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It’s an evening in 1531, in the city of Venice. In a printer’s workshop, an apprentice labors over the layout of a page that’s destined for an astronomy textbook—a dense line of type and a woodblock illustration of a cherubic head observing shapes moving through the cosmos, representing a lunar eclipse.

Like all aspects of book production in the 16th century, it’s a time-consuming process, but one that allows knowledge to spread with unprecedented speed.

Five hundred years later, the production of information is a different beast entirely: terabytes of images, video, and text in torrents of digital data that circulate almost instantly and have to be analyzed nearly as quickly, allowing—and requiring—the training of machine-learning models to sort through the flow. This shift in the production of information has implications for the future of everything from art creation to drug development.

But those advances are also making it possible to look differently at data from the past. Historians have started using machine learning—deep neural networks in particular—to examine historical documents, including astronomical tables like those produced in Venice and other early modern cities, smudged by centuries spent in mildewed archives or distorted by the slip of a printer’s hand.

Historians say the application of modern computer science to the distant past helps draw connections across a broader swath of the historical record than would otherwise be possible, correcting distortions that come from analyzing history one document at a time. But it introduces distortions of its own, including the risk that machine learning will slip bias or outright falsifications into the historical record. All this adds up to a question for historians and others who, it’s often argued, understand the present by examining history: With machines set to play a greater role in the future, how much should we cede to them of the past?

Parsing complexity

Big data has come to the humanities throughinitiatives to digitize increasing numbers of historical documents, like the Library of Congress’s collection of millions of newspaper pages and the Finnish Archives’ court records dating back to the 19th century. For researchers, this is at once a problem and an opportunity: there is much more information, and often there has been no existing way to sift through it.

That challenge has been met with the development of computational tools that help scholars parse complexity. In 2009, Johannes Preiser-Kapeller, a professor at the Austrian Academy of Sciences, was examining a registry of decisions from the 14th-century Byzantine Church. Realizing that making sense of hundreds of documents would require a systematic digital survey of bishops’ relationships, Preiser-Kapeller built a database of individuals and used network analysis software to reconstruct their connections.

This reconstruction revealed hidden patterns of influence, leading Preiser-Kapeller to argue that the bishops who spoke the most in meetings weren’t the most influential; he’s since applied the technique to other networks, including the 14th-century Byzantian elite, uncovering ways in which its social fabric was sustained through the hidden contributions of women. “We were able to identify, to a certain extent, what was going on outside the official narrative,” he says.

Preiser-Kapeller’s work is but one example of this trend in scholarship. But until recently, machine learning has often been unable to draw conclusions from ever larger collections of text—not least because certain aspects of historical documents (in Preiser-Kapeller’s case, poorly handwritten Greek) made them indecipherable to machines. Now advances in deep learning have begun to address these limitations, using networks that mimic the human brain to pick out patterns in large and complicated data sets.

Nearly 800 years ago, the 13th-century astronomer Johannes de Sacrobosco published the Tractatus de sphaera, an introductory treatise on the geocentric cosmos. That treatise became required reading for early modern university students. It was the most widely distributed textbook on geocentric cosmology, enduring even after the Copernican revolution upended the geocentric view of the cosmos in the 16th century.

The treatise is also the star player in a digitized collection of 359 astronomy textbooks published between 1472 and 1650—76,000 pages, including tens of thousands of scientific illustrations and astronomical tables. In that comprehensive data set, Matteo Valleriani, a professor with the Max Planck Institute for the History of Science, saw an opportunity to trace the evolution of European knowledge toward a shared scientific worldview. But he realized that discerning the pattern required more than human capabilities. So Valleriani and a team of researchers at the Berlin Institute for the

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By: Moira Donovan
Title: How AI is helping historians better understand our past
Sourced From: www.technologyreview.com/2023/04/11/1071104/ai-helping-historians-analyze-past/
Published Date: Tue, 11 Apr 2023 09:00:00 +0000

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Scaling green hydrogen technology for the future

Thyssenkrupp Nucera green

Unlike conventional energy sources, green hydrogen offers a way to store and transfer energy without emitting harmful pollutants, positioning it as essential to a sustainable and net-zero future. By converting electrical power from renewable sources into green hydrogen, these low-carbon-intensity energy storage systems can release clean, efficient power on demand through combustion engines or fuel cells. When produced emission-free, hydrogen can decarbonize some of the most challenging industrial sectors, such as steel and cement production, industrial processes, and maritime transport.

