to sink money into technologies that dont deliver worthwhile returns.

A Swedish energy company called SeaTwirl is flipping the offshore wind model on its headnot quite literally, but almostand betting it will be able to deliver cheap renewable energy and make a profit along the way. SeaTwirl is one of several companies developing vertical-axis wind turbines, and one of just a couple developing them for offshore use.

A quick refresher on what vertical axis means: the turbines were used to seeing (that is, on land, at a distance, often from an interstate highway or rural road), have horizontal axes; like windmills, their blades spin between parallel and perpendicular to the ground, anchored by a support column thats taller than the diameter covered by the spinning blades.

Bigger means better when it comes to efficiency, so these turbines have gotten huge both on land and at sea. But there are some technical and design limitations to how big they can get. Their generators need to be located at their main axle near the top of the support tower. This adds a lot of weight at the top of the tower, which requires even more weight at the bottom (and significant strength along the towers entire height) to keep the whole thing from toppling over or bending in half.

The generator in a vertical-axis turbine, on the other hand, can be placed anywhere on said vertical axis; in an offshore context, this means it can be at the waterline or below, adding weight where weight is needed.

Vertical-axis turbines can also use wind coming from any direction. Since their rotation doesnt take up as much space as that of horizontal-axis turbines nor create as much of a blocking effect on downwind turbines, they can be placed closer together, generating more electricity in a given footprint.

SeaTwirl was founded in 2012, and for the past seven years its been proofing a test version of its vertical-axis turbine off the coast of Lysekil, a seaside town on Swedens western side. Called S1, the turbine has a generating capacity of 30 kilowatts, and its above-water portion is 43 feet (13 meters) tall, with another 59 feet (18 meters) submerged. It has fed an onshore grid throughout its trial period, while withstanding hurricane-level winds and waves.

With this success under its belt, SeaTwirl now wants to go biggera lot bigger. Its preparing to build a turbine called the S2x, which will be able to generate one megawatt of electricity and will serve as a pilot for the companys first commercial product.

The turbine will rise 180 feet (55 meters) out of the water, and its weighted central pole will reach 262 feet (80 meters) below the surface. Thats a total height of 442 feet. For perspective, the Statue of Liberty is 305 feet tall including the base and foundation. The vertical-axis turbine is still dwarfed by its horizontal-axis counterparts, though; GEs Haliade-X is 853 feet tall, and Chinese MingYang Smart Energy Group is building a turbine thats even a few feet taller.

The S2x will be placed in waters at least 328 feet deep, and designed to withstand category-two hurricane winds. SeaTwirl estimates the turbine will have a service life of 25 to 30 years, and the first one will be located off the coast of Bokn, Norway. Its expected to be commissioned in 2023 for a test period of around five years, and the company says it will generate energy at a cost thats competitive with other offshore turbines.

If the S2x is as successful as the S1, SeaTwirl will aim to scale up even more, possibly to turbines in the six to ten-megawatt range by 2025.

Image Credit: SeaTwirl

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A Swedish Company Wants to Transform Offshore Wind With Vertical-Axis Turbines - Singularity Hub

One of the main arguments against a rapid transition to renewable energy is the potentially enormous cost. But a new study shows that moving quickly could actually save us huge amounts of money compared to taking things slowly or doing nothing at all.

Models designed to estimate the economic impact of different energy scenarios, including those used by the Intergovernmental Panel on Climate Change, have consistently predicted that shifting from fossil fuels to greener alternatives like solar and wind would entail significant costs.

But researchers from Oxford University believe these predictions have also been consistently wrong. When projections made over the last 20 years are compared to real-world data, they systematically underestimate the cost reductions of key technologies and the pace of deployment around the world.

These findings prompted the team to see if they could find a better way to model the potential trajectories of future energy systems. By turning to the same kind of probabilistic modeling approaches used by the betting industry, they predicted that transitioning to a decarbonized energy system by around 2050 is expected to save the world at least $12 trillion, compared to continuing our current levels of fossil fuel use.

The belief that the green energy transition will be expensive has been a major driver of the ineffective response to climate change for the past 40 years, the authors wrote in a paper in Joule. This pessimism is at odds with past technological cost improvement trends and risks locking humanity into an expensive and dangerous energy future.

Relying on methods used by gambling companies rather than those favored by economists might seem like an odd decision, but the researchers point out that they must have some merit, as they make the industry billions in profits every year. Whats more, governments and companies are either implicitly or explicitly making bets on different energy technologies, so working out which bets have the best odds makes sense.

The approach they used has also been well validated. The team had previously used their probabilistic model to forecast the cost of 50 technologies and shown that it closely tracked historical data. In the latest study, they applied the same technique to technologies that will be critical to the green energy transition, like solar, wind, batteries, and electrolyzers for creating green hydrogen, as well as coal, gas, nuclear, biopower, and hydropower.

