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How Smart Devices Are Actually Built: An Engineer’s View Pick up any smart device you own. A doorbell that recognizes faces, a watch that reads your heart rhythm, a thermostat that learns when you leave for work. They feel simple. You tap, they respond. That simplicity is a lie. A useful one, but a lie. Behind the clean app and the satisfying click is a stack of engineering decisions that most people never see. And the gap between a device that works for five years and one that dies in eight months almost always traces back to those invisible choices. So let’s look at what actually goes into building the connected gadgets shipping in 2026. Smart starts with the circuit board, not the cloud Most coverage of smart devices jumps straight to AI features and voice assistants. But the foundation is physical. A device is a printed circuit board, a microcontroller, a fistful of sensors, a radio, and a battery, all crammed into a shell that has to survive being dropped, sat on, and left in a hot car. This is where hardware development does its quiet, unglamorous work. Engineers pick a microcontroller based on how much computing the device needs versus how little power it can afford to burn. They route signal traces on the board so a Wi-Fi radio doesn’t drown out a delicate sensor reading. They run the whole thing through thermal testing, drop testing, and certification for FCC and CE marks before it can legally ship. Get this layer wrong, and no amount of clever software saves you. A poorly designed board produces flaky sensor data. Bad antenna placement means the device drops off your network the moment you walk to the next room. These aren’t software bugs. You can’t patch your way out of a physics problem. The companies building good hardware treat the proof-of-concept stage as a real checkpoint. They wire up development boards and modular parts to test the core idea cheaply, before committing to a custom design that costs real money to manufacture. It’s the boring discipline that separates products from expensive paperweights. Firmware is where the device actually thinks Sitting on top of the hardware is firmware. This is the low-level code that tells the chip what to do, when to wake up, how to read a sensor, and when to phone home. People mix up firmware and software all the time, so here’s the clean split. Software runs on your phone or in the cloud and handles the screens you tap. Firmware lives inside the device and controls the hardware directly. Firmware is genuinely hard to write well. The constraints are brutal. A typical IoT microcontroller has a tiny amount of memory, often measured in kilobytes, and it might run on a coin cell that needs to last a year. Every line of code competes for space and power. Then there’s timing. A lot of devices need deterministic, real-time behavior, meaning a sensor reading has to be processed within a fixed window or the whole thing falls apart. A heart monitor that processes a beat “eventually” is useless. The firmware has to guarantee it happens now. If you want the deep version of how this gets built in practice, Yalantis published a solid breakdown of firmware development for embedded IoT devices that covers architecture, power management, and the over-the-air update workflows that keep a device current after it ships. The OTA piece matters more than it sounds. A device that can’t safely update its own firmware is frozen in time the day it leaves the factory. Connectivity is a series of trade-offs Your smart device has to talk to something. Your phone, your router, a cloud server, or all three. Choosing how it talks is one of the most consequential engineering calls in the whole project, and there’s no single right answer. Bluetooth Low Energy sips power and works great for a wearable talking to your phone, but its range is short and it can’t reach the internet on its own. Wi-Fi reaches everything but drains batteries fast. LoRaWAN travels for miles on almost no power, which is perfect for a soil sensor in a field, but it carries tiny amounts of data slowly. Cellular options like NB-IoT and LTE-M let a device work anywhere there’s a signal, with the catch of ongoing data costs and bigger power draw. Engineers usually mix these. A fitness band might use BLE to sync with your phone, and your phone carries the data the rest of the way. An industrial sensor in a remote location might use LoRaWAN to a gateway, which then forwards everything over cellular. The “right” combination depends entirely on power budget, data volume, range, and cost, which is exactly why this decision gets made early and gets revisited often. Sensors and the messy job of trusting them A smart device is only as good as the data it collects. And raw sensor data is messy. Take a simple temperature reading. The sensor drifts over time. It gets warmed by the heat of the chip sitting next to it. It returns noisy values that jitter up and down even when nothing changes. Firmware has to calibrate, filter, and sanity-check all of it before the device acts on a single number. This gets serious fast in regulated fields. A continuous glucose monitor or a medical wearable can’t ship a reading that’s “close enough.” The sensor design, the calibration, and the firmware that validates the data all have to meet standards that consumer gadgets never face. The engineering bar is much higher, and the cost of getting it wrong is measured in patient safety, not customer reviews. For everyday devices the stakes are lower, but the principle holds. Good devices spend a lot of hidden effort turning unreliable physical signals into numbers you can actually trust. Where the AI hype meets the silicon Here’s the part that has changed most recently. A growing share of smart devices now run machine learning models directly on the chip instead of sending everything to the cloud. This is edge computing, and it’s reshaping how devices get built. The appeal is obvious. Processing data on the device means lower latency, since you’re not waiting on a round trip to a server. It means better privacy, because your data never leaves your hand. And it means the device keeps working when your internet goes down. The catch is that running a model on a chip with kilobytes of memory is an engineering puzzle. Models have to be shrunk, quantized, and optimized until they fit in the space available without melting the battery. The face-recognition that runs locally on a modern doorbell is a heavily compressed version of what would run on a server. Squeezing it down to fit is real, specialized work, and it’s increasingly where the competitive difference between two similar gadgets actually lives. Security can’t be the last step For years, connected devices treated security as an afterthought. Ship the product, patch problems later. That approach has aged badly. Outdated firmware is now one of the most common ways attackers break into IoT systems. Research from the security firm ONEKEY found that vulnerable firmware accounts for a large majority of successful attacks on connected devices. Once an attacker is inside one poorly secured gadget on your network, they have a foothold to reach everything else. Building security in from the start means encrypting data both when it’s stored on the device and when it travels to the cloud. It means signing firmware updates so a device only accepts legitimate code, not something an attacker swapped in. And it means designing for recovery, so a compromised device can be safely reset and restored rather than turned into a permanent liability sitting on your shelf. This is the layer consumers never think about and pay the most for when it’s done badly. Why the next generation is harder to build Smart devices are getting more capable, and that capability has a cost that lands squarely on the engineering team. More on-device intelligence. Stricter privacy rules. Longer battery expectations. Tighter security. Regulatory scrutiny that used to apply only to medical gear now creeping toward consumer products too. None of this shows up in the marketing. The ad shows a person tapping a screen and a light turning on. What it doesn’t show is the year of board revisions, firmware rewrites, connectivity tests, and security audits that made that tap reliable. So the next time a smart device just works, give a small nod to the invisible stack underneath. The clean experience on the surface is the product of a lot of unglamorous engineering refusing to cut corners. That refusal is the whole difference between a gadget you trust and one you return. #Smart #Devices #Built #Engineers #Viewengineering,smart devices

How Smart Devices Are Actually Built: An Engineer’s View

Pick up any smart device you own. A doorbell that recognizes faces, a watch that reads your heart rhythm, a thermostat that learns when you leave for work. They feel simple. You tap, they respond.

