Monday, May 8, 2023
Sunday, May 7, 2023
'Darkest Dungeon II' arrives on Steam next week
After almost two years of early access and more than five years after it was first announced, Darkest Dungeon II is ready for release. Red Hook Studios announced this week that version 1.0 of the sequel to its hit 2016 RPG will arrive on the Epic Games Store and Steam, where the game was previously unavailable, on May 8th. For fans who already own Darkest Dungeon on Valve’s storefront, Red Hook said it would offer a limited-time discount on its new game.
Even if you’ve spent some time playing the game in early access, the 1.0 release has something for you. The public release adds one playable character and the game’s final two story acts. As with Darkest Dungeon, Red Hook is promising plenty of post-launch support. In the future, the studio said fans can look forward to quality-of-life improvements, the addition of new monsters and hero skins, ongoing balance tuning and, most notably, mod support.
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Dota 2's biggest tournament will return to Seattle this year
For the first time since 2017, The International, Dota 2's most prestigious tournament, will take place in Valve's hometown. The tournament will kick off with a group stage that begins on October 14th before moving to Seattle's Climate Pledge Arena on October 27th, the studio announced on Saturday. The Climate Pledge Arena, previously known as KeyArena, is the same venue where Valve held The International between 2014 and 2017. It's also the venue where Dota fans got to see one of the best plays in the tournament's history.
In 2018, Valve moved The International to Vancouver's Rogers Arena due to the start of multi-year renovations at KeyArena. In subsequent years, the event made stops in China, Romania and Singapore. Valve had also planned to bring the tournament to Sweden, but the pandemic forced the studio to cancel The International in 2020. On Saturday, Valve said The International 2023 would host the event's largest audience to date. The studio promised to share more information about how fans can purchase tickets to The International 2023 closer to the date of the event.
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Twitter says a 'security incident' led to private Circle tweets becoming public
Back in April, users found a bug with Twitter’s Circle feature that saw the platform expose private tweets to strangers. Now, nearly a month later, the company has finally commented on the issue. In an email seen by The Guardian, Twitter told affected users the exposure was the result of “a security incident that occured earlier this year.”
The company claims the issue was “immediately fixed.” It also shared an apology. “Twitter is committed to protecting the privacy of the people who use our service, and we understand the risks that an incident like this can introduce and we deeply regret this happened,” the company said. When news of the exposure first started circulating online, some, including creator Theo Brown, speculated the issue was the result of Twitter failing to filter Circle tweets out of its recommendation algorithm. Twitter has not operated a communications department since Elon Musk's first round of layoffs, and the company did not initially acknowledge the issue.
More broadly, Twitter has dealt with a growing number of technical issues since Musk’s takeover of the company in October. The billionaire has reduced the company’s workforce by at least 60 percent, gutting many of its technical teams of senior leadership. Over that time, Twitter has suffered multiple outages and otherwise created confusion over feature rollouts and removals.
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Hitting the Books: Why a Dartmouth professor coined the term 'artificial intelligence'
If the Wu-Tang produced it in '23 instead of '93, they'd have called it D.R.E.A.M. — because data rules everything around me. Where once our society brokered power based on strength of our arms and purse strings, the modern world is driven by data empowering algorithms to sort, silo and sell us out. These black box oracles of imperious and imperceptible decision-making deign who gets home loans, who gets bail, who finds love and who gets their kids taken from them by the state.
In their new book, How Data Happened: A History from the Age of Reason to the Age of Algorithms, which builds off their existing curriculum, Columbia University Professors Chris Wiggins and Matthew L Jones examine how data is curated into actionable information and used to shape everything from our political views and social mores to our military responses and economic activities. In the excerpt below, Wiggins and Jones look at the work of mathematician John McCarthy, the junior Dartmouth professor who single-handedly coined the term "artificial intelligence"... as part of his ploy to secure summer research funding.
Excerpted from How Data Happened: A History from the Age of Reason to the Age of Algorithms by Chris Wiggins and Matthew L Jones. Published by WW Norton. Copyright © 2023 by Chris Wiggins and Matthew L Jones. All rights reserved.