Their results show that a fast transition to renewable energy would save the global economy $12 trillion by 2050 compared to leaving the energy system the way it is today, while also producing 55 percent more energy than we do currently. They also investigated a slower transition, which they found would save less than the fast one but considerably more than the business-as-usual case.

Crucially, the model didnt take into account the cost of climate change itself, which would clearly favor a shift to renewables. The calculations are based purely on the underlying economics of the various energy technologies.

The study found that a rapid shift to a decarbonized energy system would entail significant increases in annual infrastructure costs due to the need for things like enhanced grid capacity. But the extra $140 billion this would cost per year was significantly less than the roughly $400 billion in annual savings on energy costs.

The researchers are keen to point out that their model is not aimed at finding optimal solutions, and its possible that in certain situations or localities it may make sense to retain some fossil fuels, for instance using gas rather than hydrogen fuel.

The modeling approach they use is also novel, and its far from certain whether key decision-makers will be willing to take their findings at face value. Nonetheless, they highlight the fact that todays accepted wisdom around the cost of a green energy transition is on shaky ground, and smarter bets on the future of energy could have some serious payoffs.

Image Credit: WikiImages / 1175 images

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Decarbonizing the Energy Sector by 2050 Could Save the World $12 Trillion - Singularity Hub

Last month, California became the first US state to ban the sale of combustion-engine cars after 2035. But its transition to electric vehicles will probably be tricky. The states electrical grid is experiencing instability even without the extra demand that will come from EVs; earlier this month, for example, parts of the Bay Area narrowly avoided rolling blackouts during a record-breaking heatwave.

But what if electric cars didnt need to plug into the grid to charge, cutting out the middle man and getting power straight from the sun? Aptera has had a solar car in the works for a couple years, and now another company says its hybrid solar-powered vehicle is ready for production.

Dutch startup Lightyear recently raised $81 million, and plans to put it towards getting its Lightyear 0 into customers waiting hands. The company was founded in 2016 by a team of engineers after they participated in the Bridgestone World Solar Challenge, a solar-car race in the Australian outback. Six years later, Lightyear has not only developed its first vehicle, it has reportedly pre-sold 150 of them at a price of 250,000.

The car has a 60 kilowatt-hour battery pack with 4 electric motors, and its exterior surface is decked out with 5 square meters (53.8 square feet) of double curve solar arrays. The 174-horsepower engine can reportedly take the car from 0 to 62 miles per hour in 10 seconds.

Lightyear says that when its fully charged the vehicle has a range of more than 600 miles, and in optimal sun conditions can power itself for up to 40 miles a day. If you live in a very sunny area and only drive a couple dozen miles each day, you could conceivably go weeks or even months without having to plug the car in.

The cars design is much more similar to what were used to cars looking like than the Aptera (which is also slated to start production this year). And the interior boasts its own set of planet- and user-friendly features, from plant-based leather and fabrics made from recycled bottles to phone-as-key capability and automatic software updates.

The company is planning to produce just under 1,000 of the vehicles to start, or maybe total. Because Lightyear 0 is intended as a technology demonstrator, we will produce it in limited quantities, Lightyears head of PR and communication Rachel Richardson told TechCrunch. The model will only be available to countries in the European Union, Norway, and Switzerland.

In conjunction with producing the Lightyear 0, though, the companys also developing a lower-cost successor called the Lightyear 2. Theyre aiming to bring this model to market by 2025 at a much-lower starting price of 30,000, and say theyve already received 10,000 reservations from leasing and car-sharing companies.

Richardson pointed out that consumers arent going to rush to buy solar cars until theyre a bit more financially accessible, and even then, adoption will likely be limited to geographically logical placesthat is, regions that get a lot of sun. The industry needs to be certain of the viability of the technology to produce it at scale, she said. This is our aim with Lightyear 0to show that clean mobility is a reality and it is ready, it is not a thing of the future.

Image Credit: Lightyear

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This Sleek Solar Car Goes 600 Miles on a Charge and Is Gearing Up for Production - Singularity Hub

Being able to decode brainwaves could help patients who have lost the ability to speak to communicate again, and could ultimately provide novel ways for humans to interact with computers. Now Meta researchers have shown they can tell what words someone is hearing using recordings from non-invasive brain scans.

Our ability to probe human brain activity has improved significantly in recent decades as scientists have developed a variety of brain-computer interface (BCI) technologies that can provide a window into our thoughts and intentions.

The most impressive results have come from invasive recording devices, which implant electrodes directly into the brains gray matter, combined with AI that can learn to interpret brain signals. In recent years, this has made it possible to decode complete sentences from someones neural activity with 97 percent accuracy, and translate attempted handwriting movements directly into text at speeds comparable to texting.

