×
How Synthflow AI is cutting through the noise in a loud AI voice category

How Synthflow AI is cutting through the noise in a loud AI voice category

AI Artificial Intelligence Enterprise funding round synthflow Tech-news voice AI , , ,

The conversational AI market has exploded since ChatGPT was released in November 2022 and is predicted to grow into a nearly $50 billion global industry by 2031, according to MarketsAndMarkets.

Synthflow AI is just one of many companies building in this space that hopes to stand out from the pack because of its focus on being enterprise-grade and easy to set up.

Berlin-based Synthflow is a no-code platform that lets enterprises build and deploy customized white-labeled voice AI customer service agents. The company, which launched in 2023, has amassed more than 1,000 customers and has handled more than 45 million calls.

The startup’s voice agents are both HIPAA and GDPR compliant and can be plugged into more than 200 integrations with other enterprise platforms, including Salesforce, Twilio, and HubSpot, among others.

Hakob Astabatsyan, co-founder and CEO, told TechCrunch that he and his co-founders, Albert Astabatsyan, now CPO, and Sassun Mirzakhan-Saky, now CTO, started messing around with OpenAI’s ChatGPT API back in early 2023 to find potential ways to build no-code business applications on top of the AI model.

They started with a text-to-text AI bot and then tried to build a voice bot. When they realized how much harder voice was, they got excited about the potential.

“We realized, oh my god, voice is really complicated, right? To actually make AI speak in real time like we do, having this 400 milliseconds latency, and handling interruptions, it turned out to be such a complicated task,” Astabatsyan said. “We fell in love with this problem, and we said, look, we’re gonna work only on voice bots from now on.”

The group formed Synthflow and spent the rest of 2023 building. They launched Synthflow’s first version of the product at the beginning of 2024 before releasing an enterprise-grade version of the tech at the end of the year. The company grew 15x last year and has seen over 90% retention from its enterprise customers, according to Astabatsyan.

“We process 5 million calls monthly,” he said. “Last year, it was like, I don’t know, 1 million, 2 million, and then we started growing very quickly. This is where Synthflow started really getting better and better because we had this velocity.”

The startup also recently raised a $20 million Series A round led by Accel with participation from existing investors Atlantic Labs and Singular. Astabatsyan said the company raised this recent round so that it could expand its team, boost research and development, and open its first U.S. office in an undecided location.

Luca Bocchio, a partner at Accel, told TechCrunch that the Accel team had been tracking Synthflow since it started developing its first product. What stood out to Bocchio was the founding team’s drive and its early push into building enterprise-friendly integrations.

“This team has [had] really strong views since the get-go about creating more depth with the technology and extensive integrations across CRMs, across tools enterprises may use to really provide enterprise-grade compliance,” Bocchio said.

Regardless of the company’s traction, conversational AI seems poised to be a tough category. There are numerous other companies building in the space, including Bret Taylor’s Sierra, which has raised $285 million in VC money, and Bland AI, which has raised more than $50 million in venture funding, to name a couple.

“AI is moving so fast, and sometimes things happen faster than you would expect,” Astabatsyan said. “But for us, it’s very clear. We’re at this stage where, I would say, [we’re] in a post-product-market-fit era, where we know who our customers are. We have a pretty clear idea what’s our product roadmap, and where we want to be in the next three to five years.”

Source link
#Synthflow #cutting #noise #loud #voice #category

Tag

Related Posts


Since LIGO’s Nobel-winning discovery of gravitational waves—ripples in spacetime—the U.S.-based detector has been picking up on hundreds of signals from black hole mergers. And, after a decade of studying gravitational waves, researchers believe a significant fraction of black holes may come from cosmic chain reactions.

A recent paper published in Physical Review Letters describes an analysis of 155 pairs of binary black holes, identified by LIGO and its sisters, Virgo and KAGRA, in Italy and Japan, respectively. According to the study, about 14% of merging black holes may be what’s called “second-generation black holes,” or black holes that form from previous mergers of two smaller black holes. This “hierarchical” backstory is vastly different from the textbook version of how black holes emerge from the explosive death of a star.

“Overall in the universe, black holes are merging all the time,” Cailin Plunkett, the study’s first author and a graduate student at the Massachusetts Institute of Technology, told MIT News. “Now we’re seeing a relatively consistent picture where there’s a decent percentage of black holes that are coming from this repeated pathway.”

Tracking the invisible

Gravitational waves that reach Earth’s detectors typically come from extremely intense events. Over the years, LIGO has picked up some truly perplexing signals. For example, last summer it found the most colossal black hole merger ever—and if that wasn’t wild enough, the black holes that took part in the merger lie within a cosmic “dead zone” for black holes.

This zone refers to a range of black hole masses in which, physically speaking, black holes can’t form through ordinary stellar collapse. From these discoveries, astronomers realized just how little we knew about black holes, which are challenging to investigate directly. In that sense, it was a no-brainer that the ever-growing catalog of LIGO’s gravitational signals would turn up entirely new insights about black holes.

“It is increasingly clear, both from individual events and population analyses, that massive black holes exist in [this] range,” the researchers wrote in the latest paper. “These observations have spurred further investigation into mechanisms that can populate this gap.”

A wobbly imprint

The latest research represents one such investigation. During mergers, the two black holes spiral toward each other along an orbital plane. When one or both black hole spins are misaligned, the orbital plane can wobble, or “precess,” the researchers explained to MIT News. The degree to which the disk wobbles acts as a parameter from which researchers can measure the masses and spins of the merging black holes.

One telling sign of hierarchical mergers is that they’re “lopsided,” meaning one of the pair has a much higher spin and mass than the other. For the study, the team created an analytic model to capture the kind of wobble that would have emerged from second-generation black holes. Around 14% of merging black holes followed this pattern, and the second-generation black holes identified had a very specific range of masses, at around 20 solar masses or 40 solar masses and above.

Of mysterious origins

To be fair, that might not sound like a whole lot. But it demonstrates that a sizeable portion of known black holes indeed follow this pattern. As for why, the team suspects hierarchical mergers emerge from dense stellar environments. Simply, when multiple neighboring stars die and collapse into black holes, the dense environment can make it easier for those black holes to find each other and merge. That could further lead to the formation of second-generation black holes. Theoretically, this could “repeat potentially ad infinitum, by virtue of the fact that you have a ton of stars and black holes in this really dense environment,” Plunkett said.