That simplicity is a lie. A useful one, but a lie.

Behind the clean app and the satisfying click is a stack of engineering decisions that most people never see. And the gap between a device that works for five years and one that dies in eight months almost always traces back to those invisible choices. So let’s look at what actually goes into building the connected gadgets shipping in 2026.

Smart starts with the circuit board, not the cloud

Most coverage of smart devices jumps straight to AI features and voice assistants. But the foundation is physical. A device is a printed circuit board, a microcontroller, a fistful of sensors, a radio, and a battery, all crammed into a shell that has to survive being dropped, sat on, and left in a hot car.

This is where hardware development does its quiet, unglamorous work. Engineers pick a microcontroller based on how much computing the device needs versus how little power it can afford to burn. They route signal traces on the board so a Wi-Fi radio doesn’t drown out a delicate sensor reading. They run the whole thing through thermal testing, drop testing, and certification for FCC and CE marks before it can legally ship.

Get this layer wrong, and no amount of clever software saves you. A poorly designed board produces flaky sensor data. Bad antenna placement means the device drops off your network the moment you walk to the next room. These aren’t software bugs. You can’t patch your way out of a physics problem.

The companies building good hardware treat the proof-of-concept stage as a real checkpoint. They wire up development boards and modular parts to test the core idea cheaply, before committing to a custom design that costs real money to manufacture. It’s the boring discipline that separates products from expensive paperweights.

Firmware is where the device actually thinks

Sitting on top of the hardware is firmware. This is the low-level code that tells the chip what to do, when to wake up, how to read a sensor, and when to phone home. People mix up firmware and software all the time, so here’s the clean split. Software runs on your phone or in the cloud and handles the screens you tap. Firmware lives inside the device and controls the hardware directly.

Firmware is genuinely hard to write well. The constraints are brutal. A typical IoT microcontroller has a tiny amount of memory, often measured in kilobytes, and it might run on a coin cell that needs to last a year. Every line of code competes for space and power.

Then there’s timing. A lot of devices need deterministic, real-time behavior, meaning a sensor reading has to be processed within a fixed window or the whole thing falls apart. A heart monitor that processes a beat “eventually” is useless. The firmware has to guarantee it happens now.

If you want the deep version of how this gets built in practice, Yalantis published a solid breakdown of firmware development for embedded IoT devices that covers architecture, power management, and the over-the-air update workflows that keep a device current after it ships. The OTA piece matters more than it sounds. A device that can’t safely update its own firmware is frozen in time the day it leaves the factory.

Connectivity is a series of trade-offs

Your smart device has to talk to something. Your phone, your router, a cloud server, or all three. Choosing how it talks is one of the most consequential engineering calls in the whole project, and there’s no single right answer.

Bluetooth Low Energy sips power and works great for a wearable talking to your phone, but its range is short and it can’t reach the internet on its own. Wi-Fi reaches everything but drains batteries fast. LoRaWAN travels for miles on almost no power, which is perfect for a soil sensor in a field, but it carries tiny amounts of data slowly. Cellular options like NB-IoT and LTE-M let a device work anywhere there’s a signal, with the catch of ongoing data costs and bigger power draw.

Engineers usually mix these. A fitness band might use BLE to sync with your phone, and your phone carries the data the rest of the way. An industrial sensor in a remote location might use LoRaWAN to a gateway, which then forwards everything over cellular. The “right” combination depends entirely on power budget, data volume, range, and cost, which is exactly why this decision gets made early and gets revisited often.

Sensors and the messy job of trusting them

A smart device is only as good as the data it collects. And raw sensor data is messy.

Take a simple temperature reading. The sensor drifts over time. It gets warmed by the heat of the chip sitting next to it. It returns noisy values that jitter up and down even when nothing changes. Firmware has to calibrate, filter, and sanity-check all of it before the device acts on a single number.

This gets serious fast in regulated fields. A continuous glucose monitor or a medical wearable can’t ship a reading that’s “close enough.” The sensor design, the calibration, and the firmware that validates the data all have to meet standards that consumer gadgets never face. The engineering bar is much higher, and the cost of getting it wrong is measured in patient safety, not customer reviews.

For everyday devices the stakes are lower, but the principle holds. Good devices spend a lot of hidden effort turning unreliable physical signals into numbers you can actually trust.

Where the AI hype meets the silicon

Here’s the part that has changed most recently. A growing share of smart devices now run machine learning models directly on the chip instead of sending everything to the cloud. This is edge computing, and it’s reshaping how devices get built.

The appeal is obvious. Processing data on the device means lower latency, since you’re not waiting on a round trip to a server. It means better privacy, because your data never leaves your hand. And it means the device keeps working when your internet goes down.

The catch is that running a model on a chip with kilobytes of memory is an engineering puzzle. Models have to be shrunk, quantized, and optimized until they fit in the space available without melting the battery. The face-recognition that runs locally on a modern doorbell is a heavily compressed version of what would run on a server. Squeezing it down to fit is real, specialized work, and it’s increasingly where the competitive difference between two similar gadgets actually lives.

Security can’t be the last step

For years, connected devices treated security as an afterthought. Ship the product, patch problems later. That approach has aged badly.

Outdated firmware is now one of the most common ways attackers break into IoT systems. Research from the security firm ONEKEY found that vulnerable firmware accounts for a large majority of successful attacks on connected devices. Once an attacker is inside one poorly secured gadget on your network, they have a foothold to reach everything else.

Building security in from the start means encrypting data both when it’s stored on the device and when it travels to the cloud. It means signing firmware updates so a device only accepts legitimate code, not something an attacker swapped in. And it means designing for recovery, so a compromised device can be safely reset and restored rather than turned into a permanent liability sitting on your shelf.

This is the layer consumers never think about and pay the most for when it’s done badly.

