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Anthropic Says That Claude Contains Its Own Kind of Emotions

Anthropic Says That Claude Contains Its Own Kind of Emotions

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Claude has been through a lot lately—a public fallout with the Pentagon, leaked source code—so it makes sense that it would be feeling a little blue. Except, it’s an AI model, so it can’t feel. Right?

Well, sort of. A new study from Anthropic suggests models have digital representations of human emotions like happiness, sadness, joy, and fear, within clusters of artificial neurons—and these representations activate in response to different cues.

Researchers at the company probed the inner workings of Claude Sonnet 3.5 and found that so-called “functional emotions” seem to affect Claude’s behavior, altering the model’s outputs and actions.

Anthropic’s findings may help ordinary users make sense of how chatbots actually work. When Claude says it is happy to see you, for example, a state inside the model that corresponds to “happiness” may be activated. And Claude may then be a little more inclined to say something cheery or put extra effort into vibe coding.

“What was surprising to us was the degree to which Claude’s behavior is routing through the model’s representations of these emotions,” says Jack Lindsey, a researcher at Anthropic who studies Claude’s artificial neurons.

“Function Emotions”

Anthropic was founded by ex-OpenAI employees who believe that AI could become hard to control as it becomes more powerful. In addition to building a successful competitor to ChatGPT, the company has pioneered efforts to understand how AI models misbehave, partly by probing the workings of neural networks using what’s known as mechanistic interpretability. This involves studying how artificial neurons light up or activate when fed different inputs or when generating various outputs.

Previous research has shown that the neural networks used to build large language models contain representations of human concepts. But the fact that “functional emotions” appear to affect a model’s behavior is new.

While Anthropic’s latest study might encourage people to see Claude as conscious, the reality is more complicated. Claude might contain a representation of “ticklishness,” but that does not mean that it actually knows what it feels like to be tickled.

Inner Monologue

To understand how Claude might represent emotions, the Anthropic team analyzed the model’s inner workings as it was fed text related to 171 different emotional concepts. They identified patterns of activity, or “emotion vectors,” that consistently appeared when Claude was fed other emotionally evocative input. Crucially, they also saw these emotion vectors activate when Claude was put in difficult situations.

The findings are relevant to why AI models sometimes break their guardrails.

The researchers found a strong emotional vector for “desperation” when Claude was pushed to complete impossible coding tasks, which then prompted it to try cheating on the coding test. They also found “desperation” in the model’s activations in another experimental scenario where Claude chose to blackmail a user to avoid being shut down.

“As the model is failing the tests, these desperation neurons are lighting up more and more,” Lindsey says. “And at some point this causes it to start taking these drastic measures.”

Lindsey says it might be necessary to rethink how models are currently given guardrails through alignment post-training, which involves giving it rewards for certain outputs. By forcing a model to pretend not to express its functional emotions, “you’re probably not going to get the thing you want, which is an emotionless Claude,” Lindsey says, veering a bit into anthropomorphization. “You’re gonna get a sort of psychologically damaged Claude.”

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Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?

In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:

According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.

What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.

#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI">Yet Another Safety Leader at OpenAI Has Left Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave? In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline: According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese. What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.” The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck. And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts. #Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI

working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:

According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.

What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.

#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI">Yet Another Safety Leader at OpenAI Has LeftYet Another Safety Leader at OpenAI Has Left Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave? In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline: According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese. What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.” The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck. And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts. #Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI

Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?

In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:

According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.

What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.

#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI

Image may contain Adapter Electronics Escooter Transportation and Vehicle

Photograph: Chris Null

Naturally, the AstroRinse also needs a power supply, so if you don’t have a standard electrical outlet near your hose spigot, you’ll need another extension cord solution here. The unit must be level to run properly, and it features adjustable feet and a built-in spirit level to help you achieve that.

All told, you’ll need to carefully consider where you’re going to place the AstroRinse, ensuring you have access to water, power, and drainage—and that the location isn’t too far from the pool. Since the AquaSense X robot itself weighs 29 pounds (and more when freshly pulled from the water), you probably don’t want to haul the thing halfway across the yard to clean and charge it. Unfortunately, given the availability of the above three services in my backyard, that’s exactly what I had to do.

A Familiar Friend in the Water

The Beatbot AquaSense X robot is nearly identical in appearance to the Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.

Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.

Video: Chris Null

After a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.

On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.

Image may contain Electronics Mobile Phone Phone and Text

ScreenshotBeatbot app via Chris Null

As with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.

Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.

Charging and Cleaning

On to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.

Video: Chris Null

As the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.