But an ensuing mystery concerns those black holes in the 40-and-above regime, which coincides with the aforementioned “death zones” for black hole masses. According to stellar evolution theory, black holes born of supernovas shouldn’t leave any black holes above roughly 45 solar masses, explained Plunkett.

“Yet we have seen black holes that are that massive,” she mused. “And the question is: Where did they come from?”

For now, it’s hard to say when we’ll get an answer to that question, if ever. But one thing seems to be clear: black holes are a lot weirder than we could ever imagine.

#Scientists #Black #Holes #Born #Black #HolesBlack holes,Gravitational wave,LIGO">Scientists Say Some Black Holes Are Born From Other Black Holes Since LIGO’s Nobel-winning discovery of gravitational waves—ripples in spacetime—the U.S.-based detector has been picking up on hundreds of signals from black hole mergers. And, after a decade of studying gravitational waves, researchers believe a significant fraction of black holes may come from cosmic chain reactions. A recent paper published in Physical Review Letters describes an analysis of 155 pairs of binary black holes, identified by LIGO and its sisters, Virgo and KAGRA, in Italy and Japan, respectively. According to the study, about 14% of merging black holes may be what’s called “second-generation black holes,” or black holes that form from previous mergers of two smaller black holes. This “hierarchical” backstory is vastly different from the textbook version of how black holes emerge from the explosive death of a star. “Overall in the universe, black holes are merging all the time,” Cailin Plunkett, the study’s first author and a graduate student at the Massachusetts Institute of Technology, told MIT News. “Now we’re seeing a relatively consistent picture where there’s a decent percentage of black holes that are coming from this repeated pathway.” Tracking the invisible Gravitational waves that reach Earth’s detectors typically come from extremely intense events. Over the years, LIGO has picked up some truly perplexing signals. For example, last summer it found the most colossal black hole merger ever—and if that wasn’t wild enough, the black holes that took part in the merger lie within a cosmic “dead zone” for black holes. This zone refers to a range of black hole masses in which, physically speaking, black holes can’t form through ordinary stellar collapse. From these discoveries, astronomers realized just how little we knew about black holes, which are challenging to investigate directly. In that sense, it was a no-brainer that the ever-growing catalog of LIGO’s gravitational signals would turn up entirely new insights about black holes. “It is increasingly clear, both from individual events and population analyses, that massive black holes exist in [this] range,” the researchers wrote in the latest paper. “These observations have spurred further investigation into mechanisms that can populate this gap.” A wobbly imprint The latest research represents one such investigation. During mergers, the two black holes spiral toward each other along an orbital plane. When one or both black hole spins are misaligned, the orbital plane can wobble, or “precess,” the researchers explained to MIT News. The degree to which the disk wobbles acts as a parameter from which researchers can measure the masses and spins of the merging black holes. One telling sign of hierarchical mergers is that they’re “lopsided,” meaning one of the pair has a much higher spin and mass than the other. For the study, the team created an analytic model to capture the kind of wobble that would have emerged from second-generation black holes. Around 14% of merging black holes followed this pattern, and the second-generation black holes identified had a very specific range of masses, at around 20 solar masses or 40 solar masses and above. Of mysterious origins To be fair, that might not sound like a whole lot. But it demonstrates that a sizeable portion of known black holes indeed follow this pattern. As for why, the team suspects hierarchical mergers emerge from dense stellar environments. Simply, when multiple neighboring stars die and collapse into black holes, the dense environment can make it easier for those black holes to find each other and merge. That could further lead to the formation of second-generation black holes. Theoretically, this could “repeat potentially ad infinitum, by virtue of the fact that you have a ton of stars and black holes in this really dense environment,” Plunkett said. But an ensuing mystery concerns those black holes in the 40-and-above regime, which coincides with the aforementioned “death zones” for black hole masses. According to stellar evolution theory, black holes born of supernovas shouldn’t leave any black holes above roughly 45 solar masses, explained Plunkett. “Yet we have seen black holes that are that massive,” she mused. “And the question is: Where did they come from?” For now, it’s hard to say when we’ll get an answer to that question, if ever. But one thing seems to be clear: black holes are a lot weirder than we could ever imagine. #Scientists #Black #Holes #Born #Black #HolesBlack holes,Gravitational wave,LIGO

Physical Review Letters describes an analysis of 155 pairs of binary black holes, identified by LIGO and its sisters, Virgo and KAGRA, in Italy and Japan, respectively. According to the study, about 14% of merging black holes may be what’s called “second-generation black holes,” or black holes that form from previous mergers of two smaller black holes. This “hierarchical” backstory is vastly different from the textbook version of how black holes emerge from the explosive death of a star.

“Overall in the universe, black holes are merging all the time,” Cailin Plunkett, the study’s first author and a graduate student at the Massachusetts Institute of Technology, told MIT News. “Now we’re seeing a relatively consistent picture where there’s a decent percentage of black holes that are coming from this repeated pathway.”

Tracking the invisible

Gravitational waves that reach Earth’s detectors typically come from extremely intense events. Over the years, LIGO has picked up some truly perplexing signals. For example, last summer it found the most colossal black hole merger ever—and if that wasn’t wild enough, the black holes that took part in the merger lie within a cosmic “dead zone” for black holes.

This zone refers to a range of black hole masses in which, physically speaking, black holes can’t form through ordinary stellar collapse. From these discoveries, astronomers realized just how little we knew about black holes, which are challenging to investigate directly. In that sense, it was a no-brainer that the ever-growing catalog of LIGO’s gravitational signals would turn up entirely new insights about black holes.

“It is increasingly clear, both from individual events and population analyses, that massive black holes exist in [this] range,” the researchers wrote in the latest paper. “These observations have spurred further investigation into mechanisms that can populate this gap.”

A wobbly imprint

The latest research represents one such investigation. During mergers, the two black holes spiral toward each other along an orbital plane. When one or both black hole spins are misaligned, the orbital plane can wobble, or “precess,” the researchers explained to MIT News. The degree to which the disk wobbles acts as a parameter from which researchers can measure the masses and spins of the merging black holes.

