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Microsoft will buy AI firm Nuance for $19.7 Billion to Bolster Healthcare Tech

Microsoft has agreed to buy the AI and voice communications firm Nuance for $19.7 billion.

The deal, expected to close at the end of the year, would value Nuance at $56 per share, implying a premium of 23% to the stock’s closing price on April 9.

Nuance is Microsoft’s second largest acquisition after its $24 billion purchase of LinkedIn in 2016.

Nuance’s speech recognition engine is the basis for Apple’s voice assistant Siri, and the company has developed Dragon Naturally Speaking voice technology products.

Microsoft intends to integrate Nuance’s technology into its healthcare-specific cloud strategy. More than half of physicians and 77% of US hospitals use Nuance’s technology, according to a release. Revenue for Nuance’s Healthcare Cloud grew 37% year-over-year at the end of 2020.

“Nuance provides the AI layer at the healthcare point of delivery and is a pioneer in the real-world application of enterprise AI,” Microsoft CEO Satya Nadella said in a statement. “Together, with our partner ecosystem, we will put advanced AI solutions into the hands of professionals everywhere to drive better decision-making and create more meaningful connections, as we accelerate growth of Microsoft Cloud in Healthcare and Nuance.”

Nadella told CNBC he expects the pandemic to accelerate the “digital transformation” of healthcare, and improving health outcomes will require help from tech companies.

“Not only will we be able to serve all the providers with everything we do in Microsoft 365 dynamics, 365 Azure, but Nuance will be able to help us deliver these AI-first solutions for doctors and radiologists and overall clinical decision support in partnership with the rest of the ecosystem,” Nadella said.

Nuance CEO Mark Benjamin, who will remain at the helm after the deal with Microsoft closes, said the partnership will allow the firm to hyper-scale existing technology on a global scale and provide better access to care.

Benjamin added that he hopes to decrease burnout among physicians by reducing the amount of charting, which tends to add two hours of work per one hour of patient care.

“We believe that our solutions coupled with Microsoft’s platform and capabilities will bring actually the practice of medicine back to that intimate physician, patient interaction, and really reduce that administrative burden,” Benjamin told CNBC.

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Pixel 5a isn’t Canceled

The Pixel 5a is one of the most hotly anticipated phones of the year in the budget phone realm, making the rumor that it was canceled fairly disheartening.

However, in an official statement to Engadget, Google has clarified that the Pixel 5a is still coming. It’s simply not coming quite as soon as earlier rumors had suggested and it will see a much more limited release than previous A-series Pixels.

Rumors had pegged the release date for the Pixel 5a as June 11, this would be closer to the May release of the Pixel 3a and 3a XL and in keeping with the originally planned release date for the Pixel 4a. However, Google’s statement indicates that it will be “announced in line with when last year’s a-series phone was introduced,” which would be August.

This isn’t terribly shocking as from everything that we know about the Pixel 5a so far. It’s incredibly similar to the Pixel 4a 5G, making it an awkward fit to have in the market alongside that phone for long.

The surprising news is that the Pixel 5a will see a much more limited release than previous models with availability only in the U.S. and Japan. The rumors of its cancelation were based on supply chain leaks of component shortages, indicating that this is out of Google’s hands. That certainly seems more likely than a conscious decision to limit its release by Google considering the popularity of the lower-priced Pixels.

So if you’ve been holding out for the Pixel 5a, you’re just going to have to wait a bit longer. You could always consider the Pixel 4a 5G or Pixel 5, they are often discounted now and with that April update performance boost, they are better than ever.

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Nintendo Switch Bluetooth Audio Support Reportedly in Latest Update

Nintendo Switch owners have been craving bluetooth headphone support ever since it launched. But just as we thought we’d finally get wireless audio support, the company takes away our hopes and dreams.

Dataminer OatmealDome spotted Nintendo added Bluetooth audio support in its latest 12.0.0 system update, hinting that wireless headsets would now work with the Switch. The bad news? It doesn’t seem to actually work.

The dataminer points out that while support is clearly there, it has yet to support any Bluetooth devices. In the patch notes for the system update (via Nintendo Life), Nintendo makes no mention of the added support.

The patch was released to fix an issue concerning the console’s save data backup feature, to help prevent the save data backup process from being interrupted. Thanks, Nintendo, but what about that Bluetooth support?