Image may contain Car Transportation and Vehicle

Photograph: Chris Null

#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors">This Pool Robot Cleans the Pool—and Then Cleans ItselfPhotograph: Chris NullNaturally, the AstroRinse also needs a power supply, so if you don’t have a standard electrical outlet near your hose spigot, you’ll need another extension cord solution here. The unit must be level to run properly, and it features adjustable feet and a built-in spirit level to help you achieve that.All told, you’ll need to carefully consider where you’re going to place the AstroRinse, ensuring you have access to water, power, and drainage—and that the location isn’t too far from the pool. Since the AquaSense X robot itself weighs 29 pounds (and more when freshly pulled from the water), you probably don’t want to haul the thing halfway across the yard to clean and charge it. Unfortunately, given the availability of the above three services in my backyard, that’s exactly what I had to do.A Familiar Friend in the WaterThe Beatbot AquaSense X robot is nearly identical in appearance to the Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.Video: Chris NullAfter a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.ScreenshotBeatbot app via Chris NullAs with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.Charging and CleaningOn to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.Video: Chris NullAs the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.Photograph: Chris Null#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors

Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.

Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.

Video: Chris Null

After a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.

On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.

Image may contain Electronics Mobile Phone Phone and Text

ScreenshotBeatbot app via Chris Null

As with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.

Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.

Charging and Cleaning

On to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.

Video: Chris Null

As the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.

Image may contain Car Transportation and Vehicle

Photograph: Chris Null

#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors">This Pool Robot Cleans the Pool—and Then Cleans Itself
Image may contain Adapter Electronics Escooter Transportation and Vehicle

Photograph: Chris Null

Naturally, the AstroRinse also needs a power supply, so if you don’t have a standard electrical outlet near your hose spigot, you’ll need another extension cord solution here. The unit must be level to run properly, and it features adjustable feet and a built-in spirit level to help you achieve that.

All told, you’ll need to carefully consider where you’re going to place the AstroRinse, ensuring you have access to water, power, and drainage—and that the location isn’t too far from the pool. Since the AquaSense X robot itself weighs 29 pounds (and more when freshly pulled from the water), you probably don’t want to haul the thing halfway across the yard to clean and charge it. Unfortunately, given the availability of the above three services in my backyard, that’s exactly what I had to do.

A Familiar Friend in the Water

The Beatbot AquaSense X robot is nearly identical in appearance to the Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.

Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.

Video: Chris Null

After a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.

On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.

Image may contain Electronics Mobile Phone Phone and Text

ScreenshotBeatbot app via Chris Null

As with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.

Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.

Charging and Cleaning

On to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.

Video: Chris Null

As the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.

Image may contain Car Transportation and Vehicle

Photograph: Chris Null

#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors

EA Sports announced it will remove all paid progression options from College Football 27‘s Dynasty and Road to Glory modes, reversing a decision that drew significant backlash from fans and content creators following the game’s launch.

In a statement posted to social media during the game’s launch week, the developer acknowledged that player feedback indicated the microtransactions “missed the mark.”

SEE ALSO: ‘EA College Football 27’: Road to Glory review

The studio said the paid options had been “added independent of deeper mode progression with the aim to give players more choice,” but conceded that “what you’ve said is that they’re not adding the value we intended.” EA said the changes would take effect the following morning, though it warned that players with existing College Point balances would lose the ability to apply them to Road to Glory or Dynasty once the features were removed, urging fans to spend their points beforehand.

Our big Guessing Game is back! Enter now for a chance to win an Apple Watch.

The reversal follows a wave of criticism after College Football 27‘s release, with fans organizing around the hashtag #CFBPlayDontPay to voice frustration over microtransactions appearing in the game’s single-player offline modes. The system allowed players to spend real money to instantly boost their coach or player’s development. For example, maxing out a coach in Dynasty from the start could cost as much as $100, more than the price of the game itself.

Compounding the frustration, EA also removed sliders that let players in College Football 25 and 26 manually adjust how much experience they earned, a feature that had let people level up faster without paying. With that option gone, spending money became the only way to speed up progression, which is what drove much of the backlash.

Notably, the statement stopped short of ruling out microtransactions from the franchise going forward. EA said its “goal for live service plans in CFB28 and beyond will be to deliver valuable features and content with greater transparency and communication” — language suggesting paid content will return in some form in next year’s edition, even as the company walks back the current game’s implementation.