One telling sign of hierarchical mergers is that they’re “lopsided,” meaning one of the pair has a much higher spin and mass than the other. For the study, the team created an analytic model to capture the kind of wobble that would have emerged from second-generation black holes. Around 14% of merging black holes followed this pattern, and the second-generation black holes identified had a very specific range of masses, at around 20 solar masses or 40 solar masses and above.

Of mysterious origins

To be fair, that might not sound like a whole lot. But it demonstrates that a sizeable portion of known black holes indeed follow this pattern. As for why, the team suspects hierarchical mergers emerge from dense stellar environments. Simply, when multiple neighboring stars die and collapse into black holes, the dense environment can make it easier for those black holes to find each other and merge. That could further lead to the formation of second-generation black holes. Theoretically, this could “repeat potentially ad infinitum, by virtue of the fact that you have a ton of stars and black holes in this really dense environment,” Plunkett said.

But an ensuing mystery concerns those black holes in the 40-and-above regime, which coincides with the aforementioned “death zones” for black hole masses. According to stellar evolution theory, black holes born of supernovas shouldn’t leave any black holes above roughly 45 solar masses, explained Plunkett.

“Yet we have seen black holes that are that massive,” she mused. “And the question is: Where did they come from?”

For now, it’s hard to say when we’ll get an answer to that question, if ever. But one thing seems to be clear: black holes are a lot weirder than we could ever imagine.

#Scientists #Black #Holes #Born #Black #HolesBlack holes,Gravitational wave,LIGO">Scientists Say Some Black Holes Are Born From Other Black HolesScientists Say Some Black Holes Are Born From Other Black Holes Since LIGO’s Nobel-winning discovery of gravitational waves—ripples in spacetime—the U.S.-based detector has been picking up on hundreds of signals from black hole mergers. And, after a decade of studying gravitational waves, researchers believe a significant fraction of black holes may come from cosmic chain reactions. A recent paper published in Physical Review Letters describes an analysis of 155 pairs of binary black holes, identified by LIGO and its sisters, Virgo and KAGRA, in Italy and Japan, respectively. According to the study, about 14% of merging black holes may be what’s called “second-generation black holes,” or black holes that form from previous mergers of two smaller black holes. This “hierarchical” backstory is vastly different from the textbook version of how black holes emerge from the explosive death of a star. “Overall in the universe, black holes are merging all the time,” Cailin Plunkett, the study’s first author and a graduate student at the Massachusetts Institute of Technology, told MIT News. “Now we’re seeing a relatively consistent picture where there’s a decent percentage of black holes that are coming from this repeated pathway.” Tracking the invisible Gravitational waves that reach Earth’s detectors typically come from extremely intense events. Over the years, LIGO has picked up some truly perplexing signals. For example, last summer it found the most colossal black hole merger ever—and if that wasn’t wild enough, the black holes that took part in the merger lie within a cosmic “dead zone” for black holes. This zone refers to a range of black hole masses in which, physically speaking, black holes can’t form through ordinary stellar collapse. From these discoveries, astronomers realized just how little we knew about black holes, which are challenging to investigate directly. In that sense, it was a no-brainer that the ever-growing catalog of LIGO’s gravitational signals would turn up entirely new insights about black holes. “It is increasingly clear, both from individual events and population analyses, that massive black holes exist in [this] range,” the researchers wrote in the latest paper. “These observations have spurred further investigation into mechanisms that can populate this gap.” A wobbly imprint The latest research represents one such investigation. During mergers, the two black holes spiral toward each other along an orbital plane. When one or both black hole spins are misaligned, the orbital plane can wobble, or “precess,” the researchers explained to MIT News. The degree to which the disk wobbles acts as a parameter from which researchers can measure the masses and spins of the merging black holes. One telling sign of hierarchical mergers is that they’re “lopsided,” meaning one of the pair has a much higher spin and mass than the other. For the study, the team created an analytic model to capture the kind of wobble that would have emerged from second-generation black holes. Around 14% of merging black holes followed this pattern, and the second-generation black holes identified had a very specific range of masses, at around 20 solar masses or 40 solar masses and above. Of mysterious origins To be fair, that might not sound like a whole lot. But it demonstrates that a sizeable portion of known black holes indeed follow this pattern. As for why, the team suspects hierarchical mergers emerge from dense stellar environments. Simply, when multiple neighboring stars die and collapse into black holes, the dense environment can make it easier for those black holes to find each other and merge. That could further lead to the formation of second-generation black holes. Theoretically, this could “repeat potentially ad infinitum, by virtue of the fact that you have a ton of stars and black holes in this really dense environment,” Plunkett said. But an ensuing mystery concerns those black holes in the 40-and-above regime, which coincides with the aforementioned “death zones” for black hole masses. According to stellar evolution theory, black holes born of supernovas shouldn’t leave any black holes above roughly 45 solar masses, explained Plunkett. “Yet we have seen black holes that are that massive,” she mused. “And the question is: Where did they come from?” For now, it’s hard to say when we’ll get an answer to that question, if ever. But one thing seems to be clear: black holes are a lot weirder than we could ever imagine. #Scientists #Black #Holes #Born #Black #HolesBlack holes,Gravitational wave,LIGO

Since LIGO’s Nobel-winning discovery of gravitational waves—ripples in spacetime—the U.S.-based detector has been picking up on hundreds of signals from black hole mergers. And, after a decade of studying gravitational waves, researchers believe a significant fraction of black holes may come from cosmic chain reactions.

A recent paper published in Physical Review Letters describes an analysis of 155 pairs of binary black holes, identified by LIGO and its sisters, Virgo and KAGRA, in Italy and Japan, respectively. According to the study, about 14% of merging black holes may be what’s called “second-generation black holes,” or black holes that form from previous mergers of two smaller black holes. This “hierarchical” backstory is vastly different from the textbook version of how black holes emerge from the explosive death of a star.

“Overall in the universe, black holes are merging all the time,” Cailin Plunkett, the study’s first author and a graduate student at the Massachusetts Institute of Technology, told MIT News. “Now we’re seeing a relatively consistent picture where there’s a decent percentage of black holes that are coming from this repeated pathway.”

Tracking the invisible

Gravitational waves that reach Earth’s detectors typically come from extremely intense events. Over the years, LIGO has picked up some truly perplexing signals. For example, last summer it found the most colossal black hole merger ever—and if that wasn’t wild enough, the black holes that took part in the merger lie within a cosmic “dead zone” for black holes.