Why the next generation is harder to build

Smart devices are getting more capable, and that capability has a cost that lands squarely on the engineering team. More on-device intelligence. Stricter privacy rules. Longer battery expectations. Tighter security. Regulatory scrutiny that used to apply only to medical gear now creeping toward consumer products too.

None of this shows up in the marketing. The ad shows a person tapping a screen and a light turning on. What it doesn’t show is the year of board revisions, firmware rewrites, connectivity tests, and security audits that made that tap reliable.

So the next time a smart device just works, give a small nod to the invisible stack underneath. The clean experience on the surface is the product of a lot of unglamorous engineering refusing to cut corners. That refusal is the whole difference between a gadget you trust and one you return.

#Smart #Devices #Built #Engineers #Viewengineering,smart devices

Tech-news ,

Pick up any smart device you own. A doorbell that recognizes faces, a watch that reads your heart rhythm, a thermostat that learns when you leave for work. They feel simple. You tap, they respond.

That simplicity is a lie. A useful one, but a lie.

Behind the clean app and the satisfying click is a stack of engineering decisions that most people never see. And the gap between a device that works for five years and one that dies in eight months almost always traces back to those invisible choices. So let’s look at what actually goes into building the connected gadgets shipping in 2026.

Smart starts with the circuit board, not the cloud

Most coverage of smart devices jumps straight to AI features and voice assistants. But the foundation is physical. A device is a printed circuit board, a microcontroller, a fistful of sensors, a radio, and a battery, all crammed into a shell that has to survive being dropped, sat on, and left in a hot car.

This is where hardware development does its quiet, unglamorous work. Engineers pick a microcontroller based on how much computing the device needs versus how little power it can afford to burn. They route signal traces on the board so a Wi-Fi radio doesn’t drown out a delicate sensor reading. They run the whole thing through thermal testing, drop testing, and certification for FCC and CE marks before it can legally ship.

Get this layer wrong, and no amount of clever software saves you. A poorly designed board produces flaky sensor data. Bad antenna placement means the device drops off your network the moment you walk to the next room. These aren’t software bugs. You can’t patch your way out of a physics problem.

The companies building good hardware treat the proof-of-concept stage as a real checkpoint. They wire up development boards and modular parts to test the core idea cheaply, before committing to a custom design that costs real money to manufacture. It’s the boring discipline that separates products from expensive paperweights.

Firmware is where the device actually thinks

Sitting on top of the hardware is firmware. This is the low-level code that tells the chip what to do, when to wake up, how to read a sensor, and when to phone home. People mix up firmware and software all the time, so here’s the clean split. Software runs on your phone or in the cloud and handles the screens you tap. Firmware lives inside the device and controls the hardware directly.

Firmware is genuinely hard to write well. The constraints are brutal. A typical IoT microcontroller has a tiny amount of memory, often measured in kilobytes, and it might run on a coin cell that needs to last a year. Every line of code competes for space and power.

Then there’s timing. A lot of devices need deterministic, real-time behavior, meaning a sensor reading has to be processed within a fixed window or the whole thing falls apart. A heart monitor that processes a beat “eventually” is useless. The firmware has to guarantee it happens now.

If you want the deep version of how this gets built in practice, Yalantis published a solid breakdown of firmware development for embedded IoT devices that covers architecture, power management, and the over-the-air update workflows that keep a device current after it ships. The OTA piece matters more than it sounds. A device that can’t safely update its own firmware is frozen in time the day it leaves the factory.

Connectivity is a series of trade-offs

Your smart device has to talk to something. Your phone, your router, a cloud server, or all three. Choosing how it talks is one of the most consequential engineering calls in the whole project, and there’s no single right answer.

Bluetooth Low Energy sips power and works great for a wearable talking to your phone, but its range is short and it can’t reach the internet on its own. Wi-Fi reaches everything but drains batteries fast. LoRaWAN travels for miles on almost no power, which is perfect for a soil sensor in a field, but it carries tiny amounts of data slowly. Cellular options like NB-IoT and LTE-M let a device work anywhere there’s a signal, with the catch of ongoing data costs and bigger power draw.

Engineers usually mix these. A fitness band might use BLE to sync with your phone, and your phone carries the data the rest of the way. An industrial sensor in a remote location might use LoRaWAN to a gateway, which then forwards everything over cellular. The “right” combination depends entirely on power budget, data volume, range, and cost, which is exactly why this decision gets made early and gets revisited often.

Sensors and the messy job of trusting them

A smart device is only as good as the data it collects. And raw sensor data is messy.

Take a simple temperature reading. The sensor drifts over time. It gets warmed by the heat of the chip sitting next to it. It returns noisy values that jitter up and down even when nothing changes. Firmware has to calibrate, filter, and sanity-check all of it before the device acts on a single number.

This gets serious fast in regulated fields. A continuous glucose monitor or a medical wearable can’t ship a reading that’s “close enough.” The sensor design, the calibration, and the firmware that validates the data all have to meet standards that consumer gadgets never face. The engineering bar is much higher, and the cost of getting it wrong is measured in patient safety, not customer reviews.

For everyday devices the stakes are lower, but the principle holds. Good devices spend a lot of hidden effort turning unreliable physical signals into numbers you can actually trust.

Where the AI hype meets the silicon

Here’s the part that has changed most recently. A growing share of smart devices now run machine learning models directly on the chip instead of sending everything to the cloud. This is edge computing, and it’s reshaping how devices get built.

The appeal is obvious. Processing data on the device means lower latency, since you’re not waiting on a round trip to a server. It means better privacy, because your data never leaves your hand. And it means the device keeps working when your internet goes down.

The catch is that running a model on a chip with kilobytes of memory is an engineering puzzle. Models have to be shrunk, quantized, and optimized until they fit in the space available without melting the battery. The face-recognition that runs locally on a modern doorbell is a heavily compressed version of what would run on a server. Squeezing it down to fit is real, specialized work, and it’s increasingly where the competitive difference between two similar gadgets actually lives.

Security can’t be the last step

For years, connected devices treated security as an afterthought. Ship the product, patch problems later. That approach has aged badly.

Outdated firmware is now one of the most common ways attackers break into IoT systems. Research from the security firm ONEKEY found that vulnerable firmware accounts for a large majority of successful attacks on connected devices. Once an attacker is inside one poorly secured gadget on your network, they have a foothold to reach everything else.