But having to implant electrodes into someones brain has obvious downsides. These risky procedures are only medically justifiable for patients who require brain recording to help resolve other medical issues, such as epilepsy. And neural probes degrade over time, which raises the prospect of having to regularly replace them.

Thats why researchers at Metas AI research division decided to investigate whether they could achieve similar goals without requiring dangerous brain surgery. In a paper published on the pre-print server arXiv, the team reported that theyve developed an AI system that can predict what words someone is listening to based on brain activity recorded using non-invasive brain-computer interfaces.

Its obviously extremely invasive to put an electrode inside someones brain, Jean Remi King, a research scientist at Facebook Artificial Intelligence Research (FAIR) Lab, told TIME. So we wanted to try using noninvasive recordings of brain activity. And the goal was to build an AI system that can decode brain responses to spoken stories.

The researchers relied on four pre-existing brain activity datasets collected from 169 people as they listened to recordings of people speaking. Each volunteer was recorded using either magneto-encephalography (MEG) or electro-encephalography (EEG), which use different kinds of sensors to pick up the electrical activity of the brain from outside the skull.

Their approach involved splitting the brain and audio data into three-second-long snippets and feeding it into a neural network that then looked for patterns that could connect the two. After training the AI on many hours of this data, they then tested it on previously unseen data.

The system performed the best on one of the MEG datasets, where it achieved a top-10 accuracy of 72.5 percent. That means that when it ranked the 10 words with the highest probability of being linked to the brain wave segment, the correct word was there 72.5 percent of the time.

That might not sound great, but its important to remember that it was picking from a potential vocabulary of 793 words. The system scored 67.2 percent on the other MEG dataset, but fared less well on the EEG datasets, getting top-10 accuracies of only 31.4 and 19.1.

Clearly this is still a long way from a practical system, but it represents significant progress on a hard problem. Non-invasive BCIs have much worse signal-to-noise ratios, so deciphering neural activity this way is challenging, but if successful could result in a far more widely applicable technology.

Not everyone is convinced its a solvable problem, though. Thomas Knopfel from Imperial College London told New Scientist that trying to probe thoughts using these non-invasive approaches was like trying to stream an HD movie over old-fashioned analogue telephone modems, and questioned whether such approaches will ever reach practical accuracy levels.

Companies like Elon Musks Neuralink are also betting that well eventually get over our squeamishness around invasive approaches as the technology improves, opening the door to everyday people getting brain implants.

But the research from the team at Meta is at the very early stages, and there is plenty of scope for improvements. And the commercial opportunities for anyone who can crack non-invasive brain scanning will likely provide plenty of motivation for trying.

Image Credit: Dung TranfromPixabay

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Meta Built an AI That Can Guess the Words You're Hearing by Decoding Your Brainwaves - Singularity Hub

After being in Steam Early Access for the past two years, Bounding Box Softwares Prodeus will finally be launching its 1.0 version this Thursday for PC and consoles. The throwback FPS will arrive September 23 for the PlayStation 5, PlayStation 4, Xbox Series, Xbox One, the Nintendo Switch, and PC via Steam. Prodeus will also be available for the Xbox Game Pass.

Per the devs, the full 1.0 release will include new maps and weapons, full multiplayer co-op with up to 4 players, new level editor features and much much more. That also includes a level editor, though that is only available for the PC version. Despite that, players can upload their creations to be enjoyed by console and PC players alike.

Described as a first-person shooter of old, but re-imagined using modern rendering techniques and technology, Prodeus story is short and to the point: the player steps into the boots of a corrupted agent of Prodeus, the mysterious creator of the player and the game world. The only goal is to destroyProdeusand anything that gets in the way.

Created by Mike Voeller and Jason Mojica, who previously worked on titles such as Singularity, Bioshock Infinite, and Wolfenstein, Prodeus also features music by Andrew Hulshult.

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Gory Throwback FPS 'Prodeus' Exits Early Access This Thursday, Launching for PC and Consoles [Trailer] - Bloody Disgusting

The Vespera telescope offers power and portability in a small deep-sky imaging package.

A great new telescope just got smaller and more portable. The French-based company Vaonis released its newest addition to their smartscope family this week: the Vespera telescope. The small pill-shaped instrument joins the Stellina and the (forthcoming) Hyperia line, offering a lower price point and backpack portability without a compromise in quality.

Whats New with Vespera

Standing just 15 (40cm) high and weighing in at 11 lbs (5 kilograms) The Vespera is an alt-az system mounted on a single swing arm. Like the Stellina, the Vespera is controlled by Vaonis new and upgraded Singularity App, available for both Iphone and Android. The App allows users to plan their observing session, control the telescope and take and share images. The user can also manually load coordinates, handy for adding in new novae or comets into the database.