This zone refers to a range of black hole masses in which, physically speaking, black holes can’t form through ordinary stellar collapse. From these discoveries, astronomers realized just how little we knew about black holes, which are challenging to investigate directly. In that sense, it was a no-brainer that the ever-growing catalog of LIGO’s gravitational signals would turn up entirely new insights about black holes.

“It is increasingly clear, both from individual events and population analyses, that massive black holes exist in [this] range,” the researchers wrote in the latest paper. “These observations have spurred further investigation into mechanisms that can populate this gap.”

A wobbly imprint

The latest research represents one such investigation. During mergers, the two black holes spiral toward each other along an orbital plane. When one or both black hole spins are misaligned, the orbital plane can wobble, or “precess,” the researchers explained to MIT News. The degree to which the disk wobbles acts as a parameter from which researchers can measure the masses and spins of the merging black holes.

One telling sign of hierarchical mergers is that they’re “lopsided,” meaning one of the pair has a much higher spin and mass than the other. For the study, the team created an analytic model to capture the kind of wobble that would have emerged from second-generation black holes. Around 14% of merging black holes followed this pattern, and the second-generation black holes identified had a very specific range of masses, at around 20 solar masses or 40 solar masses and above.

Of mysterious origins

To be fair, that might not sound like a whole lot. But it demonstrates that a sizeable portion of known black holes indeed follow this pattern. As for why, the team suspects hierarchical mergers emerge from dense stellar environments. Simply, when multiple neighboring stars die and collapse into black holes, the dense environment can make it easier for those black holes to find each other and merge. That could further lead to the formation of second-generation black holes. Theoretically, this could “repeat potentially ad infinitum, by virtue of the fact that you have a ton of stars and black holes in this really dense environment,” Plunkett said.

But an ensuing mystery concerns those black holes in the 40-and-above regime, which coincides with the aforementioned “death zones” for black hole masses. According to stellar evolution theory, black holes born of supernovas shouldn’t leave any black holes above roughly 45 solar masses, explained Plunkett.

“Yet we have seen black holes that are that massive,” she mused. “And the question is: Where did they come from?”

For now, it’s hard to say when we’ll get an answer to that question, if ever. But one thing seems to be clear: black holes are a lot weirder than we could ever imagine.

#Scientists #Black #Holes #Born #Black #HolesBlack holes,Gravitational wave,LIGO

Ready for the 2026 World Cup final? You might think you are, but your body is going to have to be prepared to put in some work—especially if your favorite team makes it.

Research shows that watching high-pressure matches can raise your heart rate, increase your stress levels, and put extra strain on your cardiovascular system.

According to a recent study from researchers at Bielefeld University in Germany, fans’ physiological stress increases by about 41 percent during a soccer final compared to a normal day. Heart rate also rose significantly, jumping from 70.9 beats per minute to 78.7 beats per minute—a difference even when compared to other weekends.

Researchers at Bielefeld tracked 229 fans of the German club Arminia Bielefeld for three months. Participants wore smartwatches that continuously recorded heart rate and an estimated stress index based on heart rate variability, allowing researchers to compare the day of the 2025 German Cup final with the days leading up to the match.

The physiological reaction to the soccer final began long before the match began. The researchers saw fans’ stress levels begin to rise in the morning and peak just before kickoff. Even after the final whistle, viewers showed signs of elevated stress.

Where you watch the game also makes a difference. The study found that fans who watched at the stadium had an average heart rate of 94.2 beats per minute compared to 79.4 among those who watched the match on television. After their team’s first goal, those in the stands saw their heart rate climb to an average of up to 108 beats per minute—a much more intense response than that observed in other contexts.

Alcohol consumption appeared to amplify that effect. Participants who reported drinking during the game had a heart rate approximately 5 percent higher than the rest of the fans during the match and nearly 12 percent higher after their team’s first goal. Although the researchers did not assess medical risks, they note that alcohol can increase cardiovascular strain when people are in an emotional state.

During the first few minutes of the match, when the outcome was still uncertain, heart rates reached their highest levels. Once the game seemed to be decided, fans’ heart rates dropped.

However, two goals scored in the final minutes caused them to spike again, even though the chances of a comeback were practically nil. (You can only imagine how fast Argentina fans’ hearts were thumping during this week’s furious comeback against Egypt.) For the authors, this reflects that the body responds not only to the objective chances of winning but also to emotions such as hope, pride, or attachment to the team.

The findings align with the results of previous studies on the physiological impacts of soccer. That incluides a study published in the New England Journal of Medicine after the 2006 World Cup in Germany, found that the risk of suffering an acute cardiovascular event nearly triples during German national team matches among people with preexisting heart conditions.

Subsequent research shows that matches can lead to an increase in stress hormones such as cortisol and found that fans who identify more strongly with their team exhibit more intense biological responses during decisive matches.

This article originally appeared on WIRED en Español and has been translated from Spanish.