Building security in from the start means encrypting data both when it’s stored on the device and when it travels to the cloud. It means signing firmware updates so a device only accepts legitimate code, not something an attacker swapped in. And it means designing for recovery, so a compromised device can be safely reset and restored rather than turned into a permanent liability sitting on your shelf.

This is the layer consumers never think about and pay the most for when it’s done badly.

Why the next generation is harder to build

Smart devices are getting more capable, and that capability has a cost that lands squarely on the engineering team. More on-device intelligence. Stricter privacy rules. Longer battery expectations. Tighter security. Regulatory scrutiny that used to apply only to medical gear now creeping toward consumer products too.

None of this shows up in the marketing. The ad shows a person tapping a screen and a light turning on. What it doesn’t show is the year of board revisions, firmware rewrites, connectivity tests, and security audits that made that tap reliable.

So the next time a smart device just works, give a small nod to the invisible stack underneath. The clean experience on the surface is the product of a lot of unglamorous engineering refusing to cut corners. That refusal is the whole difference between a gadget you trust and one you return.

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Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.  

Wang is in talks to raise about $200 million at a $2 billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.

Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment.

The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised $400 million at a $3.8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.

Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety.

Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.)

At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#OpenAI #researcher #Miles #Wang #talks #launch #drug #discovery #startup #valued #TechCrunchdrug discovery,lightspeed,OpenAI">OpenAI researcher Miles Wang in talks to launch AI drug discovery startup valued at B | TechCrunch Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.   Wang is in talks to raise about 0 million at a billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change. Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment. The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised 0 million at a .8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a .1 billion Series B in May. Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety. Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.) At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#OpenAI #researcher #Miles #Wang #talks #launch #drug #discovery #startup #valued #TechCrunchdrug discovery,lightspeed,OpenAI

Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.  

Wang is in talks to raise about $200 million at a $2 billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.

Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment.

The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised $400 million at a $3.8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.

Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety.

Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.)

At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#OpenAI #researcher #Miles #Wang #talks #launch #drug #discovery #startup #valued #TechCrunchdrug discovery,lightspeed,OpenAI">OpenAI researcher Miles Wang in talks to launch AI drug discovery startup valued at $2B | TechCrunch

Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.  

Wang is in talks to raise about $200 million at a $2 billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.

Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment.

The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised $400 million at a $3.8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.

Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety.

Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.)

At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#OpenAI #researcher #Miles #Wang #talks #launch #drug #discovery #startup #valued #TechCrunchdrug discovery,lightspeed,OpenAI
The Esports World Cup 2026 has just begun in Paris and is expected to see thousands of players compete over the coming weeks. The tournament will continue until August 23 at the Paris Expo Porte de Versailles. The event has seen the participation of over 2,000 professional players and over 200 esports teams from over 100 nations. With a record $75 million prize pool on the line, the event promises weeks of intense competition across some of the world’s most popular games like PUBG Mobile. Here’s everything you need to know.

Players had to compete through the biggest qualification program in Esports World Cup history. More than 1.5 million players joined the qualification process. Organizers hosted around 330 qualifying tournaments, publisher leagues, and international circuits worldwide. Only the best-performing players and teams reached the final stage in Paris.

Club Championship Returns with Massive Rewards

The Club Championship remains one of the major highlights of the Esports World Cup 2026. Points can be scored by different teams playing many games over seven weeks. The championship will not be about winning a particular title but rather about the clubs’ performance. As much as $30 million in total will be awarded across different positions, with the winner receiving $7 million. Team Falcons will aim for another successful campaign after winning previous editions.

The Esports World Cup 2026 has retained Cristiano Ronaldo and Magnus Carlsen as Global Ambassadors. Both icons represent excellence in their respective fields. The involvement of these individuals enables the link between the worlds of esports, football, and chess.

[embed]https://www.youtube.com/watch?v=ZGJhWLYQjrU[/embed]

Games Included in Esports World Cup 2026

The Esports World Cup 2026 comprises 25 tournaments across 24 esports titles. Some of the best-known games on PC, console, and mobile platforms will be represented in this list.

VALORANTCounter-Strike 2Dota 2
League of LegendsPUBG MOBILEPUBG: Battlegrounds
FortniteApex LegendsRocket League
EA SPORTS FC 26Call of Duty: Black Ops 7Call of Duty: Warzone
ChessTekken 8Street Fighter 6
Honor of KingsMobile Legends: Bang BangOverwatch 2
Rainbow Six Siege XTeamfight TacticsFree Fire
CrossfireFatal Fury: City of the WolvesTrackmania

The 2026 Esports World Cup will be widely available on TV and online platforms. Viewers from more than 160 countries can follow the tournament on television and the Internet. Coverage will be available in more than 40 languages worldwide, and over 100 broadcasting partners will air the tournament. There will be over 7,000 hours of live coverage and 5,000 official co-streamers.

#Esports #World #Cup #Opens #PariseSports">Esports World Cup 2026 Opens in Paris: Everything You Need to Know The Esports World Cup 2026 has just begun in Paris and is expected to see thousands of players compete over the coming weeks. The tournament will continue until August 23 at the Paris Expo Porte de Versailles. The event has seen the participation of over 2,000 professional players and over 200 esports teams from over 100 nations. With a record million prize pool on the line, the event promises weeks of intense competition across some of the world’s most popular games like PUBG Mobile. Here’s everything you need to know. Players had to compete through the biggest qualification program in Esports World Cup history. More than 1.5 million players joined the qualification process. Organizers hosted around 330 qualifying tournaments, publisher leagues, and international circuits worldwide. Only the best-performing players and teams reached the final stage in Paris. Club Championship Returns with Massive Rewards The Club Championship remains one of the major highlights of the Esports World Cup 2026. Points can be scored by different teams playing many games over seven weeks. The championship will not be about winning a particular title but rather about the clubs’ performance. As much as million in total will be awarded across different positions, with the winner receiving million. Team Falcons will aim for another successful campaign after winning previous editions. The Esports World Cup 2026 has retained Cristiano Ronaldo and Magnus Carlsen as Global Ambassadors. Both icons represent excellence in their respective fields. The involvement of these individuals enables the link between the worlds of esports, football, and chess. [embed]https://www.youtube.com/watch?v=ZGJhWLYQjrU[/embed] Games Included in Esports World Cup 2026 The Esports World Cup 2026 comprises 25 tournaments across 24 esports titles. Some of the best-known games on PC, console, and mobile platforms will be represented in this list. VALORANTCounter-Strike 2Dota 2League of LegendsPUBG MOBILEPUBG: BattlegroundsFortniteApex LegendsRocket LeagueEA SPORTS FC 26Call of Duty: Black Ops 7Call of Duty: WarzoneChessTekken 8Street Fighter 6Honor of KingsMobile Legends: Bang BangOverwatch 2Rainbow Six Siege XTeamfight TacticsFree FireCrossfireFatal Fury: City of the WolvesTrackmania The 2026 Esports World Cup will be widely available on TV and online platforms. Viewers from more than 160 countries can follow the tournament on television and the Internet. Coverage will be available in more than 40 languages worldwide, and over 100 broadcasting partners will air the tournament. There will be over 7,000 hours of live coverage and 5,000 official co-streamers. #Esports #World #Cup #Opens #PariseSports

PUBG Mobile. Here’s everything you need to know.