Thyssenkrupp Nucera green hydrogen 1200px 1

“Green hydrogen is the key driver to advance decarbonization,” says Dr. Christoph Noeres, head of green hydrogen at global electrolysis specialist thyssenkrupp nucera. This promising low-carbon-intensity technology has the potential to transform entire industries by providing a clean, renewable fuel source, moving us toward a greener world aligned with industry climate goals.

ccelerating production of green hydrogen

Hydrogen is the most abundant element in the universe, and its availability is key to its appeal as a clean energy source. However, hydrogen does not occur naturally in its pure form; it is always bound to other elements in compounds like water (H2O). Pure hydrogen is extracted and isolated from water through an energy-intensive process called conventional electrolysis.

Hydrogen is typically produced today via steam-methane reforming, in which high-temperature steam is used to produce hydrogen from natural gas. Emissions produced by this process have implications for hydrogen’s overall carbon footprint: worldwide hydrogen production is currently responsible for as many CO2 emissions as the United Kingdom and Indonesia combined.

A solution lies in green hydrogen—hydrogen produced using electrolysis powered by renewable sources. This unlocks the benefits of hydrogen without the dirty fuels. Unfortunately, very little hydrogen is currently powered by renewables: less than 1% came from non-fossil fuel sources in 2022.

A massive scale-up is underway. According to McKinsey, an estimated 130 to 345 gigawatts (GW) of electrolyzer capacity will be necessary to meet the green hydrogen demand by 2030, with 246 GW of this capacity already announced. This stands in stark contrast to the current installed base of just 1.1 GW. Notably, to ensure that green hydrogen constitutes at least 14% of total energy consumption by 2050, a target that the International Renewable Energy Agency (IRENA) estimates is required to meet climate goals, 5,500 GW of cumulative installed electrolyzer capacity will be required.

However, scaling up green hydrogen production to these levels requires overcoming cost and infrastructure constraints. Becoming cost-competitive means improving and standardizing the technology, harnessing the scale efficiencies of larger projects, and encouraging government action to create market incentives. Moreover, the expansion of renewable energy in regions with significant solar, hydro, or wind energy potential is another crucial factor in lowering renewable power prices and, consequently, the costs of green hydrogen.

Electrolysis innovation

While electrolysis technologies have existed for decades, scaling them up to meet the demand for clean energy will be essential. Alkaline Water Electrolysis (AWE), the most dominant and developed electrolysis method, is poised for this transition. It has been utilized for decades, demonstrating efficiency and reliability in the chemical industry. Moreover, it is more cost effective than other electrolysis technologies and is well suited to be run directly with fluctuating renewable power input. Especially for large-scale applications, AWE demonstrates significant advantages in terms of investment and operating costs. “Transferring small-scale manufacturing and optimizing it towards mass manufacturing will need a high level of investment across the industry,” says Noeres.

Industries that already practice electrolysis, as well as those that already use hydrogen, such as fertilizer production, are well poised for conversion to green hydrogen. For example, thyssenkrupp nucera benefits from a decades-long heritage using electrolyzer technology in the

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By: MIT Technology Review Insights
Title: Scaling green hydrogen technology for the future
Sourced From: www.technologyreview.com/2024/06/18/1092956/scaling-green-hydrogen-technology-for-the-future/
Published Date: Tue, 18 Jun 2024 14:00:00 +0000

Did you miss our previous article…
https://mansbrand.com/the-download-ais-limitations/

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The Download: AI’s limitations

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This is today’s edition of The Download our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Why does AI hallucinate?

