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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. 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.

If you missed the chance to buy the Echo Show 8 when it was discounted to $75 at the start of April, Amazon has once again reduced the smart display to that price. The $55 cut means the Echo Show 8 is only $5 more than it was during Black Friday last year. If you’ve been eyeing one of Amazon’s larger smart displays, the retailer has also reduced the price of the Echo Show 10 and Echo Show 15. You can get the company’s largest smart display for $214.98, down from $279.98. Meanwhile, the Echo Show 10 is currently priced at $185.

The Echo Show 8 is one of the best smart displays you can buy. While it’s a few years old now, the Show 8 offers a compelling mix of features for an affordable price. Its 8-inch, 1,280 x 800 resolution display is large enough to make viewing photos and taking part in video calls comfortable, but the Show 8’s screen isn’t so large the device will look out of place in your kitchen or bedroom. At the same time, the Show 8’s built-in speakers are powerful enough to fill a small room. And if you’re worried about privacy, the Show 8 ships with a physical camera shutter and mic mute button.

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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.  

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.

Apple’s second-generation AirPods Pro are among the best Bluetooth earbuds you can pair with an iPhone – but at $250, they’re expensive. Thankfully, you can frequently find them on sale on Amazon and other retailers. Following a $50 price drop at the start of April, the 2022 AirPods Pro are once again on sale for $200.

Engadget awarded the second-generation AirPods Pro a score of 88 in 2022. They feature one of the best transparency modes of any wireless earbuds on the market, and improved active noise cancellation performance over the original AirPods Pro. They also sound better than their predecessor. Of course, the reason to buy a pair of AirPods Pro is for their hands-free Siri support and tight integration with iOS and the rest of Apple’s ecosystem. Pairing any set of AirPods with an iPhone is easy, as is switching between different Apple devices. About the only area where the 2022 AirPods Pro disappoint is when it comes to battery life. Engadget Senior Editor Billy Steele found the earbuds offer little over six hours of use on one charge, or less than many other premium wireless earbuds.

If the AirPods Pro are out of your budget, it’s worth noting Amazon has discounted other Apple audio products, including the third-generation AirPods. After an 11 percent discount, they’re $150, down from their usual $169 starting price.

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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.

WW Norton

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:

1. “Automatic Computers” (programming languages)

2. “How Can a Computer be Programmed to Use a Language” (natural language processing)

3. “Neuron Nets” (neural nets and deep learning)

4. “Theory of the Size of a Calculation” (computational complexity)

5. “Self-​improvement” (machine learning)

6. “Abstractions” (feature engineering)

7. “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.)

For the last few years, you’ve been able to say “Stop” to tell Google Assistant to end an alarm early without the need to preface your command with “Hey Google.” It’s a handy feature Google first debuted on Assistant-enabled smart displays and speakers before later rolling it out to Pixel smartphones. And for the most part, it works like a charm, though one person recently discovered a fun quirk of the feature that involves the Pixies classic “Where Is My Mind?”

In a Reddit post spotted by Android Police, Pixel user “asevarte” recounts how their morning alarm would go off and sometimes turn off moments later for seemingly no reason. “Maybe once every other week or so, I would wake up 30 minutes later on my backup alarm, with no indication as to why the first shut itself off,” they told the Google Pixel subreddit.

Earlier this week, asevarte decided to wake up early to get to the bottom of the issue. Thankfully, it didn’t take long to find the culprit. Their alarm was set to play a Spotify playlist that features “Where Is My Mind?” If you’re a Pixies fan, you know exactly where this is going. The Surfer Rosa cut opens with bassist and vocalist Kim Deal singing “Ooh” before frontman Black Francis says, “Stop,” and the song, following a brief pause, then continues. The section caused Google Assistant to prematurely end asevarte’s alarm. They had the playlist set to shuffle, which is what made identifying the bug tricky.

Android Police recorded a video of the oversight in action, and sure enough, playing “Where Is My Mind?” ends an alarm early. Interestingly, other songs that feature a prominent “stop,” such as “Don’t Stop Me Now” by Queen, don’t appear to trigger Assistant’s Quick Phrases feature in the same way that “Where Is My Mind?” does. Android Police speculates the reason for that could be that in those other songs “stop” is backed by instrumentals. That lines up with complaints Assistant users have had over the years that the feature doesn’t work when they try to use it while their smart display, speaker or Pixel device is playing music.

If you’re curious about what the Pixies think of all this. The band’s official Twitter account caught the original Android Police story. “Sorry about that!” the account tweeted.

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.

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.

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.

If you’re in the market for a smart scale, one of the most feature-rich models you can buy is on sale. After a 38 percent discount, the Eufy Smart Scale P2 Pro is currently priced at $50 on Amazon, down from $80. The P2 Pro is on Engadget’s list of the best smart scales and for good reason. It’s affordable, well-made and can track 16 different measurements. You can use the P2 Pro to measure your body fat percentage, bone mass, water weight and more. In other words, it offers all the stat tracking a person could use to improve their lifestyle. The P2 Pro would be among the smart scales you could buy if not for the fact Anker, Eufy’s parent company, recently misled the public about the safety of its security cameras.

The P2 Pro is part of a broader sale that also sees Eufy’s robot vacuums discounted. For instance, the RoboVac G30, one of the best budget models you can buy, is 45 percent off, making it $175.98 at the moment. It features built-in WiFi, a feature you won’t find on some of Eufy’s more affordable robot vacuums; the company’s Smart Dynamic Navigation 2.0 software; and boundary strips you can use set up no-go zones.

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