Nintendo could be laying the groundwork to eventually release Bluetooth audio support down the line. Or we could be setting ourselves up for disappointment again, since it wasn’t officially announced.

You never know, this feature could to the highly-anticipated OLED Nintendo Switch, due to arrive later this year.

For now, Switch owners will have to play the waiting game before they can get rid of their wired headphones. Unless they opt to add Bluetooth support themselves.

How to add Nintendo Switch Bluetooth support
If you’re looking to use your AirPods Pro, Sony WH-1000XM4, Bose Earbuds, or any other wireless headphones when gaming, you’ll want to know about the AirFly Pro Switch Edition.

In short, it’s a headphone-based adaptor that streams audio to wireless devices, so it could technically work with any device that has a headphone jack. Although, the Switch Edition has been built for, well, the Switch.

Instead of waiting for Nintendo, you might want to nab these instead so you can put those wireless headphones to good use.

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New Material Allows Lithium-Ion Batteries to Maintain Full Capacity for 5 Years

One of the major limiting factors of rechargeable batteries today is how quickly their capacity can degrade. After just a year of regularly recharging a lithium-ion battery, it can’t get close to its full capacity anymore. However, a new material holds the promise of changing the situation and allowing full capacity charges for five or more years.

As EurekaAlert reports, a team of scientists working at the Japan Advanced Institute of Science and Technology (JAIST) has been looking specifically at the negative terminals inside lithium-ion batteries. They use graphite anodes, but also require a binder material; otherwise the graphite would simply fall apart inside the battery.

Today, poly(vinylidene fluoride) (PVDF) is used as the binder material, but its performance isn’t great. After just 500 charge-discharge cycles, typically only 65% capacity can be achieved in a battery using PVDF. We’ve all experienced this when our smartphone battery no longer lasts a full day like it did when the phone was new, but such experiences could soon be a thing of the past.

The JAIST team discovered a new, and almost unpronounceable new binder material called bis-imino-acenaphthenequinone-paraphenylene (BP) copolymer. The good news is, BP allows a battery to maintain 95% capacity for more than 1,700 charge-discharge cycles. In other words, it allows a lithium-ion battery to be fully recharged daily for almost five years, and possibly even longer. That’s according to Professor Noriyoshi Matsumi, who led the study.

According to Matsumi, “The realization of durable batteries will help in the development of more reliable products for long-term use. This will encourage consumers to purchase more expensive battery-based assets like electric vehicles, which will be used for many years.” It’s certainly great news for our smartphones, tablets, and laptops, but even better news for electric vehicles, where the lifespan of the batteries they rely on is so important, as is the range they offer.

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Apple Figures Out How to Fit Bigger Batteries Inside a MacBook

Apple has come up with a way to increase the battery capacity of its devices without needing to adopt brand new battery technology. Instead, it just needs to encase its existing batteries in a metal housing.

Laptop batteries used to be confined to a solid block found at the back of the device below the display. More recently, the switch was made to lithium-polymer batteries housed in aluminized laminated pouches. They are preferable as they can be manufactured in custom sizes to fit in all available spaces. They present their own problems, though.

As 9To5Mac reports, Apple has applied for a patent entitled “Metal Can Battery” which solves one of the biggest problems with laminated pouch batteries. As the patent application explains:

“The sealed edges of the pouch battery can result in excess pouch material and the pouch can have a positive voltage that requires the exterior surface of the pouch to be isolated from conductive surfaces in the electronic device. To accommodate the excess pouch material and isolate the conductive surface of the pouch battery, the pouch battery needs to be smaller than the area provided in the electronic device, resulting in wasted space.”

So while the pouch design allows Apple to fit a lot more battery capacity inside the confines of a MacBook, there’s still wasted space. The solution, as the patent details, is to replace the soft pouch material with a rigid metal case. That way the internal battery can be larger to fill the space previously used by the excess material. As a bonus, the metal housing can also double as a structural element in the device, giving it more strength.

The one downside of switching to a metal casing which may concern Apple is additional weight. However, if we had to choose between extended battery life or a slightly lighter device, I’m sure most people would choose a bigger battery. Will Apple?

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OnePlus 9 Come: Everything We Know

The OnePlus 9 cameras will include a Hasselblad Pro Mode, with new color calibration and a UI based on Hasselblad’s image-processing software. The companies will work together first on color tuning and sensor calibration, “extending to more dimensions in the future,” OnePlus said. Future OnePlus cameras will have a 140-degree panoramic field of view, and “T-lens technology” for faster focus on the front-facing camera.