The World Health Organization’s new chatbot launched on April 2 with the best of intentions. The virtual avatar named SARAH, was designed to dispense health tips about how to eat well, quit smoking, de-stress, and more, for millions around the world. But like all chatbots, SARAH can flub its answers. It was quickly found to give out incorrect information. In one case, it came up with a list of fake names and addresses for nonexistent clinics in San Francisco.

Chatbot fails are now a familiar meme. Meta’s short-lived scientific chatbot Galactica made up academic papers and generated wiki articles about the history of bears in space. In February, Air Canada was ordered to honor a refund policy invented by its customer service chatbot. Last year, a lawyer was fined for submitting court documents filled with fake judicial opinions and legal citations made up by ChatGPT.

This tendency to make things up—known as hallucination—is one of the biggest obstacles holding chatbots back from more widespread adoption. Why do they do it? And why can’t we fix it? Read the full story.

—Will Douglas Heaven

Will’s article is the latest entry in MIT Technology Review Explains, our series explaining the complex, messy world of technology to help you understand what’s coming next. You can check out the rest of the series here

The story is also from the forthcoming magazine issue of MIT Technology Review, which explores the theme of Play. It’s set to go live on Wednesday June 26, so if you don’t already, subscribe now to get a copy when it lands.

Why artists are becoming less scared of AI

Knock, knock. Who’s there? An AI with generic jokes. Researchers from Google DeepMind asked 20 professional comedians to use popular AI language models to write jokes and comedy performances. Their results were mixed. Although the tools helped them to produce initial drafts and structure their routines, AI was not able to produce anything that was original, stimulating, or, crucially, funny.

The study is symptomatic of a broader trend: we’re realizing the limitations of what AI can do for artists. It can take on some of the boring, mundane, formulaic aspects of the creative process, but it can’t replace the magic and originality that humans bring. Read the full story.

—Melissa Heikkilä

This story is from The Algorithm, our weekly AI newsletter. Sign up to receive it in your inbox every Monday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The US government is suing Adobe over concealed fees
And for making it too difficult to cancel a Photoshop subscription. (The Verge)
Regulators are going after firms with hard-to-cancel accounts. (NYT $)
Adobe’s had an incredibly profitable few years. (Insider $)
The company recently announced its plans to safeguard artists against exploitative AI. (MIT Technology Review)

2 The year’s deadly heat waves have only just begun
But not everyone is at equal risk from extreme temperatures. (Vox)
Here’s what you need to know about this week’s US heat wave. (WP $)
Here’s how much heat your body can take. (MIT Technology Review)

3 Being an influencer isn’t as lucrative as it used to be
It’s getting tougher for content creators to earn a crust from social media alone. (WSJ $)
Beware the civilian creators offering to document your wedding. (The Guardian)+ Deepfakes of Chinese influencers are livestreaming 24/7. (MIT Technology Review)

4 How crypto cash could influence the US Presidential election 
‘Crypto voters’ have started mobilizing for Donald Trump, who has been making pro-crypto proclamations. (NYT $)

5 Europe is pumping money into defense tech startups
It’ll be a while until it catches up with the US though. (FT $)
Here’s the defense tech at the center of US aid to Israel, Ukraine, and Taiwan. (MIT Technology Review)

6 China’s solar industry is in serious trouble
Its rapid growth hasn’t translated into big profits. (Economist $)
Recycling solar panels is still a major environmental challenge, too. (IEEE Spectrum)
This solar giant is moving manufacturing from China back to the US. (MIT Technology Review)

7 Brace yourself for AI reading companions
The systems are trained on famous writers’ thoughts on seminal titles. (Wired $)

8 McDonalds is ditching AI chatbots at drive-thrus
The tech just proved too unreliable. (The Guardian)

9 How ice freezes is surprisingly mysterious
🧊
It’s not as simple as cooling

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By: Rhiannon Williams
Title: The Download: AI’s limitations
Sourced From: www.technologyreview.com/2024/06/18/1094001/the-download-ais-limitations/
Published Date: Tue, 18 Jun 2024 12:10:00 +0000

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The cost of building the perfect wave

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For nearly as long as surfing has existed, surfers have been obsessed with the search for the perfect wave. It’s not just a question of size, but also of shape, surface conditions, and duration—ideally in a beautiful natural environment.