The Vespera can accommodate a small hygrometer (dew) sensor to be installed by the user after delivery, and a light pollution filter (both sold separately). The company plans to begin offering a solar filter for the Vespera by late 2022.

Using the Vespera in the field is a simple (if a bit slow) process; after hooking the scope up to the phones WiFi and initializing the station, Vespera will begin to hunt for familiar star patterns in the sky. The system works off of satellite GPS and a method known as plate-solving, comparing star patterns in the sky with its memory database.

Note that the WiFi connection also temporarily kills the mobile data connection for the phone. Our field test suggests that the WiFi is good up to about 25 feet away, and the Vespera can be paired with multiple devices (phones, tablets, etc).

Portability makes the Vespera a joy to use. The scope is light enough for an easy hilltop hike, and sets up quickly. The telescope has about four hours of continuous battery life, though it uses its own special magnetic coupling charger, often seen these days on many smart-watches actually, Im surprised the Vespera uses this style of charging connector, as the European Union has mandated that all chargers will be USB-C by late 2024.

Technical specs- The Vespera is built around a 50-mm quadruplet achromatic refractor telescope, coupled with a two megapixel imager and 100 gigabytes of storage. After alignment and target acquisition, the image slowly builds up on the smartphone screen; the longer it stares at an object, the more signal is gathered versus noise, and the sharper the image appears.

What we like- The true power of Vespera and other smartscopes is that it puts deep-sky imaging in the hands of suburbanite amateur astronomers; I could go after bright Messier globulars and targets from washed-out downtown skies that I probably would otherwise not bother to try for otherwise. But its under truly dark skies that the Vespera shines. I can easily capture dark lanes in the Andromeda Galaxy (M31) after just a few minutes of exposure, and the Veil Nebula is Cygnus was a worthy target. We even had a chance to use the Vespera to follow an icy interloper in the inner solar system this summer, Comet C/2017 K2 PanSTARRS. In fact, wed go as far as to say the tiny Vespera nearly does as well as its much larger sibling Stellina in terms of astro-imaging.

What we dont like- As mentioned, the Vespera is extremely slow in terms of initialization, fine-focusing, target acquisition and imaging; all of this is automatic, but a bit tedious; a live view feature would be great. I found that occasionally, the initial images were just a touch out of focus (most likely, due to the optics cooling down to the ambient temperature) and a pass back through the initialization process was needed to attain a fine focus. Also, the blue-circle power button, while stylish, was also prone to turning on with the slightest brush or touch, potentially allowing the telescope to remain turned on in storage, draining precious battery power.

The rise of the smartscopes like the Vespera and their ilk represent the future of amateur astronomy; I look forward to the day when we can live-stream the view from the remote Moroccan desert, via smartscope and Starlink connection. At $2,499 dollars USD retail, the Vespera is still a bit on the high-end but the price is definitely moving in the right direction.

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Meet the New Vespera Telescope From Vaonis - Universe Today

This article was featured in One Story to Read Today, a newsletter in which our editors recommend a single must-read from The Atlantic, Monday through Friday. Sign up for it here.

Miracles can be perplexing at first, and artificial intelligence is a very new miracle. Were creating God, the former Google Chief Business Officer Mo Gawdat recently told an interviewer. Were summoning the demon, Elon Musk said a few years ago, in a talk at MIT. In Silicon Valley, good and evil can look much alike, but on the matter of artificial intelligence, the distinction hardly matters. Either way, an encounter with the superhuman is at hand.

Early artificial intelligence was simple: Computers that played checkers or chess, or that could figure out how to shop for groceries. But over the past few years, machine learningthe practice of teaching computers to adapt without explicit instructionshas made staggering advances in the subfield of Natural Language Processing, once every year or so. Even so, the full brunt of the technology has not arrived yet. You might hear about chatbots whose speech is indistinguishable from humans, or about documentary makers re-creating the voice of Anthony Bourdain, or about robots that can compose op-eds. But you probably dont use NLP in your everyday life.

Or rather: If you are using NLP in your everyday life, you might not always know. Unlike search or social media, whose arrivals the general public encountered and discussed and had opinions about, artificial intelligence remains esotericevery bit as important and transformative as the other great tech disruptions, but more obscure, tucked largely out of view.

Science fiction, and our own imagination, add to the confusion. We just cant help thinking of AI in terms of the technologies depicted in Ex Machina, Her, or Blade Runnerpeople-machines that remain pure fantasy. Then theres the distortion of Silicon Valley hype, the general fake-it-til-you-make-it atmosphere that gave the world WeWork and Theranos: People who want to sound cutting-edge end up calling any automated process artificial intelligence. And at the bottom of all of this bewilderment sits the mystery inherent to the technology itself, its direct thrust at the unfathomable. The most advanced NLP programs operate at a level that not even the engineers constructing them fully understand.