The company is investing $150 million in camera development. The underlying story is that while OnePlus phones are known for terrific speed and performance at reasonable prices, their camera image quality has typically fallen behind competitors at Samsung, Apple, and Huawei.

OnePlus is on a roll here in the US right now, with its midrange Nord phones becoming a surprise success at Metro by T-Mobile. Making it at the high end in the US is going to mean going toe-to-toe with Samsung, though, so OnePlus will need every advantage it can get.

What Will the OnePlus 9 Be?
There will be three phones in the series.

Two of them will come out in the US and be sold by T-Mobile. They are the OnePlus 9 and the OnePlus 9 Pro. It’s not clear whether they’ll be compatible with any other carriers.

OnePlus confirmed a third model, the OnePlus 9R, which we have heard will only come out in India.

The OnePlus 9 Pro will come in a “morning mist” color and a “pine green” color while the OnePlus 9 will come in a “winter mist” purple color, as shown in this tweet.

The OnePlus 9 Pro will have a 6.7-inch, 1440p display with a brand new, power-efficient screen technology. We got exclusive test results from DisplayMate Labs showing how it will be unusually readable in sunlight.

A leak on Slashleaks shows a 2,400-by-1,080, 6.55-inch 120Hz screen on the OnePlus 9.

The company confirmed on Twitter that the new phones would have a Snapdragon 888 processor with a “5-layer gaming-grade cooling system.” Slashleaks has what appears to be OnePlus 9 Pro Geekbench scores, which are on par with other Snapdragon 888 phones. The company also said it’s using Qualcomm’s new, slightly lower-end Snapdragon 870, though, which may power the OnePlus 9R. The leak from Evan Blass above shows 8GB/128GB and 12GB/256GB models for both the 9 and 9 Plus.

The OnePlus 9 Pro will certainly have at least 65-watt fast charging, as the OnePlus 8T did. The OnePlus 9 Pro will also have 50-watt wireless charging, which will charge the phone in 43 minutes. That phone will have two batteries and the ability to wireless charge horizontally, according to OnePlus.

The phones will have a new “freeform lens,” which eliminates edge distortion, and will use a custom Sony IMX789 camera sensor with 12-bit RAW color, supporting 4K video at 120fps and 8K video at 30fps.

CEO Lau has been busy tweeting about the camera. He says it will include 12-bit RAW image capture; a 48-megapixel main sensor; a 50-megapixel ultra-wide-angle camera; improved bokeh algorithms; a tilt-shift photography feature; and enhanced HDR. A story on TechRadar goes into more details on each of these features. A video posted to YouTube implies that there will be major improvements to the wide-angle camera, and a OnePlus Tweet showed images from a macro camera as well.

As for the Hasselblad tie-up, color me skeptical for two reasons. The first is that Hasselblad’s previous smartphone collaboration, the Hasselblad True Zoom Camera, was an utter lemon. We rated it much too high, largely because it was the only 10x zoom option in the smartphone world at the time. Heavy, noisy, and glacially slow, it was the opposite of OnePlus’s reputation for speed and a “burdenless” experience. On the other hand, that was five years ago, so maybe it’s learned.

Beyond that, though, I’ve never seen any of these phone/camera brand tie-ups really mean anything. Nokia with Zeiss, Huawei with Leica, Sony with, um, Sony; the names appear on phones, but the phones never seem to have any real relationship to the companies’ professional camera products. This OnePlus-Hasselblad tie-up already appears to be more involved than most, but once again, I have too many memories of the True Zoom Camera.

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How smartwatches are helping encourage social distancing in the workplace

Healthcare data is collected from a lot of sources such as lab data, clinical data, actuarial data, physiological data, nurses’ notes and consumer data. Add wearable technologies and portable medical devices to the picture and the amount of information a clinician receives becomes overwhelming.

All these data could collectively help the industry address problems related to variability in healthcare quality and escalating healthcare spend. However, the healthcare industry is not utilising rich data to the fullest. And the data is not currently used for good reasons- clinical professionals cannot review all of these data because there are too much of them. The overwhelming nature of data collection rapidly outpaces the human minds capacity to process, associate and find patterns and knowledge, especially now in the digital age.