Confecting “Artificial Intelligence”
A passionate advocate of symbolic approaches, the mathematician John McCarthy is often credited with inventing the term “artificial intelligence,” including by himself: “I invented the term artificial intelligence,” he explained, “when we were trying to get money for a summer study” to aim at “the long term goal of achieving human level intelligence.” The “summer study” in question was titled “The Dartmouth Summer Research Project on Artificial Intelligence,” and the funding requested was from the Rockefeller Foundation. At the time a junior professor of mathematics at Dartmouth, McCarthy was aided in his pitch to Rockefeller by his former mentor Claude Shannon. As McCarthy describes the term’s positioning, “Shannon thought that artificial intelligence was too flashy a term and might attract unfavorable notice.” However, McCarthy wanted to avoid overlap with the existing field of “automata studies” (including “nerve nets” and Turing machines) and took a stand to declare a new field. “So I decided not to fly any false flags anymore.” The ambition was enormous; the 1955 proposal claimed “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” McCarthy ended up with more brain modelers than axiomatic mathematicians of the sort he wanted at the 1956 meeting, which came to be known as the Dartmouth Workshop. The event saw the coming together of diverse, often contradictory efforts to make digital computers perform tasks considered intelligent, yet as historian of artificial intelligence Jonnie Penn argues, the absence of psychological expertise at the workshop meant that the account of intelligence was “informed primarily by a set of specialists working outside the human sciences.” Each participant saw the roots of their enterprise differently. McCarthy reminisced, “anybody who was there was pretty stubborn about pursuing the ideas that he had before he came, nor was there, as far as I could see, any real exchange of ideas.”
Like Turing’s 1950 paper, the 1955 proposal for a summer workshop in artificial intelligence seems in retrospect incredibly prescient. The seven problems that McCarthy, Shannon, and their collaborators proposed to study became major pillars of computer science and the field of artificial intelligence:
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“Automatic Computers” (programming languages)
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“How Can a Computer be Programmed to Use a Language” (natural language processing)
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“Neuron Nets” (neural nets and deep learning)
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“Theory of the Size of a Calculation” (computational complexity)
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“Self-improvement” (machine learning)
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“Abstractions” (feature engineering)
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“Randomness and Creativity” (Monte Carlo methods including stochastic learning).
The term “artificial intelligence,” in 1955, was an aspiration rather than a commitment to one method. AI, in this broad sense, involved both discovering what comprises human intelligence by attempting to create machine intelligence as well as a less philosophically fraught effort simply to get computers to perform difficult activities a human might attempt.
Only a few of these aspirations fueled the efforts that, in current usage, became synonymous with artificial intelligence: the idea that machines can learn from data. Among computer scientists, learning from data would be de-emphasized for generations.
Most of the first half century of artificial intelligence focused on combining logic with knowledge hard-coded into machines. Data collected from everyday activities was hardly the focus; it paled in prestige next to logic. In the last five years or so, artificial intelligence and machine learning have begun to be used synonymously; it’s a powerful thought-exercise to remember that it didn’t have to be this way. For the first several decades in the life of artificial intelligence, learning from data seemed to be the wrong approach, a nonscientific approach, used by those who weren’t willing “to just program” the knowledge into the computer. Before data reigned, rules did.
For all their enthusiasm, most participants at the Dartmouth workshop brought few concrete results with them. One group was different. A team from the RAND Corporation, led by Herbert Simon, had brought the goods, in the form of an automated theorem prover. This algorithm could produce proofs of basic arithmetical and logical theorems. But math was just a test case for them. As historian Hunter Heyck has stressed, that group started less from computing or mathematics than from the study of how to understand large bureaucratic organizations and the psychology of the people solving problems within them. For Simon and Newell, human brains and computers were problem solvers of the same genus.
Our position is that the appropriate way to describe a piece of problem-solving behavior is in terms of a program: a specification of what the organism will do under varying environmental circumstances in terms of certain elementary information processes it is capable of performing... Digital computers come into the picture only because they can, by appropriate programming, be induced to execute the same sequences of information processes that humans execute when they are solving problems. Hence, as we shall see, these programs describe both human and machine problem solving at the level of information processes.
Though they provided many of the first major successes in early artificial intelligence, Simon and Newell focused on a practical investigation of the organization of humans. They were interested in human problem-solving that mixed what Jonnie Penn calls a “composite of early twentieth century British symbolic logic and the American administrative logic of a hyper-rationalized organization.” Before adopting the moniker of AI, they positioned their work as the study of “information processing systems” comprising humans and machines alike, that drew on the best understanding of human reasoning of the time.