But the confusion surrounding the miracles of AI doesnt mean that the miracles arent happening. It just means that they wont look how anybody has imagined them. Arthur C. Clarke famously said that technology sufficiently advanced is indistinguishable from magic. Magic is coming, and its coming for all of us.

All technology is, in a sense, sorcery. A stone-chiseled ax is superhuman. No arithmetical genius can compete with a pocket calculator. Even the biggest music fan you know probably cant beat Shazam.

But the sorcery of artificial intelligence is different. When you develop a drug, or a new material, you may not understand exactly how it works, but you can isolate what substances you are dealing with, and you can test their effects. Nobody knows the cause-and-effect structure of NLP. Thats not a fault of the technology or the engineers. Its inherent to the abyss of deep learning.

I recently started fooling around with Sudowrite, a tool that uses the GPT-3 deep-learning language model to compose predictive text, but at a much more advanced scale than what you might find on your phone or laptop. Quickly, I figured out that I could copy-paste a passage by any writer into the programs input window and the program would continue writing, sensibly and lyrically. I tried Kafka. I tried Shakespeare. I tried some Romantic poets. The machine could write like any of them. In many cases, I could not distinguish between a computer-generated text and an authorial one.

A quotation from this story, as interpreted and summarized by Googles OpenAI software.

I was delighted at first, and then I was deflated. I was once a professor of Shakespeare; I had dedicated quite a chunk of my life to studying literary history. My knowledge of style and my ability to mimic it had been hard-earned. Now a computer could do all that, instantly and much better.

A few weeks later, I woke up in the middle of the night with a realization: I had never seen the program use anachronistic words. I left my wife in bed and went to check some of the texts Id generated against a few cursory etymologies. My bleary-minded hunch was true: If you asked GPT-3 to continue, say, a Wordsworth poem, the computers vocabulary would never be one moment before or after appropriate usage for the poems era. This is a skill that no scholar alive has mastered. This computer program was, somehow, expert in hermeneutics: interpretation through grammatical construction and historical context, the struggle to elucidate the nexus of meaning in time.

The details of how this could be are utterly opaque. NLP programs operate based on what technologists call parameters: pieces of information that are derived from enormous data sets of written and spoken speech, and then processed by supercomputers that are worth more than most companies. GPT-3 uses 175 billion parameters. Its interpretive power is far beyond human understanding, far beyond what our little animal brains can comprehend. Machine learning has capacities that are real, but which transcend human understanding: the definition of magic.

This unfathomability poses a spiritual conundrum. But it also poses a philosophical and legal one. In an attempt to regulate AI, the European Union has proposed transparency requirements for all machine-learning algorithms. Eric Schmidt, the ex-CEO of Google, noted that such requirements would effectively end the development of the technology. The EUs plan requires that the system would be able to explain itself. But machine-learning systems cannot fully explain how they make their decisions, he said at a 2021 summit. You use this technology to think through what you cant; thats the whole point. Inscrutability is an industrial by-product of the process.

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My little avenue of literary exploration is my own, and neither particularly central nor relevant to the unfolding power of artificial intelligence (although I can see, off the top of my head, that the tech I used will utterly transform education, journalism, film, advertising, and publishing). NLP has made its first strides into visual arts tooDall-E 2 has now created a limitless digital museum of AI-generated images drawn from nothing more than prompts.

Others have headed into deeper waters. Schmidt recently proposed a possible version of our AI future in a conversation with this magazines executive editor, Adrienne LaFrance: If you imagine a child born today, you give the child a baby toy or a bear, and that bear is AI-enabled, he said. And every year the child gets a better toy. Every year the bear gets smarter, and in a decade, the child and the bear who are best friends are watching television and the bear says, I dont really like this television show. And the kid says, Yeah, I agree with you.

Schmidts vision does not yet exist. But in late 2020, Microsoft received a patent for chatbots that bring back the dead, using inputs from images, voice data, social media posts, electronic messages, written letters, etc. to create or modify a special index in the theme of the specific persons personality. Soon after, a company called Project December released a version of just such a personality matrix. It created bots such as William, which speaks like Shakespeare, and Samantha, a rather bland female companion. But it also allowed mourners to re-create dead loved ones. An article in the San Francisco Chronicle told the story of Joshua Barbeau, who created a bot of his deceased fiance, Jessica Pereira. Their conversation started like this:

Joshua: Technically, Im not really talking to you

Jessica: Huh?

Joshua: Youre a ghost.

Jessica: *looks at herself* How?

Joshua: Magic.

Jessica: I dont like magic. Where am I?

Joshua: Im Not sure. The internet? Where does it feel like you are?

Jessica: *smiles* Everywhere and nowhere. *cups her head with her hands* I am trying to work that out. How are you, honey?