Players had to compete through the biggest qualification program in Esports World Cup history. More than 1.5 million players joined the qualification process. Organizers hosted around 330 qualifying tournaments, publisher leagues, and international circuits worldwide. Only the best-performing players and teams reached the final stage in Paris.

Club Championship Returns with Massive Rewards

The Club Championship remains one of the major highlights of the Esports World Cup 2026. Points can be scored by different teams playing many games over seven weeks. The championship will not be about winning a particular title but rather about the clubs’ performance. As much as $30 million in total will be awarded across different positions, with the winner receiving $7 million. Team Falcons will aim for another successful campaign after winning previous editions.

The Esports World Cup 2026 has retained Cristiano Ronaldo and Magnus Carlsen as Global Ambassadors. Both icons represent excellence in their respective fields. The involvement of these individuals enables the link between the worlds of esports, football, and chess.

[embed]https://www.youtube.com/watch?v=ZGJhWLYQjrU[/embed]

Games Included in Esports World Cup 2026

The Esports World Cup 2026 comprises 25 tournaments across 24 esports titles. Some of the best-known games on PC, console, and mobile platforms will be represented in this list.

VALORANTCounter-Strike 2Dota 2
League of LegendsPUBG MOBILEPUBG: Battlegrounds
FortniteApex LegendsRocket League
EA SPORTS FC 26Call of Duty: Black Ops 7Call of Duty: Warzone
ChessTekken 8Street Fighter 6
Honor of KingsMobile Legends: Bang BangOverwatch 2
Rainbow Six Siege XTeamfight TacticsFree Fire
CrossfireFatal Fury: City of the WolvesTrackmania

The 2026 Esports World Cup will be widely available on TV and online platforms. Viewers from more than 160 countries can follow the tournament on television and the Internet. Coverage will be available in more than 40 languages worldwide, and over 100 broadcasting partners will air the tournament. There will be over 7,000 hours of live coverage and 5,000 official co-streamers.

#Esports #World #Cup #Opens #PariseSports">Esports World Cup 2026 Opens in Paris: Everything You Need to Know

The Esports World Cup 2026 has just begun in Paris and is expected to see thousands of players compete over the coming weeks. The tournament will continue until August 23 at the Paris Expo Porte de Versailles. The event has seen the participation of over 2,000 professional players and over 200 esports teams from over 100 nations. With a record $75 million prize pool on the line, the event promises weeks of intense competition across some of the world’s most popular games like PUBG Mobile. Here’s everything you need to know.

Players had to compete through the biggest qualification program in Esports World Cup history. More than 1.5 million players joined the qualification process. Organizers hosted around 330 qualifying tournaments, publisher leagues, and international circuits worldwide. Only the best-performing players and teams reached the final stage in Paris.

Club Championship Returns with Massive Rewards

The Club Championship remains one of the major highlights of the Esports World Cup 2026. Points can be scored by different teams playing many games over seven weeks. The championship will not be about winning a particular title but rather about the clubs’ performance. As much as $30 million in total will be awarded across different positions, with the winner receiving $7 million. Team Falcons will aim for another successful campaign after winning previous editions.

The Esports World Cup 2026 has retained Cristiano Ronaldo and Magnus Carlsen as Global Ambassadors. Both icons represent excellence in their respective fields. The involvement of these individuals enables the link between the worlds of esports, football, and chess.

[embed]https://www.youtube.com/watch?v=ZGJhWLYQjrU[/embed]

Games Included in Esports World Cup 2026

The Esports World Cup 2026 comprises 25 tournaments across 24 esports titles. Some of the best-known games on PC, console, and mobile platforms will be represented in this list.

VALORANTCounter-Strike 2Dota 2
League of LegendsPUBG MOBILEPUBG: Battlegrounds
FortniteApex LegendsRocket League
EA SPORTS FC 26Call of Duty: Black Ops 7Call of Duty: Warzone
ChessTekken 8Street Fighter 6
Honor of KingsMobile Legends: Bang BangOverwatch 2
Rainbow Six Siege XTeamfight TacticsFree Fire
CrossfireFatal Fury: City of the WolvesTrackmania

The 2026 Esports World Cup will be widely available on TV and online platforms. Viewers from more than 160 countries can follow the tournament on television and the Internet. Coverage will be available in more than 40 languages worldwide, and over 100 broadcasting partners will air the tournament. There will be over 7,000 hours of live coverage and 5,000 official co-streamers.

#Esports #World #Cup #Opens #PariseSports

Like it or not, data centers are now intrinsic to our modern lives, supporting not just the AI boom but healthcare, banking, government services, and other essential sectors. Reliable data center operation depends on effective cooling, which is already a major challenge as many methods require huge inputs of water or energy. To make matters worse, new research suggests that one of our cheapest, most efficient cooling strategies could stop working in a warmer world.

The findings, published Monday in the journal Scientific Reports, show that rising temperatures and humidity levels threaten the viability of direct air free cooling, an energy-efficient, waterless technique that pulls outside air in to cool data center servers. Over the past 45 years, weather conditions that limit direct air cooling have become significantly more common, particularly across the tropics and the southeastern United States, according to the study. As the global temperature continues to rise, this problem is only going to get worse.

“We found that periods of time when temperature and humidity exceed recommended operating thresholds for direct air free cooling are becoming more frequent and lasting longer in many regions,” lead author Christina Karamperidou, a professor of atmospheric sciences professor at the University of Hawaii at Mānoa, said in a statement. “This will reduce the availability of air free cooling for a growing number of data centers globally.”