Simon and his collaborators were deeply involved in debates about the nature of human beings as reasoning animals. Simon later received the Nobel Prize in Economics for his work on the limitations of human rationality. He was concerned, alongside a bevy of postwar intellectuals, with rebutting the notion that human psychology should be understood as animal-like reaction to positive and negative stimuli. Like others, he rejected a behaviorist vision of the human as driven by reflexes, almost automatically, and that learning primarily concerned the accumulation of facts acquired through such experience. Great human capacities, like speaking a natural language or doing advanced mathematics, never could emerge only from experience—they required far more. To focus only on data was to misunderstand human spontaneity and intelligence. This generation of intellectuals, central to the development of cognitive science, stressed abstraction and creativity over the analysis of data, sensory or otherwise. Historian Jamie Cohen-Cole explains, “Learning was not so much a process of acquiring facts about the world as of developing a skill or acquiring proficiency with a conceptual tool that could then be deployed creatively.” This emphasis on the conceptual was central to Simon and Newell’s Logic Theorist program, which didn’t just grind through logical processes, but deployed human-like “heuristics” to accelerate the search for the means to achieve ends. Scholars such as George Pólya investigating how mathematicians solved problems had stressed the creativity involved in using heuristics to solve math problems. So mathematics wasn’t drudgery — it wasn’t like doing lots and lots of long division or of reducing large amounts of data. It was creative activity — and, in the eyes of its makers, a bulwark against totalitarian visions of human beings, whether from the left or the right. (And so, too, was life in a bureaucratic organization — it need not be drudgery in this picture — it could be a place for creativity. Just don’t tell that to its employees.)
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Saturday, May 6, 2023
Microsoft permanently drops the price of Xbox Series X/S storage
Earlier this week, a handful of retailers discounted Seagate’s Xbox Series X/S Expansion Cards to new all-time low prices. Now, Microsoft is making those price cuts permanent (via Polygon). As of Friday, pricing for the Expansion Cards starts at $90 for the 512GB model, while the 1TB and 2TB variants will set you back $150 and $280, respectively. That’s 32 percent and 30 percent off the $220 and $280 the 1TB and 2TB models started at previously.
Think of all the new games you’ll be able to download and play now 👀
— Xbox (@Xbox) May 5, 2023
The @Seagate Storage Expansion Card is now available starting at a lower price: https://t.co/qjgbTRuMeBpic.twitter.com/RovCaXADmd
While you could (accurately) argue Microsoft’s proprietary storage solution for the Xbox Series X and Series S is still too expensive, a permanent price cut is a step in the right direction for the company’s ninth-generation consoles. It means those Expansion Cards will cost less with subsequent sales, making them more competitive with the regular NVMe drives you can buy for Sony’s PlayStation 5. Moreover, further price relief could be on the way. In April, Best Buy briefly listed a 1TB expansion card from Western Digital. At the time, the listing suggested the NVMe would cost $180 (now more expensive than Seagate’s 1TB model), but more competition could push prices lower.
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The iPhone 15 Pro probably may not feature solid-state buttons as previously rumored
If you’ve been following the Apple rumor mill since last year, you may recall the iPhone 15 Pro has been widely expected to feature a set of touch-sensitive solid-state buttons. It now looks like Apple won’t replace the iPhone’s physical buttons for at least another year. In a shareholder letter spotted by MacRumors, Apple supplier Cirrus Logic said “a new product that we mentioned in previous shareholder letters as being scheduled for introduction this fall is no longer expected to come to market as planned.”
Cirrus is best known for producing a handful of components that go into the iPhone’s Taptic Engine. Apple is the firm’s largest customer, accounting for 79 percent of its revenue in 2022. In November, Cirrus told investors and analysts it was working on a new high-performance mixed-signal (HPMS) component (that’s the same category of part as the Tapic Engine), and that it would arrive in smartphones sometime in 2023. This week, Cirrus said it had “limited visibility” into the product’s future.
Reports suggesting the iPhone 15 Pro would feature a set of solid-state buttons originated from Apple analyst Ming-Chi Kuo, who said last fall the company was planning to replace the physical volume and power buttons on its next flagship phone with touch-sensitive buttons. Last month, Kuo revised his forecast, noting Apple had decided to change plans due to “unresolved technical issues before mass production.” If nothing else, the development is a reminder to treat smartphone leaks with skepticism, particularly those that circulate months and sometimes years in advance of a product’s announcement.
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Apple's 'Silo' is simply transcendent sci-fi TV
You've heard this premise before: In a post-apocalyptic world, the remnants of civilization live in a stratified society, governed by oppressive rules as they struggle to maintain their humanity. Then, a hero appears and threatens to topple the social order. We've seen this story repeated so often throughout the history of dystopian fiction — most notably in Fritz Lang's masterpiece, Metropolis — that I wasn't immediately excited when Apple first announced Silo, an adaptation of Hugh Howie's wildly popular Wool novels. Surely, this can't top Bong Joon-ho's bonkers Snowpiercer (itself adapted from an '80s French graphic novel), so why even bother?