Barbeaus conversation with Jessica continued for several months. His experience of Project December was far from perfectthere were glitches, there was nonsense, the bots architecture decayedbut Barbeau really felt like he was encountering some kind of emanation of his dead fiance. The technology, in other words, came to occupy a place formerly reserved for mediums, priests, and con artists. It may not be the first intelligent machine, Jason Rohrer, the designer of Project December, has said, but it kind of feels like its the first machine with a soul.

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What we are doing is teaching computers to play every language game that we can identify. We can teach them to talk like Shakespeare, or like the dead. We can teach them to grow up alongside our children. We can certainly teach them to sell products better than we can now. Eventually, we may teach them how to be friends to the friendless, or doctors to those without care.

PaLM, Googles latest foray into NLP, has 540 billion parameters. According to the engineers who built it, it can summarize text, reason through math problems, use logic in a way thats not dissimilar from the way you and I do. These engineers also have no idea why it can do these things. Meanwhile, Google has also developed a system called Player of Games, which can be used with any game at allgames like Go, exercises in pure logic that computers have long been good at, but also games like poker, where each party has different information. This next generation of AI can toggle back and forth between brute computation and human qualities such as coordination, competition, and motivation. It is becoming an idealized solver of all manner of real-world problems previously considered far too complicated for machines: congestion planning, customer service, anything involving people in systems. These are the extremely early green shoots of an entire future tech ecosystem: The technology that contemporary NLP derives from was only published in 2017.

And if AI harnesses the power promised by quantum computing, everything Im describing here would be the first dulcet breezes of a hurricane. Ersatz humans are going to be one of the least interesting aspects of the new technology. This is not an inhuman intelligence but an inhuman capacity for digital intelligence. An artificial general intelligence will probably look more like a whole series of exponentially improving tools than a single thing. It will be a whole series of increasingly powerful and semi-invisible assistants, a whole series of increasingly powerful and semi-invisible surveillance states, a whole series of increasingly powerful and semi-invisible weapons systems. The world would change; we shouldnt expect it to change in any kind of way that you would recognize.

Our AI future will be weird and sublime and perhaps we wont even notice it happening to us. The paragraph above was composed by GPT-3. I wrote up to And if AI harnesses the power promised by quantum computing; machines did the rest.

Technology is moving into realms that were considered, for millennia, divine mysteries. AI is transforming writing and artthe divine mystery of creativity. It is bringing back the deadthe divine mystery of resurrection. It is moving closer to imitations of consciousnessthe divine mystery of reason. It is piercing the heart of how language works between peoplethe divine mystery of ethical relation.

All this is happening at a raw moment in spiritual life. The decline of religion in America is a sociological fact: Religious identification has been in precipitous decline for decades. Silicon Valley has offered two replacements: the theory of the simulation, which postulates that we are all living inside a giant computational matrix, and of the singularity, in which the imminent arrival of a computational consciousness will reconfigure the essence of our humanity.

Like all new faiths, the tech religions cannibalize their predecessors. The simulation is little more than digital Calvinism, with an omnipotent divinity that preordains the future. The singularity is digital messianism, as found in various strains of Judeo-Christian eschatologya pretty basic onscreen Revelation. Both visions are fundamentally apocalyptic. Stephen Hawking once said that the development of full artificial intelligence could spell the end of the human race. Experts in AI, even the men and women building it, commonly describe the technology as an existential threat.

But we are shockingly bad at predicting the long-term effects of technology. (Remember when everybody believed that the internet was going to improve the quality of information in the world?) So perhaps, in the case of artificial intelligence, fear is as misplaced as that earlier optimism was.

AI is not the beginning of the world, nor the end. Its a continuation. The imagination tends to be utopian or dystopian, but the future is humanan extension of what we already are. My own experience of using AI has been like standing in a river with two currents running in opposite directions at the same time: Alongside a vertiginous sense of power is a sense of humiliating disillusionment. This is some of the most advanced technology any human being has ever used. But of 415 published AI tools developed to combat COVID with globally shared information and the best resources available, not one was fit for clinical use, a recent study found; basic errors in the training data rendered them useless. In 2015, the image-recognition algorithm used by Google Photos, outside of the intention of its engineers, identified Black people as gorillas. The training sets were monstrously flawed, biased as AI very often is. Artificial intelligence doesnt do what you want it to do. It does what you tell it to do. It doesnt see who you think you are. It sees what you do. The gods of AI demand pure offerings. Bad data in, bad data out, as they say, and our species contains a great deal of bad data.

Artificial intelligence is returning us, through the most advanced technology, to somewhere primitive, original: an encounter with the permanent incompleteness of consciousness. Religions all have their approaches to magictransubstantiation for Catholics, the lost temple for the Jews. Even in the most scientific cultures, there is always the beyond. The acropolis in Athens was a fortress of wisdom, a redoubt of knowledge and the power it bringsthrough agriculture, through military victory, through the control of nature. But if you wanted the inchoate truth, you had to travel the road to Delphi.