Climate-driven cooling constraints

For direct air free cooling, the American Society of Heating, Refrigerating and Air-Conditioning Engineers recommends keeping the air entering a data center between 64 and 81 degrees Fahrenheit (18 and 27 degrees Celsius), with 10% to 70% relative humidity and a dew point below 59 degrees F (15 degrees C). Air that is hotter and more humid than this won’t cool the servers effectively and could corrode metal components.

To investigate how this cooling method will function in a warmer, wetter world, Karamperidou and her colleagues used a combination of high-resolution hourly weather observations, climate model simulations, and global records of data center locations. With this data, they evaluated how often environmental conditions exceeded recommended operating limits for direct air free cooling over the past 45 years and in future climate scenarios.

The researchers found that the prevalence of weather conditions that limit direct air free cooling has increased significantly in recent decades. Even regions that have only seen modest long-term increases in heat and humidity are experiencing longer daily exceedance events, and the share of data centers exposed to conditions that limit direct air free cooling availability for at least one quarter of the year is rising.

Interestingly, the findings suggest that the hottest, most humid days are intensifying faster than average days, indicating that environmental stress on direct air free cooling systems is become more and more concentrated in rare, highly consequential events.

“From an operational perspective, those worst-day conditions often drive contingency planning, system overrides, redundancy requirements, and reliability decisions,” Karamperidou said. “This suggests that infrastructure planning may need to account not only for average environmental conditions but also for how the most stressful days are changing over time.”

By 2050, the number of hours that exceed temperature and humidity limits for direct air free cooling is protected to increase under high greenhouse gas emissions scenarios, according to the researchers. In most regions globally, the average number of hours per day during which this cooling strategy is constrained increases by more than two hours per day, the findings show.

A troubling feedback loop

While this study focuses on how weather can influence data centers, it’s important to remember that data centers can influence local weather too. These facilities dissipate a lot of heat, and research has shown that they can actually create heat islands within a 6-mile radius of themselves.

Karamperidou and her colleagues did not account for this effect, so the direct air free cooling constraints they identified may be conservative, they write in their report. Still, they emphasize that their findings do not mean that this cooling strategy is necessarily infeasible in warm, humid regions. Rather, the study shows that the window of feasibility for direct air free cooling is narrowing due to climate change.

“Alternative strategies—including indirect evaporative cooling, liquid cooling, and hybrid architectures—can partially offset these constraints, albeit with distinct trade-offs in water use, system complexity, and operational design,” the researchers write.

Indeed, as one of the simplest, cheapest, and most efficient cooling strategies becomes increasingly unreliable, data center operators may be forced to turn to more energy- and water-intensive methods. This, in turn, could put added strain on electric grids and water resources that are themselves strained by climate change. Adapting data centers to a warming world without exacerbating the impacts of rising global temperatures will require innovative solutions.

#Cheapest #Cool #Data #Centers #Wont #Work #Warmer #WorldAI,data centers,extreme heat,Global warming">The Cheapest Way to Cool Data Centers Won’t Work in a Warmer World  Like it or not, data centers are now intrinsic to our modern lives, supporting not just the AI boom but healthcare, banking, government services, and other essential sectors. Reliable data center operation depends on effective cooling, which is already a major challenge as many methods require huge inputs of water or energy. To make matters worse, new research suggests that one of our cheapest, most efficient cooling strategies could stop working in a warmer world. The findings, published Monday in the journal Scientific Reports, show that rising temperatures and humidity levels threaten the viability of direct air free cooling, an energy-efficient, waterless technique that pulls outside air in to cool data center servers. Over the past 45 years, weather conditions that limit direct air cooling have become significantly more common, particularly across the tropics and the southeastern United States, according to the study. As the global temperature continues to rise, this problem is only going to get worse. “We found that periods of time when temperature and humidity exceed recommended operating thresholds for direct air free cooling are becoming more frequent and lasting longer in many regions,” lead author Christina Karamperidou, a professor of atmospheric sciences professor at the University of Hawaii at Mānoa, said in a statement. “This will reduce the availability of air free cooling for a growing number of data centers globally.” Climate-driven cooling constraints For direct air free cooling, the American Society of Heating, Refrigerating and Air-Conditioning Engineers recommends keeping the air entering a data center between 64 and 81 degrees Fahrenheit (18 and 27 degrees Celsius), with 10% to 70% relative humidity and a dew point below 59 degrees F (15 degrees C). Air that is hotter and more humid than this won’t cool the servers effectively and could corrode metal components. To investigate how this cooling method will function in a warmer, wetter world, Karamperidou and her colleagues used a combination of high-resolution hourly weather observations, climate model simulations, and global records of data center locations. With this data, they evaluated how often environmental conditions exceeded recommended operating limits for direct air free cooling over the past 45 years and in future climate scenarios. The researchers found that the prevalence of weather conditions that limit direct air free cooling has increased significantly in recent decades. Even regions that have only seen modest long-term increases in heat and humidity are experiencing longer daily exceedance events, and the share of data centers exposed to conditions that limit direct air free cooling availability for at least one quarter of the year is rising. Interestingly, the findings suggest that the hottest, most humid days are intensifying faster than average days, indicating that environmental stress on direct air free cooling systems is become more and more concentrated in rare, highly consequential events. “From an operational perspective, those worst-day conditions often drive contingency planning, system overrides, redundancy requirements, and reliability decisions,” Karamperidou said. “This suggests that infrastructure planning may need to account not only for average environmental conditions but also for how the most stressful days are changing over time.” By 2050, the number of hours that exceed temperature and humidity limits for direct air free cooling is protected to increase under high greenhouse gas emissions scenarios, according to the researchers. In most regions globally, the average number of hours per day during which this cooling strategy is constrained increases by more than two hours per day, the findings show. A troubling feedback loop While this study focuses on how weather can influence data centers, it’s important to remember that data centers can influence local weather too. These facilities dissipate a lot of heat, and research has shown that they can actually create heat islands within a 6-mile radius of themselves. Karamperidou and her colleagues did not account for this effect, so the direct air free cooling constraints they identified may be conservative, they write in their report. Still, they emphasize that their findings do not mean that this cooling strategy is necessarily infeasible in warm, humid regions. Rather, the study shows that the window of feasibility for direct air free cooling is narrowing due to climate change. “Alternative strategies—including indirect evaporative cooling, liquid cooling, and hybrid architectures—can partially offset these constraints, albeit with distinct trade-offs in water use, system complexity, and operational design,” the researchers write. Indeed, as one of the simplest, cheapest, and most efficient cooling strategies becomes increasingly unreliable, data center operators may be forced to turn to more energy- and water-intensive methods. This, in turn, could put added strain on electric grids and water resources that are themselves strained by climate change. Adapting data centers to a warming world without exacerbating the impacts of rising global temperatures will require innovative solutions. #Cheapest #Cool #Data #Centers #Wont #Work #Warmer #WorldAI,data centers,extreme heat,Global warming