#Watching #Soccer #Final #Body #Scienceworld cup 2026,sports,health,soccer,stress,fandom">What Watching a Soccer Final Does to Your Body, According to ScienceReady for the 2026 World Cup final? You might think you are, but your body is going to have to be prepared to put in some work—especially if your favorite team makes it.Research shows that watching high-pressure matches can raise your heart rate, increase your stress levels, and put extra strain on your cardiovascular system.According to a recent study from researchers at Bielefeld University in Germany, fans’ physiological stress increases by about 41 percent during a soccer final compared to a normal day. Heart rate also rose significantly, jumping from 70.9 beats per minute to 78.7 beats per minute—a difference even when compared to other weekends.Researchers at Bielefeld tracked 229 fans of the German club Arminia Bielefeld for three months. Participants wore smartwatches that continuously recorded heart rate and an estimated stress index based on heart rate variability, allowing researchers to compare the day of the 2025 German Cup final with the days leading up to the match.The physiological reaction to the soccer final began long before the match began. The researchers saw fans’ stress levels begin to rise in the morning and peak just before kickoff. Even after the final whistle, viewers showed signs of elevated stress.Where you watch the game also makes a difference. The study found that fans who watched at the stadium had an average heart rate of 94.2 beats per minute compared to 79.4 among those who watched the match on television. After their team’s first goal, those in the stands saw their heart rate climb to an average of up to 108 beats per minute—a much more intense response than that observed in other contexts.Alcohol consumption appeared to amplify that effect. Participants who reported drinking during the game had a heart rate approximately 5 percent higher than the rest of the fans during the match and nearly 12 percent higher after their team’s first goal. Although the researchers did not assess medical risks, they note that alcohol can increase cardiovascular strain when people are in an emotional state.During the first few minutes of the match, when the outcome was still uncertain, heart rates reached their highest levels. Once the game seemed to be decided, fans’ heart rates dropped.However, two goals scored in the final minutes caused them to spike again, even though the chances of a comeback were practically nil. (You can only imagine how fast Argentina fans’ hearts were thumping during this week’s furious comeback against Egypt.) For the authors, this reflects that the body responds not only to the objective chances of winning but also to emotions such as hope, pride, or attachment to the team.The findings align with the results of previous studies on the physiological impacts of soccer. That incluides a study published in the New England Journal of Medicine after the 2006 World Cup in Germany, found that the risk of suffering an acute cardiovascular event nearly triples during German national team matches among people with preexisting heart conditions.Subsequent research shows that matches can lead to an increase in stress hormones such as cortisol and found that fans who identify more strongly with their team exhibit more intense biological responses during decisive matches.This article originally appeared on WIRED en Español and has been translated from Spanish.#Watching #Soccer #Final #Body #Scienceworld cup 2026,sports,health,soccer,stress,fandom

2026 World Cup final? You might think you are, but your body is going to have to be prepared to put in some work—especially if your favorite team makes it.

Research shows that watching high-pressure matches can raise your heart rate, increase your stress levels, and put extra strain on your cardiovascular system.

According to a recent study from researchers at Bielefeld University in Germany, fans’ physiological stress increases by about 41 percent during a soccer final compared to a normal day. Heart rate also rose significantly, jumping from 70.9 beats per minute to 78.7 beats per minute—a difference even when compared to other weekends.

Researchers at Bielefeld tracked 229 fans of the German club Arminia Bielefeld for three months. Participants wore smartwatches that continuously recorded heart rate and an estimated stress index based on heart rate variability, allowing researchers to compare the day of the 2025 German Cup final with the days leading up to the match.

The physiological reaction to the soccer final began long before the match began. The researchers saw fans’ stress levels begin to rise in the morning and peak just before kickoff. Even after the final whistle, viewers showed signs of elevated stress.

Where you watch the game also makes a difference. The study found that fans who watched at the stadium had an average heart rate of 94.2 beats per minute compared to 79.4 among those who watched the match on television. After their team’s first goal, those in the stands saw their heart rate climb to an average of up to 108 beats per minute—a much more intense response than that observed in other contexts.

Alcohol consumption appeared to amplify that effect. Participants who reported drinking during the game had a heart rate approximately 5 percent higher than the rest of the fans during the match and nearly 12 percent higher after their team’s first goal. Although the researchers did not assess medical risks, they note that alcohol can increase cardiovascular strain when people are in an emotional state.

During the first few minutes of the match, when the outcome was still uncertain, heart rates reached their highest levels. Once the game seemed to be decided, fans’ heart rates dropped.

However, two goals scored in the final minutes caused them to spike again, even though the chances of a comeback were practically nil. (You can only imagine how fast Argentina fans’ hearts were thumping during this week’s furious comeback against Egypt.) For the authors, this reflects that the body responds not only to the objective chances of winning but also to emotions such as hope, pride, or attachment to the team.

The findings align with the results of previous studies on the physiological impacts of soccer. That incluides a study published in the New England Journal of Medicine after the 2006 World Cup in Germany, found that the risk of suffering an acute cardiovascular event nearly triples during German national team matches among people with preexisting heart conditions.

Subsequent research shows that matches can lead to an increase in stress hormones such as cortisol and found that fans who identify more strongly with their team exhibit more intense biological responses during decisive matches.

This article originally appeared on WIRED en Español and has been translated from Spanish.

#Watching #Soccer #Final #Body #Scienceworld cup 2026,sports,health,soccer,stress,fandom">What Watching a Soccer Final Does to Your Body, According to Science

Ready for the 2026 World Cup final? You might think you are, but your body is going to have to be prepared to put in some work—especially if your favorite team makes it.

Research shows that watching high-pressure matches can raise your heart rate, increase your stress levels, and put extra strain on your cardiovascular system.

According to a recent study from researchers at Bielefeld University in Germany, fans’ physiological stress increases by about 41 percent during a soccer final compared to a normal day. Heart rate also rose significantly, jumping from 70.9 beats per minute to 78.7 beats per minute—a difference even when compared to other weekends.

Researchers at Bielefeld tracked 229 fans of the German club Arminia Bielefeld for three months. Participants wore smartwatches that continuously recorded heart rate and an estimated stress index based on heart rate variability, allowing researchers to compare the day of the 2025 German Cup final with the days leading up to the match.

The physiological reaction to the soccer final began long before the match began. The researchers saw fans’ stress levels begin to rise in the morning and peak just before kickoff. Even after the final whistle, viewers showed signs of elevated stress.

Where you watch the game also makes a difference. The study found that fans who watched at the stadium had an average heart rate of 94.2 beats per minute compared to 79.4 among those who watched the match on television. After their team’s first goal, those in the stands saw their heart rate climb to an average of up to 108 beats per minute—a much more intense response than that observed in other contexts.

Alcohol consumption appeared to amplify that effect. Participants who reported drinking during the game had a heart rate approximately 5 percent higher than the rest of the fans during the match and nearly 12 percent higher after their team’s first goal. Although the researchers did not assess medical risks, they note that alcohol can increase cardiovascular strain when people are in an emotional state.

During the first few minutes of the match, when the outcome was still uncertain, heart rates reached their highest levels. Once the game seemed to be decided, fans’ heart rates dropped.

However, two goals scored in the final minutes caused them to spike again, even though the chances of a comeback were practically nil. (You can only imagine how fast Argentina fans’ hearts were thumping during this week’s furious comeback against Egypt.) For the authors, this reflects that the body responds not only to the objective chances of winning but also to emotions such as hope, pride, or attachment to the team.