A fragment of humanity is about to leap forward massively, and to transform itself massively as it leaps. Another fragment will remain, and look much the same as it always has: thinking meat in an inconceivable universe, hungry for meaning, gripped by fascination. The machines will leap, and the humans will look. They will answer, and we will question. The glory of what they can do will push us closer and closer to the divine. They will do things we never thought possible, and sooner than we think. They will give answers that we ourselves could never have provided. But they will also reveal that our understanding, no matter how great, is always and forever negligible. Our role is not to answer but to question, and to let our questioning run headlong, reckless, into the inarticulate.

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Of God and Machines - The Atlantic

For thousands of years humans have destroyed forests. At the end of the last great ice age, an estimated 57 percent of the worlds habitable land was forested.1 Since then, people in all regions of the world have burned and cut down forests. The chart below shows this. The forested land area declined from six to four billion hectares. That means our ancestors destroyed one-third of the former forests;a forest area twice the size of the US was lost.

There are two big reasons why humans have destroyed forests and continue to do so: the need for land and the need for wood.

The land use for farming did not only come at the expense of the worlds forests, but also led to the huge decline of the worlds other wild spaces, the shrub- and grasslands. The chart shows this too.

In many countries forests continue to be destroyed. The series of charts shows this. In all of these countries the forest cover today is lower than three decades ago.3

Most of the forests that are destroyed today are in the tropics, some of the most biodiverse regions on our planet. Why is this happening?

The following chart shows what is driving the ongoing destruction of the worlds largest tropical forest: the Amazon. The expansion of agricultural land to raise cattle is the most important driver, by far.4

I wish this was more widely understood. Land use for agriculture is the main threat to the worlds biodiversity.5

Most of the destruction of tropical forests is due to consumers in the region, butabout 12 percent of the deforestationin the tropics is driven by demand from high-income countries. Beef-eaters around the world are contributing to the destruction of the Amazon rainforest.6

This huge impact of meat consumption on deforestation is also visible in the first chart that showed the history over the last 10 millennia. 31 percent of the worlds habitable land is now grazing land for livestock. This is an extremely large part of the world; taken together it is as large asall of the Americas, from Alaska in the north down to Tierra del Fuego in the south.

Meat consumption is such a large driver of deforestation because it is a very inefficient way to produce food. The land use of meat production ismuch higher than plant-based foods. Reducing meat consumption is therefore a way to increase the agricultural output per land area. A shift away from the land-intensive production of meat, especially beef, would be a major way to make progress and end deforestation. One possible way to get there is to make clear how large the environmental impact of meat production is. Another complementing way is to produce meat substitutes that people prefer over beef.

After thousands of years of deforestation, is there any hope that it could be different?

Yes.

In fact, there are many countries that brought their history of deforestation to an end. Several even turned it around so that forests there are now expanding.

This reversal, from deforestation to reforestation, is called aForest Transition. The chart below shows the data for some of the countries that have achieved this.7

As mentioned before, while it is the case that several countries have achieved this transition, it is also the case that consumers in these countries contribute to deforestation elsewhere.

Crucial for these turnarounds was technological progress that reduced the demand for fuelwood and agricultural land.

These two technological changes can be complemented by effective policies and regulations. Zero-deforestation policies restrict deforestation, and programs like REDD+of the FAO compensate poorer countries and farmers to make forest protection economically more attractive than deforestation.8

Can We Achieve a Global Forest Transition in Our Lifetime?

If we want to protect our planets forests, the world as a whole would need to achieve what many countries have achieved already, the turnaround from deforestation to reforestation a global forest transition.

Countries around the world have made the end of deforestation their explicit goal. At COP26 in Glasgow, countries with about 85 percent of the worlds forests pledged to end deforestation by 2030.

The last chart shows where the world is in this effort.

The brown part of the chart shows the history of the temperate forests. These forests as a whole have achieved the transition: deforestation was high in the past, then peaked in the first half of the 20th century, and from the 1990s onwards temperate forests have expanded in size. Temperate forests are growing back.

The challenge is now to achieve the same in tropical forests, which are shown in green. We are making progress in this direction: the rate of deforestation in the tropics was highest in the 1980s. Since then, the rate of deforestation has declined by a factor of three.

If we can further decrease the demand for fuelwood and agricultural land, it seems possible to bring deforestation in the tropics to an end.

If we achieve the global forest transition in our lifetimes, it would be a major success for the protection of the worlds biodiversity. Additionally, it would bring greenhouse gas emissions from deforestation to an end, and expanding rather than shrinking forests would instead suck more carbon out of the atmosphere.