AI boom but healthcare, banking, government services, and other essential sectors. Reliable data center operation depends on effective cooling, which is already a major challenge as many methods require huge inputs of water or energy. To make matters worse, new research suggests that one of our cheapest, most efficient cooling strategies could stop working in a warmer world.

The findings, published Monday in the journal Scientific Reports, show that rising temperatures and humidity levels threaten the viability of direct air free cooling, an energy-efficient, waterless technique that pulls outside air in to cool data center servers. Over the past 45 years, weather conditions that limit direct air cooling have become significantly more common, particularly across the tropics and the southeastern United States, according to the study. As the global temperature continues to rise, this problem is only going to get worse.

“We found that periods of time when temperature and humidity exceed recommended operating thresholds for direct air free cooling are becoming more frequent and lasting longer in many regions,” lead author Christina Karamperidou, a professor of atmospheric sciences professor at the University of Hawaii at Mānoa, said in a statement. “This will reduce the availability of air free cooling for a growing number of data centers globally.”

Climate-driven cooling constraints

For direct air free cooling, the American Society of Heating, Refrigerating and Air-Conditioning Engineers recommends keeping the air entering a data center between 64 and 81 degrees Fahrenheit (18 and 27 degrees Celsius), with 10% to 70% relative humidity and a dew point below 59 degrees F (15 degrees C). Air that is hotter and more humid than this won’t cool the servers effectively and could corrode metal components.

To investigate how this cooling method will function in a warmer, wetter world, Karamperidou and her colleagues used a combination of high-resolution hourly weather observations, climate model simulations, and global records of data center locations. With this data, they evaluated how often environmental conditions exceeded recommended operating limits for direct air free cooling over the past 45 years and in future climate scenarios.

The researchers found that the prevalence of weather conditions that limit direct air free cooling has increased significantly in recent decades. Even regions that have only seen modest long-term increases in heat and humidity are experiencing longer daily exceedance events, and the share of data centers exposed to conditions that limit direct air free cooling availability for at least one quarter of the year is rising.

Interestingly, the findings suggest that the hottest, most humid days are intensifying faster than average days, indicating that environmental stress on direct air free cooling systems is become more and more concentrated in rare, highly consequential events.

“From an operational perspective, those worst-day conditions often drive contingency planning, system overrides, redundancy requirements, and reliability decisions,” Karamperidou said. “This suggests that infrastructure planning may need to account not only for average environmental conditions but also for how the most stressful days are changing over time.”

By 2050, the number of hours that exceed temperature and humidity limits for direct air free cooling is protected to increase under high greenhouse gas emissions scenarios, according to the researchers. In most regions globally, the average number of hours per day during which this cooling strategy is constrained increases by more than two hours per day, the findings show.

A troubling feedback loop

While this study focuses on how weather can influence data centers, it’s important to remember that data centers can influence local weather too. These facilities dissipate a lot of heat, and research has shown that they can actually create heat islands within a 6-mile radius of themselves.

Karamperidou and her colleagues did not account for this effect, so the direct air free cooling constraints they identified may be conservative, they write in their report. Still, they emphasize that their findings do not mean that this cooling strategy is necessarily infeasible in warm, humid regions. Rather, the study shows that the window of feasibility for direct air free cooling is narrowing due to climate change.

“Alternative strategies—including indirect evaporative cooling, liquid cooling, and hybrid architectures—can partially offset these constraints, albeit with distinct trade-offs in water use, system complexity, and operational design,” the researchers write.

Indeed, as one of the simplest, cheapest, and most efficient cooling strategies becomes increasingly unreliable, data center operators may be forced to turn to more energy- and water-intensive methods. This, in turn, could put added strain on electric grids and water resources that are themselves strained by climate change. Adapting data centers to a warming world without exacerbating the impacts of rising global temperatures will require innovative solutions.