While this hunt has taken surfers from tropical coastlines reachable only by boat to swells breaking off icebergs, these days—as the sport goes mainstream—that search may take place closer to home. That is, at least, the vision presented by developers and boosters in the growing industry of surf pools, spurred by advances in wave-­generating technology that have finally created artificial waves surfers actually want to ride.

Some surf evangelists think these pools will democratize the sport, making it accessible to more communities far from the coasts—while others are simply interested in cashing in. But a years-long fight over a planned surf pool in Thermal, California, shows that for many people who live in the places where they’re being built, the calculus isn’t about surf at all.

Just some 30 miles from Palm Springs, on the southeastern edge of the Coachella Valley desert, Thermal is the future home of the 118-acre private, members-only Thermal Beach Club (TBC). The developers promise over 300 luxury homes with a dazzling array of amenities; the planned centerpiece is a 20-plus-acre artificial lagoon with a 3.8-acre surf pool offering waves up to seven feet high. According to an early version of the website, club memberships will start at $175,000 a year. (TBC’s developers did not respond to multiple emails asking for comment.)

That price tag makes it clear that the club is not meant for locals. Thermal, an unincorporated desert community, currently has a median family income of $32,340. Most of its residents are Latino; many are farmworkers. The community lacks much of the basic infrastructure that serves the western Coachella Valley, including public water service—leaving residents dependent on aging private wells for drinking water.

Just a few blocks away from the TBC site is the 60-acre Oasis Mobile Home Park. A dilapidated development designed for some 1,500 people in about 300 mobile homes, Oasis has been plagued for decades by a lack of clean drinking water. The park owners have been cited numerous times by the Environmental Protection Agency for providing tap water contaminated with high levels of arsenic, and last year, the US Department of Justice filed a lawsuit against them for violating the Safe Drinking Water Act. Some residents have received assistance to relocate, but many of those who remain rely on weekly state-funded deliveries of bottled water and on the local high school for showers.

Stephanie Ambriz, a 28-year-old special-needs teacher who grew up near Thermal, recalls feeling “a lot of rage” back in early 2020 when she first heard about plans for the TBC development. Ambriz and other locals organized a campaign against the proposed club, which she says the community doesn’t want and won’t be able to access. What residents do want, she tells me, is drinkable water, affordable housing, and clean air—and to have their concerns heard and taken seriously by local officials.

Despite the grassroots pushback, which twice led to delays to allow more time for community feedback, the Riverside County Board of Supervisors unanimously approved the plans for the club in October 2020. It was, Ambriz says, “a shock to see that the county is willing to approve these luxurious developments when they’ve ignored community members” for decades. (A Riverside County representative did not respond to specific questions about TBC.)

The desert may seem like a counterintuitive place to build a water-intensive surf pool, but the Coachella Valley is actually “the very best place to possibly put one of these things,” argues Doug Sheres, the developer behind DSRT Surf, another private pool planned for the area. It is “close to the largest [and] wealthiest surf population in the world,” he says, featuring “360 days a year of surfable weather” and mountain and lake views in “a beautiful resort setting” served by “a very robust aquifer.”

In addition to the two planned projects, the Palm Springs Surf Club (PSSC) has already opened locally. The trifecta is turning the Coachella Valley into “the North Shore of wave pools,” as one aficionado described it to Surfer magazine.

The effect is an acute cognitive dissonance—one that I experienced after spending a few recent days crisscrossing the valley and trying out the waves at PSSC. But as odd as this setting may seem, an analysis by MIT Technology Review reveals that the Coachella Valley is not the exception. Of an estimated 162 surf pools that have been built or announced around the world, as tracked by the industry publication Wave Pool Magazine, 54 are in areas considered by the nonprofit World Resources Institute

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By: Eileen Guo
Title: The cost of building the perfect wave
Sourced From: www.technologyreview.com/2024/06/17/1093388/surf-pools-ocean-climate-change-water-scarcity/
Published Date: Mon, 17 Jun 2024 09:00:00 +0000

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