Well, I was wrong. Spearheaded by Graham Yost (Justified), Silo exemplifies everything I love about great science fiction. It wrestles with complex ideas and moral questions, it's filled with memorable and realistic characters, and it features a truly distinctive setting: a 144-story self-sustaining underground city that's reminiscent of The Matrix's Zion. In this case, though, the population seems mostly content with their situation. There's no memory of the world before the silo, so most people concern themselves with keeping the city running instead of breaking out. Why rock the bunker?
But, echoing a theme from HBO's excellent Station Eleven and Deep Space Nine, survival is insufficient. Some can't help but wonder about the nature of the silo: Is the video feed of the destroyed outside world real, or is it some sort of trap to keep them underground? Who, exactly, determines who can get pregnant? And what can they learn from the artifacts left behind from the previous civilization?
Silo makes a strong impression from the start. We're introduced to Sheriff Holsten (David Oyelowo), a well-liked law man who goes about his morning and makes a shocking announcement: He wants to go outside. The gravity of his declaration is instantly made clear, even though the show doesn't explain it up front. We later learn that anyone who asks to go out can, but it's essentially a death wish. All of this is conveyed almost wordlessly at first, thanks to the strength of Oyelowo's performance.
I can't help but love a show that begins so confidently. Throughout the first two episodes, Silo makes it clear that you're in good hands. Yost and his writing team — which includes Jessica Blaire (On Becoming a God in Central Florida) and Cassie Papas (Tyrant) — take time to introduce every character, establish their motivations and build a greater mystery. The impeccable production design makes the silo seem genuinely lived in. And the direction from Morten Tyldum deftly balances intimate drama with epic visuals (the silo has no elevator, just a very long stairwell that seems to go on forever).
Silo is the rare show where every word speaks volumes, every gesture seems meaningful, and every element of the frame tells a story. It's also filled with grounded and believable performances across the board: There's Rashida Jones as Allison, the Sheriff's wife, someone who's eager to start a family but also can't help but be curious about the history of the silo. Rebecca Ferguson (Mission Impossible: Rogue Nation and Fallout), ostensibly the star of the show, doesn't really get much screen time until the second episode, but she paints a convincing portrait of a world-weary engineer who just wants to solve the murder of her friend.
Of course, this wouldn’t be a dystopian story without some sort of greater conspiracy going on. The silo’s leadership is clearly hiding something from its citizens – though the mayor (played by Geraldine James) also seems genuinely concerned about the well-being of her people. There's a sense that even those in power are only trying to do their best, but may be faced with hard decisions to keep society going.
You’d think after being somewhat burned by Lost, The X-Files and other shows centering on major sci-fi mysteries, I’d be less inclined to commit to yet another one. But Silo is so compelling, I just can’t help it.
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Crypto giant Binance is reportedly facing US probe for violating Russian sanctions
Binance is reportedly facing yet another investigation by the US Justice Department, and this time, it's over possible violations against sanctions imposed against Russia. According to Bloomberg, the agency is looking into whether the cryptocurrency exchange allowed Russian customers to move money as a way to go around US sanctions on the country's financial institutions. The news organizations' sources also said that Binance is discussing the possibility of settling with the DOJ regarding previous allegations that the exchange was also used to move money to circumvent US sanctions against Iran.
If you'll recall, United States and the European Union imposed sanctions against Russian financial institutions following the invasion of Ukraine. Mykhailo Federov, Ukraine's Vice Prime Minister, asked major crypto exchanges to freeze all Russian and Belarusian accounts at the same time, but Binance was one of the companies that refused to do so. Back then, a spokesperson said that unilaterally banning people's access to cryptocurrency "would fly in the face of the reason why crypto exists," because it would affect ordinary users and not just Russian oligarchs.
If the DOJ truly is looking into Binance's activities related to Russian sanctions, then it's merely one of the investigations the exchange is grappling with. The DOJ and the Internal Revenue Service started looking into reports that Binance is being used for money laundering schemes in 2021. And just earlier this year, the Commodity Futures Trading Commission (CFTC) charged Binance and its founder Changpeng Zhao (pictured above) for not asking users to verify their identities, offering unregistered crypto derivatives and for implementing measures to avoid US regulation. Binance told us at the time that it found the charges "unexpected and disappointing."
This time, it told Bloomberg in a statement: "In 2021, Binance launched an initiative to completely overhaul its corporate governance structure, including bringing in a world-class bench of seasoned executives to fundamentally change how Binance operates globally." The spokesperson continued that the company now observes strict know-your-customer protocols similar to the ones employed by traditional banks. "Our policy," they said, "imposes a zero-tolerance approach to double registrations, anonymous identities, and obscure sources of money," While they didn't specifically address the allegations, the statement sounds like a denial that the company's service allowed Russian users to flout US sanctions.
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