The findings align with the results of previous studies on the physiological impacts of soccer. That incluides a study published in the New England Journal of Medicine after the 2006 World Cup in Germany, found that the risk of suffering an acute cardiovascular event nearly triples during German national team matches among people with preexisting heart conditions.

Subsequent research shows that matches can lead to an increase in stress hormones such as cortisol and found that fans who identify more strongly with their team exhibit more intense biological responses during decisive matches.

This article originally appeared on WIRED en Español and has been translated from Spanish.

#Watching #Soccer #Final #Body #Scienceworld cup 2026,sports,health,soccer,stress,fandom

These days, new versions of AI chatbots don’t just launch; they’re unshackled and released to the public following government scrutiny. OpenAI’s new GPT-5.6 models were – like Anthropic’s Claude Mythos and Fable – apparently too powerful to just launch; but now, after some tinkering, they’re available to you, dear customer.

In practice, it simply means that the new GPT-5.6 models are very powerful and smarter than before. In its introductory post, OpenAI shared a bunch of graphs showing just how much better GPT-5.6 is than the competition, whilst using fewer tokens and generally costing less.

OK, great. But GPT-5.6 is not just one model; it comes in three distinct flavors: Sol, Terra, and Luna. So what do different kinds of users get, what should they pay for, and which models should they (mostly) use? Let’s dive in.

Free users get (almost) nothing

Sorry; if you’re not a paying customer, you’ll have to make do with OpenAI’s previous flagship model, GPT-5.5. Any sort of access to GPT-5.6 models requires a subscription of some sort. Fortunately, GPT-5.5 is still quite capable at most tasks, but if you want the best of the best, you’ll have to cough up the dough.

There’s an exception to this: Free and Go users can access GPT-5.6 through ChatGPT Work. More on that below.

If you’re a Plus or Business user, you can only get Sol (the most powerful model) at medium and higher effort settings. There’s another, higher level of performance called Sol Pro, but that’s only available for Pro and Enterprise users.

In terms of availability per one million tokens, the prices are: $5 input and $30 output for Sol. $2.5 input and $15 output for Terra, and $1 input and $6 output for Luna.

SEE ALSO: Visa is connecting with ChatGPT to let AI agents automatically make purchases

Sol, Terra, or Luna?

Why are there three models in the first place? Well, OpenAI always had a multi-tier model; for example, previously users were able to choose a “mini” version of the main model to get results done cheaper. Now, the model has been split into three tiers.

If you’re a paying customer, you’re free to use all three. But you know how it is in the world of LLMs: If you pick the smartest one, your usage limits will get hit faster (yes, there are always usage limits, even if you throw a ton of money at OpenAI).

In the simplest sense, GPT-5.6 Sol is the smartest model, Terra is in between (with roughly GPT-5.5 level of performance), and Luna is the cheapest, fastest, but also least capable of the bunch.

The breakdown is as follows: Terra is a “balanced” model for everyday work. That’s the one you should be asking most of your questions. Don’t underestimate it, though, as OpenAI claims it performs better than Anthropic’s Fable 5 in some cases.

Luna is cost-efficient, and should be used for easy, non crucial everyday tasks; think recipes and movie recommendations. Again, OpenAI says it outperforms Anthropic’s Opus 4.8 in some cases, so it’s not a slouch, either.

Sol should be reserved for coding, deep research, planning, and cybersecurity: The most demanding tasks. Of course it comes at a (literal) cost: While OpenAI claims it spends less tokens than Anthropic’s Fable 5, Sol will still hit usage limits a lot faster than the other variants.

Fun fact: If you ask GPT-5.5 about any of this, right now, it’ll give you completely wrong answers. Hopefully OpenAI will fix this soon.

Wait, what’s this ChatGPT Work thing, then?

Oh yeah, OpenAI also launched ChatGPT Work, which is a new agent in ChatGPT that can access and take actions on your apps and files, and work in the background until a task is finished. It’s powered by Codex (OpenAI’s software engineering agent) and GPT-5.6. Think about it as your buddy that will go through your emails and files, browse the web, fetch the relevant data, and create that presentation your boss wants before the day is done.

ChatGPT Work is rolling out to Pro, Enterprise and Edu users first on web and mobile; this will be expanded to Plus and Business users “over the next few days.”

On the desktop, Work is available for everyone, including Free users.

Oh, and one more thing: The fact that ChatGPT Work has a built-in browser also means that OpenAI is sunsetting its standalone web browser, Atlas. Sorry.

How about GPT Live?

GPT Live is a new version of ChatGPT Voice and it will show up when you start talking to ChatGPT.

We’ve covered this in more depth here, but the bottom line is that GPT Live can listen and speak at the same time, allowing it to keep up a more realistic conversation.

Wrapping it all up

The new GPT-5.6 model is smart. It comes in three flavors: Luna, Terra, and Sol, with Sol being the most capable variant, Luna the most affordable one, and Terra somewhere in the middle. You can currently only get them on paid tiers, unless you’re using ChatGPT Work on desktop. And ChatGPT Voice has also gotten smarter with GPT-Live underneath, a model that can listen and speak at the same time.