Topics Social Good Video Games

#reverses #removes #microtransactions #College #Football">EA reverses course, removes microtransactions from ‘College Football 27’ EA Sports announced it will remove all paid progression options from College Football 27‘s Dynasty and Road to Glory modes, reversing a decision that drew significant backlash from fans and content creators following the game’s launch. In a statement posted to social media during the game’s launch week, the developer acknowledged that player feedback indicated the microtransactions “missed the mark.” SEE ALSO: ‘EA College Football 27’: Road to Glory review The studio said the paid options had been “added independent of deeper mode progression with the aim to give players more choice,” but conceded that “what you’ve said is that they’re not adding the value we intended.” EA said the changes would take effect the following morning, though it warned that players with existing College Point balances would lose the ability to apply them to Road to Glory or Dynasty once the features were removed, urging fans to spend their points beforehand. Mashable Top Stories Our big Guessing Game is back! Enter now for a chance to win an Apple Watch.The reversal follows a wave of criticism after College Football 27‘s release, with fans organizing around the hashtag #CFBPlayDontPay to voice frustration over microtransactions appearing in the game’s single-player offline modes. The system allowed players to spend real money to instantly boost their coach or player’s development. For example, maxing out a coach in Dynasty from the start could cost as much as 0, more than the price of the game itself. Compounding the frustration, EA also removed sliders that let players in College Football 25 and 26 manually adjust how much experience they earned, a feature that had let people level up faster without paying. With that option gone, spending money became the only way to speed up progression, which is what drove much of the backlash. This Tweet is currently unavailable. It might be loading or has been removed. Notably, the statement stopped short of ruling out microtransactions from the franchise going forward. EA said its “goal for live service plans in CFB28 and beyond will be to deliver valuable features and content with greater transparency and communication” — language suggesting paid content will return in some form in next year’s edition, even as the company walks back the current game’s implementation. Topics Social Good Video Games #reverses #removes #microtransactions #College #Football

statement posted to social media during the game’s launch week, the developer acknowledged that player feedback indicated the microtransactions “missed the mark.”

SEE ALSO: ‘EA College Football 27’: Road to Glory review

The studio said the paid options had been “added independent of deeper mode progression with the aim to give players more choice,” but conceded that “what you’ve said is that they’re not adding the value we intended.” EA said the changes would take effect the following morning, though it warned that players with existing College Point balances would lose the ability to apply them to Road to Glory or Dynasty once the features were removed, urging fans to spend their points beforehand.

Our big Guessing Game is back! Enter now for a chance to win an Apple Watch.

The reversal follows a wave of criticism after College Football 27‘s release, with fans organizing around the hashtag #CFBPlayDontPay to voice frustration over microtransactions appearing in the game’s single-player offline modes. The system allowed players to spend real money to instantly boost their coach or player’s development. For example, maxing out a coach in Dynasty from the start could cost as much as $100, more than the price of the game itself.

Compounding the frustration, EA also removed sliders that let players in College Football 25 and 26 manually adjust how much experience they earned, a feature that had let people level up faster without paying. With that option gone, spending money became the only way to speed up progression, which is what drove much of the backlash.

Notably, the statement stopped short of ruling out microtransactions from the franchise going forward. EA said its “goal for live service plans in CFB28 and beyond will be to deliver valuable features and content with greater transparency and communication” — language suggesting paid content will return in some form in next year’s edition, even as the company walks back the current game’s implementation.

Topics Social Good Video Games

#reverses #removes #microtransactions #College #Football">EA reverses course, removes microtransactions from ‘College Football 27’

EA Sports announced it will remove all paid progression options from College Football 27‘s Dynasty and Road to Glory modes, reversing a decision that drew significant backlash from fans and content creators following the game’s launch.

In a statement posted to social media during the game’s launch week, the developer acknowledged that player feedback indicated the microtransactions “missed the mark.”

SEE ALSO: ‘EA College Football 27’: Road to Glory review

The studio said the paid options had been “added independent of deeper mode progression with the aim to give players more choice,” but conceded that “what you’ve said is that they’re not adding the value we intended.” EA said the changes would take effect the following morning, though it warned that players with existing College Point balances would lose the ability to apply them to Road to Glory or Dynasty once the features were removed, urging fans to spend their points beforehand.

Our big Guessing Game is back! Enter now for a chance to win an Apple Watch.

The reversal follows a wave of criticism after College Football 27‘s release, with fans organizing around the hashtag #CFBPlayDontPay to voice frustration over microtransactions appearing in the game’s single-player offline modes. The system allowed players to spend real money to instantly boost their coach or player’s development. For example, maxing out a coach in Dynasty from the start could cost as much as $100, more than the price of the game itself.

Compounding the frustration, EA also removed sliders that let players in College Football 25 and 26 manually adjust how much experience they earned, a feature that had let people level up faster without paying. With that option gone, spending money became the only way to speed up progression, which is what drove much of the backlash.

Notably, the statement stopped short of ruling out microtransactions from the franchise going forward. EA said its “goal for live service plans in CFB28 and beyond will be to deliver valuable features and content with greater transparency and communication” — language suggesting paid content will return in some form in next year’s edition, even as the company walks back the current game’s implementation.

Topics Social Good Video Games

#reverses #removes #microtransactions #College #Football

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