#Cheapest #Cool #Data #Centers #Wont #Work #Warmer #WorldAI,data centers,extreme heat,Global warming">The Cheapest Way to Cool Data Centers Won’t Work in a Warmer World The Cheapest Way to Cool Data Centers Won’t Work in a Warmer World  Like it or not, data centers are now intrinsic to our modern lives, supporting not just the AI boom but healthcare, banking, government services, and other essential sectors. Reliable data center operation depends on effective cooling, which is already a major challenge as many methods require huge inputs of water or energy. To make matters worse, new research suggests that one of our cheapest, most efficient cooling strategies could stop working in a warmer world. The findings, published Monday in the journal Scientific Reports, show that rising temperatures and humidity levels threaten the viability of direct air free cooling, an energy-efficient, waterless technique that pulls outside air in to cool data center servers. Over the past 45 years, weather conditions that limit direct air cooling have become significantly more common, particularly across the tropics and the southeastern United States, according to the study. As the global temperature continues to rise, this problem is only going to get worse. “We found that periods of time when temperature and humidity exceed recommended operating thresholds for direct air free cooling are becoming more frequent and lasting longer in many regions,” lead author Christina Karamperidou, a professor of atmospheric sciences professor at the University of Hawaii at Mānoa, said in a statement. “This will reduce the availability of air free cooling for a growing number of data centers globally.” Climate-driven cooling constraints For direct air free cooling, the American Society of Heating, Refrigerating and Air-Conditioning Engineers recommends keeping the air entering a data center between 64 and 81 degrees Fahrenheit (18 and 27 degrees Celsius), with 10% to 70% relative humidity and a dew point below 59 degrees F (15 degrees C). Air that is hotter and more humid than this won’t cool the servers effectively and could corrode metal components. To investigate how this cooling method will function in a warmer, wetter world, Karamperidou and her colleagues used a combination of high-resolution hourly weather observations, climate model simulations, and global records of data center locations. With this data, they evaluated how often environmental conditions exceeded recommended operating limits for direct air free cooling over the past 45 years and in future climate scenarios. The researchers found that the prevalence of weather conditions that limit direct air free cooling has increased significantly in recent decades. Even regions that have only seen modest long-term increases in heat and humidity are experiencing longer daily exceedance events, and the share of data centers exposed to conditions that limit direct air free cooling availability for at least one quarter of the year is rising. Interestingly, the findings suggest that the hottest, most humid days are intensifying faster than average days, indicating that environmental stress on direct air free cooling systems is become more and more concentrated in rare, highly consequential events. “From an operational perspective, those worst-day conditions often drive contingency planning, system overrides, redundancy requirements, and reliability decisions,” Karamperidou said. “This suggests that infrastructure planning may need to account not only for average environmental conditions but also for how the most stressful days are changing over time.” By 2050, the number of hours that exceed temperature and humidity limits for direct air free cooling is protected to increase under high greenhouse gas emissions scenarios, according to the researchers. In most regions globally, the average number of hours per day during which this cooling strategy is constrained increases by more than two hours per day, the findings show. A troubling feedback loop While this study focuses on how weather can influence data centers, it’s important to remember that data centers can influence local weather too. These facilities dissipate a lot of heat, and research has shown that they can actually create heat islands within a 6-mile radius of themselves. Karamperidou and her colleagues did not account for this effect, so the direct air free cooling constraints they identified may be conservative, they write in their report. Still, they emphasize that their findings do not mean that this cooling strategy is necessarily infeasible in warm, humid regions. Rather, the study shows that the window of feasibility for direct air free cooling is narrowing due to climate change. “Alternative strategies—including indirect evaporative cooling, liquid cooling, and hybrid architectures—can partially offset these constraints, albeit with distinct trade-offs in water use, system complexity, and operational design,” the researchers write. Indeed, as one of the simplest, cheapest, and most efficient cooling strategies becomes increasingly unreliable, data center operators may be forced to turn to more energy- and water-intensive methods. This, in turn, could put added strain on electric grids and water resources that are themselves strained by climate change. Adapting data centers to a warming world without exacerbating the impacts of rising global temperatures will require innovative solutions. #Cheapest #Cool #Data #Centers #Wont #Work #Warmer #WorldAI,data centers,extreme heat,Global warming

Like it or not, data centers are now intrinsic to our modern lives, supporting not just the AI boom but healthcare, banking, government services, and other essential sectors. Reliable data center operation depends on effective cooling, which is already a major challenge as many methods require huge inputs of water or energy. To make matters worse, new research suggests that one of our cheapest, most efficient cooling strategies could stop working in a warmer world.

The findings, published Monday in the journal Scientific Reports, show that rising temperatures and humidity levels threaten the viability of direct air free cooling, an energy-efficient, waterless technique that pulls outside air in to cool data center servers. Over the past 45 years, weather conditions that limit direct air cooling have become significantly more common, particularly across the tropics and the southeastern United States, according to the study. As the global temperature continues to rise, this problem is only going to get worse.

“We found that periods of time when temperature and humidity exceed recommended operating thresholds for direct air free cooling are becoming more frequent and lasting longer in many regions,” lead author Christina Karamperidou, a professor of atmospheric sciences professor at the University of Hawaii at Mānoa, said in a statement. “This will reduce the availability of air free cooling for a growing number of data centers globally.”

Climate-driven cooling constraints

For direct air free cooling, the American Society of Heating, Refrigerating and Air-Conditioning Engineers recommends keeping the air entering a data center between 64 and 81 degrees Fahrenheit (18 and 27 degrees Celsius), with 10% to 70% relative humidity and a dew point below 59 degrees F (15 degrees C). Air that is hotter and more humid than this won’t cool the servers effectively and could corrode metal components.

To investigate how this cooling method will function in a warmer, wetter world, Karamperidou and her colleagues used a combination of high-resolution hourly weather observations, climate model simulations, and global records of data center locations. With this data, they evaluated how often environmental conditions exceeded recommended operating limits for direct air free cooling over the past 45 years and in future climate scenarios.

The researchers found that the prevalence of weather conditions that limit direct air free cooling has increased significantly in recent decades. Even regions that have only seen modest long-term increases in heat and humidity are experiencing longer daily exceedance events, and the share of data centers exposed to conditions that limit direct air free cooling availability for at least one quarter of the year is rising.

Interestingly, the findings suggest that the hottest, most humid days are intensifying faster than average days, indicating that environmental stress on direct air free cooling systems is become more and more concentrated in rare, highly consequential events.

“From an operational perspective, those worst-day conditions often drive contingency planning, system overrides, redundancy requirements, and reliability decisions,” Karamperidou said. “This suggests that infrastructure planning may need to account not only for average environmental conditions but also for how the most stressful days are changing over time.”

By 2050, the number of hours that exceed temperature and humidity limits for direct air free cooling is protected to increase under high greenhouse gas emissions scenarios, according to the researchers. In most regions globally, the average number of hours per day during which this cooling strategy is constrained increases by more than two hours per day, the findings show.

A troubling feedback loop

While this study focuses on how weather can influence data centers, it’s important to remember that data centers can influence local weather too. These facilities dissipate a lot of heat, and research has shown that they can actually create heat islands within a 6-mile radius of themselves.

Karamperidou and her colleagues did not account for this effect, so the direct air free cooling constraints they identified may be conservative, they write in their report. Still, they emphasize that their findings do not mean that this cooling strategy is necessarily infeasible in warm, humid regions. Rather, the study shows that the window of feasibility for direct air free cooling is narrowing due to climate change.

“Alternative strategies—including indirect evaporative cooling, liquid cooling, and hybrid architectures—can partially offset these constraints, albeit with distinct trade-offs in water use, system complexity, and operational design,” the researchers write.

Indeed, as one of the simplest, cheapest, and most efficient cooling strategies becomes increasingly unreliable, data center operators may be forced to turn to more energy- and water-intensive methods. This, in turn, could put added strain on electric grids and water resources that are themselves strained by climate change. Adapting data centers to a warming world without exacerbating the impacts of rising global temperatures will require innovative solutions.

#Cheapest #Cool #Data #Centers #Wont #Work #Warmer #WorldAI,data centers,extreme heat,Global warming

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