Topics Artificial Intelligence OpenAI

#GPT5.6 #Sol #Terra #Luna">GPT-5.6 Sol, Terra, and Luna are here. See which one’s best for you. These days, new versions of AI chatbots don’t just launch; they’re unshackled and released to the public following government scrutiny. OpenAI’s new GPT-5.6 models were – like Anthropic’s Claude Mythos and Fable – apparently too powerful to just launch; but now, after some tinkering, they’re available to you, dear customer.In practice, it simply means that the new GPT-5.6 models are very powerful and smarter than before. In its introductory post, OpenAI shared a bunch of graphs showing just how much better GPT-5.6 is than the competition, whilst using fewer tokens and generally costing less. OK, great. But GPT-5.6 is not just one model; it comes in three distinct flavors: Sol, Terra, and Luna. So what do different kinds of users get, what should they pay for, and which models should they (mostly) use? Let’s dive in. Free users get (almost) nothingSorry; if you’re not a paying customer, you’ll have to make do with OpenAI’s previous flagship model, GPT-5.5. Any sort of access to GPT-5.6 models requires a subscription of some sort. Fortunately, GPT-5.5 is still quite capable at most tasks, but if you want the best of the best, you’ll have to cough up the dough. There’s an exception to this: Free and Go users can access GPT-5.6 through ChatGPT Work. More on that below. If you’re a Plus or Business user, you can only get Sol (the most powerful model) at medium and higher effort settings. There’s another, higher level of performance called Sol Pro, but that’s only available for Pro and Enterprise users. In terms of availability per one million tokens, the prices are: input and output for Sol. .5 input and output for Terra, and input and output for Luna. SEE ALSO: Visa is connecting with ChatGPT to let AI agents automatically make purchases Sol, Terra, or Luna?Why are there three models in the first place? Well, OpenAI always had a multi-tier model; for example, previously users were able to choose a “mini” version of the main model to get results done cheaper. Now, the model has been split into three tiers. If you’re a paying customer, you’re free to use all three. But you know how it is in the world of LLMs: If you pick the smartest one, your usage limits will get hit faster (yes, there are always usage limits, even if you throw a ton of money at OpenAI). Mashable Light Speed In the simplest sense, GPT-5.6 Sol is the smartest model, Terra is in between (with roughly GPT-5.5 level of performance), and Luna is the cheapest, fastest, but also least capable of the bunch. The breakdown is as follows: Terra is a “balanced” model for everyday work. That’s the one you should be asking most of your questions. Don’t underestimate it, though, as OpenAI claims it performs better than Anthropic’s Fable 5 in some cases. Luna is cost-efficient, and should be used for easy, non crucial everyday tasks; think recipes and movie recommendations. Again, OpenAI says it outperforms Anthropic’s Opus 4.8 in some cases, so it’s not a slouch, either.Sol should be reserved for coding, deep research, planning, and cybersecurity: The most demanding tasks. Of course it comes at a (literal) cost: While OpenAI claims it spends less tokens than Anthropic’s Fable 5, Sol will still hit usage limits a lot faster than the other variants. Fun fact: If you ask GPT-5.5 about any of this, right now, it’ll give you completely wrong answers. Hopefully OpenAI will fix this soon.Wait, what’s this ChatGPT Work thing, then?Oh yeah, OpenAI also launched ChatGPT Work, which is a new agent in ChatGPT that can access and take actions on your apps and files, and work in the background until a task is finished. It’s powered by Codex (OpenAI’s software engineering agent) and GPT-5.6. Think about it as your buddy that will go through your emails and files, browse the web, fetch the relevant data, and create that presentation your boss wants before the day is done. ChatGPT Work is rolling out to Pro, Enterprise and Edu users first on web and mobile; this will be expanded to Plus and Business users “over the next few days.”On the desktop, Work is available for everyone, including Free users. Oh, and one more thing: The fact that ChatGPT Work has a built-in browser also means that OpenAI is sunsetting its standalone web browser, Atlas. Sorry. How about GPT Live?GPT Live is a new version of ChatGPT Voice and it will show up when you start talking to ChatGPT. We’ve covered this in more depth here, but the bottom line is that GPT Live can listen and speak at the same time, allowing it to keep up a more realistic conversation.Wrapping it all upThe new GPT-5.6 model is smart. It comes in three flavors: Luna, Terra, and Sol, with Sol being the most capable variant, Luna the most affordable one, and Terra somewhere in the middle. You can currently only get them on paid tiers, unless you’re using ChatGPT Work on desktop. And ChatGPT Voice has also gotten smarter with GPT-Live underneath, a model that can listen and speak at the same time. Topics Artificial Intelligence OpenAI #GPT5.6 #Sol #Terra #Luna

Fable – apparently too powerful to just launch; but now, after some tinkering, they’re available to you, dear customer.

In practice, it simply means that the new GPT-5.6 models are very powerful and smarter than before. In its introductory post, OpenAI shared a bunch of graphs showing just how much better GPT-5.6 is than the competition, whilst using fewer tokens and generally costing less.

OK, great. But GPT-5.6 is not just one model; it comes in three distinct flavors: Sol, Terra, and Luna. So what do different kinds of users get, what should they pay for, and which models should they (mostly) use? Let’s dive in.

Free users get (almost) nothing

Sorry; if you’re not a paying customer, you’ll have to make do with OpenAI’s previous flagship model, GPT-5.5. Any sort of access to GPT-5.6 models requires a subscription of some sort. Fortunately, GPT-5.5 is still quite capable at most tasks, but if you want the best of the best, you’ll have to cough up the dough.

There’s an exception to this: Free and Go users can access GPT-5.6 through ChatGPT Work. More on that below.

If you’re a Plus or Business user, you can only get Sol (the most powerful model) at medium and higher effort settings. There’s another, higher level of performance called Sol Pro, but that’s only available for Pro and Enterprise users.

In terms of availability per one million tokens, the prices are: $5 input and $30 output for Sol. $2.5 input and $15 output for Terra, and $1 input and $6 output for Luna.

SEE ALSO: Visa is connecting with ChatGPT to let AI agents automatically make purchases

Sol, Terra, or Luna?

Why are there three models in the first place? Well, OpenAI always had a multi-tier model; for example, previously users were able to choose a “mini” version of the main model to get results done cheaper. Now, the model has been split into three tiers.

If you’re a paying customer, you’re free to use all three. But you know how it is in the world of LLMs: If you pick the smartest one, your usage limits will get hit faster (yes, there are always usage limits, even if you throw a ton of money at OpenAI).

In the simplest sense, GPT-5.6 Sol is the smartest model, Terra is in between (with roughly GPT-5.5 level of performance), and Luna is the cheapest, fastest, but also least capable of the bunch.

The breakdown is as follows: Terra is a “balanced” model for everyday work. That’s the one you should be asking most of your questions. Don’t underestimate it, though, as OpenAI claims it performs better than Anthropic’s Fable 5 in some cases.

Luna is cost-efficient, and should be used for easy, non crucial everyday tasks; think recipes and movie recommendations. Again, OpenAI says it outperforms Anthropic’s Opus 4.8 in some cases, so it’s not a slouch, either.

Sol should be reserved for coding, deep research, planning, and cybersecurity: The most demanding tasks. Of course it comes at a (literal) cost: While OpenAI claims it spends less tokens than Anthropic’s Fable 5, Sol will still hit usage limits a lot faster than the other variants.

Fun fact: If you ask GPT-5.5 about any of this, right now, it’ll give you completely wrong answers. Hopefully OpenAI will fix this soon.