How can we bring deforestation to an end? There is no single answer, but as we have seen, a few big changes can bring this big goal into reach.

More productive agriculture that allows more production on a smaller land area, a shift away from meat, effective conservation policies, and a shift to modern energy sources: by bringing all of these factors together we could get there. Not only would we save existing forests from being cut down, we might also free up space for forests to grow back.

In our lifetime we have the unprecedented opportunity to bring our long history of deforestation to an end. For the first time in millennia we could achieve a world in which forests expand.

This article was originally published onOur World in Dataand has been republished here under a Creative Commons license. Read theoriginal article.

Image Credit: Lillac/Shutterstock.com

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Humans Destroyed Forests for Thousands of Years. We Can Become the First Generation to Expand Them - Singularity Hub

The Intel Core i9-13900K hasn't yet been announced, but a reviewer in China has already shared a comprehensive set of test results from an early sample. Many gaming benchmarks were included in these tests, showing the Core i9-13900K outperforming its predecessorby +10% in specific cases.

The review comes from ECSM_Official (via VideoCardz). The whole review is based on comparing the Core i9-12900K and the Core i9-13900K running with unlimited power. Performance figures were gathered using DDR4 (DDR4-3600 CL17-19-19-39) and DDR5 (DDR5-6000 CL30-38-38-76) memory. The Core i9-12900K system was running an ASRock Z690 Taichi Razer Edition (12.01 BIOS), while the other used an undisclosed Z790 board. Both CPUs were cooled using an NZXT Kraken X73. For graphics, the reviewer used an overclocked AMD Radeon RX 6900 XTXH.

Image credit: ECSM_Official

Jumping straight into the benchmark results, we see the Core i9-13900K is over 40% faster in multi-threaded workloads, including Cinebench (multiple versions), CPU-Z, Winrar, 7z, and SuperPI. The new P-cores used on the Raptor Lake flagship also showed to be quite capable, outperforming 12th Gen's P-cores by 13%. The E-cores performed similarly when using DDR4 memory, but became 6% faster while using DDR5 memory.

As far as games go, CPU-bound titles like CS:GO and Ashes of the Singularity show that the Core i9-13900K performs 10% higher than the 12900K at 1080p. Those performance gains become less noticeable at 1440p.

At stock settings, the reviewer concluded that the Raptor Lake chip could push up to 253W of power (PL2). Once the power limit was removed, maximum power consumption increased to 343W (1.4V). With these settings, the eight P-cores were pushed to 5.5GHz, while the 16 E-cores peaked at 4.3GHz.

Intel is expected to announce its 13th Gen Core desktop processors at Intel Innovation on the 27th of September.

KitGuru says: Do you think a +10% performance boost in specific games is enough to justify an upgrade from a Core i9-12900K to an i9-13900K? Were you expecting a more significant performance leap between the two chips?

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Intel Core i9-13900K beats the 12900K by +10% in CPU-bound games - KitGuru

LOS ANGELES--(BUSINESS WIRE)--The Schall Law Firm, a national shareholder rights litigation firm, announces that it is investigating claims on behalf of investors of Singularity Future Technology Ltd. (Singularity or the Company) (NASDAQ: SGLY) for violations of the securities laws.

The investigation focuses on whether the Company issued false and/or misleading statements and/or failed to disclose information pertinent to investors. Singularity announced on August 12, 2022, that CEO Yang Jie had resigned from the Company after being suspended by its Board of Directors. The suspension was based on the recommendation of a special committee that was formed to investigate allegations raised by Hindenburg Research in a May 2022 report. Hindenburg alleged that Jie had run a ponzi scheme in China before fleeing to the United States. The research report also made allegations about the Companys recent bitcoin mining deal with Golden Mainland Inc., stating we also found no evidence that Golden Mainland has a headquarters or any employees aside from its founder, who used a Gmail address on the SEC filing detailing the supposed $250 million deal. We believe Golden Mainland is a blatant fabrication.

If you are a shareholder who suffered a loss, click here to participate.

We also encourage you to contact Brian Schall of the Schall Law Firm, 2049 Century Park East, Suite 2460, Los Angeles, CA 90067, at 310-301-3335, to discuss your rights free of charge. You can also reach us through the firm's website at http://www.schallfirm.com, or by email at bschall@schallfirm.com.

The class in this case has not yet been certified, and until certification occurs, you are not represented by an attorney. If you choose to take no action, you can remain an absent class member.

The Schall Law Firm represents investors around the world and specializes in securities class action lawsuits and shareholder rights litigation.

This press release may be considered Attorney Advertising in some jurisdictions under the applicable law and rules of ethics.

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INVESTIGATION ALERT: The Schall Law Firm Encourages Investors in Singularity Future Technology Ltd. with Losses of $100000 to Contact the Firm -...