Wait, what’s this ChatGPT Work thing, then?

Oh yeah, OpenAI also launched ChatGPT Work, which is a new agent in ChatGPT that can access and take actions on your apps and files, and work in the background until a task is finished. It’s powered by Codex (OpenAI’s software engineering agent) and GPT-5.6. Think about it as your buddy that will go through your emails and files, browse the web, fetch the relevant data, and create that presentation your boss wants before the day is done.

ChatGPT Work is rolling out to Pro, Enterprise and Edu users first on web and mobile; this will be expanded to Plus and Business users “over the next few days.”

On the desktop, Work is available for everyone, including Free users.

Oh, and one more thing: The fact that ChatGPT Work has a built-in browser also means that OpenAI is sunsetting its standalone web browser, Atlas. Sorry.

How about GPT Live?

GPT Live is a new version of ChatGPT Voice and it will show up when you start talking to ChatGPT.

We’ve covered this in more depth here, but the bottom line is that GPT Live can listen and speak at the same time, allowing it to keep up a more realistic conversation.

Wrapping it all up

The new GPT-5.6 model is smart. It comes in three flavors: Luna, Terra, and Sol, with Sol being the most capable variant, Luna the most affordable one, and Terra somewhere in the middle. You can currently only get them on paid tiers, unless you’re using ChatGPT Work on desktop. And ChatGPT Voice has also gotten smarter with GPT-Live underneath, a model that can listen and speak at the same time.

Topics Artificial Intelligence OpenAI

#GPT5.6 #Sol #Terra #Luna">GPT-5.6 Sol, Terra, and Luna are here. See which one’s best for you.

These days, new versions of AI chatbots don’t just launch; they’re unshackled and released to the public following government scrutiny. OpenAI’s new GPT-5.6 models were – like Anthropic’s Claude Mythos and Fable – apparently too powerful to just launch; but now, after some tinkering, they’re available to you, dear customer.

In practice, it simply means that the new GPT-5.6 models are very powerful and smarter than before. In its introductory post, OpenAI shared a bunch of graphs showing just how much better GPT-5.6 is than the competition, whilst using fewer tokens and generally costing less.

OK, great. But GPT-5.6 is not just one model; it comes in three distinct flavors: Sol, Terra, and Luna. So what do different kinds of users get, what should they pay for, and which models should they (mostly) use? Let’s dive in.

Free users get (almost) nothing

Sorry; if you’re not a paying customer, you’ll have to make do with OpenAI’s previous flagship model, GPT-5.5. Any sort of access to GPT-5.6 models requires a subscription of some sort. Fortunately, GPT-5.5 is still quite capable at most tasks, but if you want the best of the best, you’ll have to cough up the dough.

There’s an exception to this: Free and Go users can access GPT-5.6 through ChatGPT Work. More on that below.

If you’re a Plus or Business user, you can only get Sol (the most powerful model) at medium and higher effort settings. There’s another, higher level of performance called Sol Pro, but that’s only available for Pro and Enterprise users.

In terms of availability per one million tokens, the prices are: $5 input and $30 output for Sol. $2.5 input and $15 output for Terra, and $1 input and $6 output for Luna.

SEE ALSO: Visa is connecting with ChatGPT to let AI agents automatically make purchases

Sol, Terra, or Luna?

Why are there three models in the first place? Well, OpenAI always had a multi-tier model; for example, previously users were able to choose a “mini” version of the main model to get results done cheaper. Now, the model has been split into three tiers.

If you’re a paying customer, you’re free to use all three. But you know how it is in the world of LLMs: If you pick the smartest one, your usage limits will get hit faster (yes, there are always usage limits, even if you throw a ton of money at OpenAI).

In the simplest sense, GPT-5.6 Sol is the smartest model, Terra is in between (with roughly GPT-5.5 level of performance), and Luna is the cheapest, fastest, but also least capable of the bunch.

The breakdown is as follows: Terra is a “balanced” model for everyday work. That’s the one you should be asking most of your questions. Don’t underestimate it, though, as OpenAI claims it performs better than Anthropic’s Fable 5 in some cases.

Luna is cost-efficient, and should be used for easy, non crucial everyday tasks; think recipes and movie recommendations. Again, OpenAI says it outperforms Anthropic’s Opus 4.8 in some cases, so it’s not a slouch, either.

Sol should be reserved for coding, deep research, planning, and cybersecurity: The most demanding tasks. Of course it comes at a (literal) cost: While OpenAI claims it spends less tokens than Anthropic’s Fable 5, Sol will still hit usage limits a lot faster than the other variants.

Fun fact: If you ask GPT-5.5 about any of this, right now, it’ll give you completely wrong answers. Hopefully OpenAI will fix this soon.

Wait, what’s this ChatGPT Work thing, then?

Oh yeah, OpenAI also launched ChatGPT Work, which is a new agent in ChatGPT that can access and take actions on your apps and files, and work in the background until a task is finished. It’s powered by Codex (OpenAI’s software engineering agent) and GPT-5.6. Think about it as your buddy that will go through your emails and files, browse the web, fetch the relevant data, and create that presentation your boss wants before the day is done.

ChatGPT Work is rolling out to Pro, Enterprise and Edu users first on web and mobile; this will be expanded to Plus and Business users “over the next few days.”

On the desktop, Work is available for everyone, including Free users.

Oh, and one more thing: The fact that ChatGPT Work has a built-in browser also means that OpenAI is sunsetting its standalone web browser, Atlas. Sorry.

How about GPT Live?

GPT Live is a new version of ChatGPT Voice and it will show up when you start talking to ChatGPT.

We’ve covered this in more depth here, but the bottom line is that GPT Live can listen and speak at the same time, allowing it to keep up a more realistic conversation.

Wrapping it all up

The new GPT-5.6 model is smart. It comes in three flavors: Luna, Terra, and Sol, with Sol being the most capable variant, Luna the most affordable one, and Terra somewhere in the middle. You can currently only get them on paid tiers, unless you’re using ChatGPT Work on desktop. And ChatGPT Voice has also gotten smarter with GPT-Live underneath, a model that can listen and speak at the same time.

Topics Artificial Intelligence OpenAI

#GPT5.6 #Sol #Terra #Luna

Post Comment