With so much data in healthcare, it makes sense to adopt machine learning to understand the data and how the data correlates. Machine learning is when a computer has been taught to recognise patterns by providing it with data and an algorithm to help understand that data. Because machine learning techniques learn from the data, the more data a machine learning model is fed, the more accurate the clinical prediction. Essentially, the data is fed into machine learning through and algorithm, with every action and non-action feeds. The task then gets automated without constantly requiring human or manual interference.

Wearable technology made the intersection of technology and healthcare popular. Increasing streams of wearable data create a continuous automated health monitor, that not only helps track patient’s activities but also offers guidance that identifies disease as it occurs and predicts it before it impacts the patient. With most type of wearable technology continuously receiving data, clinicians will be able to view and validate general wellbeing, and pinpoint illnesses and other irregularities, even before the patients under their care become aware of them. 60% of related factors to individual health and quality of life are correlated to lifestyle choices, including taking prescription, getting exercise, and reducing stress. Aided by wearable technology, machine learning and AI-driven models, the healthcare industry is now able to provide patients with interventions and reminders throughout the day-to-day process based on changes to the patient’s vital signs.

Utilising the rich healthcare data in machine learning has enormous potential. Integrating data from wearables with other sources of data mentioned above, along with machine learning, can be used to predict diseases or a medical condition before the emergence of symptoms, optimise treatment and potentially find new cures for rare diseases. It can predict epidemics, improve quality of life and avoid preventable deaths. It can also be used to inform consumers of lifestyle choices that promote well-being and encourage active engagement of consumers in their own care.

Wearable technologies will add new continuous patient data streams to the trillions of data points already being captured. The data then flows directly into machine learning systems that consumes this raw data, with the goal of developing correlations and ultimately causations of disease linked to a patient’s interaction with the surroundings.

Integrating wearable technology data, as well as other sources of data into machine learning is a lofty goal. It will require human directed machine learning in the early stages, which is essential to triage erroneous correlations quickly from the system. And key to an efficient process will be the presentation of the data that allows the human brain to visualise these new relationships.

But one thing for sure is, the human brain and clinical professionals will never be able to review all of this data on their own. Hence, generating actionable intelligence will be essential if we are to turn the healthcare tide to better, widely accessible and more cost-effective care.

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Integrate Wearable Data in Machine Learning

Healthcare data is collected from a lot of sources such as lab data, clinical data, actuarial data, physiological data, nurses’ notes and consumer data. Add wearable technologies and portable medical devices to the picture and the amount of information a clinician receives becomes overwhelming.

All these data could collectively help the industry address problems related to variability in healthcare quality and escalating healthcare spend. However, the healthcare industry is not utilising rich data to the fullest. And the data is not currently used for good reasons- clinical professionals cannot review all of these data because there are too much of them. The overwhelming nature of data collection rapidly outpaces the human minds capacity to process, associate and find patterns and knowledge, especially now in the digital age.

With so much data in healthcare, it makes sense to adopt machine learning to understand the data and how the data correlates. Machine learning is when a computer has been taught to recognise patterns by providing it with data and an algorithm to help understand that data. Because machine learning techniques learn from the data, the more data a machine learning model is fed, the more accurate the clinical prediction. Essentially, the data is fed into machine learning through and algorithm, with every action and non-action feeds. The task then gets automated without constantly requiring human or manual interference.

Wearable technology made the intersection of technology and healthcare popular. Increasing streams of wearable data create a continuous automated health monitor, that not only helps track patient’s activities but also offers guidance that identifies disease as it occurs and predicts it before it impacts the patient. With most type of wearable technology continuously receiving data, clinicians will be able to view and validate general wellbeing, and pinpoint illnesses and other irregularities, even before the patients under their care become aware of them. 60% of related factors to individual health and quality of life are correlated to lifestyle choices, including taking prescription, getting exercise, and reducing stress. Aided by wearable technology, machine learning and AI-driven models, the healthcare industry is now able to provide patients with interventions and reminders throughout the day-to-day process based on changes to the patient’s vital signs.

Utilising the rich healthcare data in machine learning has enormous potential. Integrating data from wearables with other sources of data mentioned above, along with machine learning, can be used to predict diseases or a medical condition before the emergence of symptoms, optimise treatment and potentially find new cures for rare diseases. It can predict epidemics, improve quality of life and avoid preventable deaths. It can also be used to inform consumers of lifestyle choices that promote well-being and encourage active engagement of consumers in their own care.

Wearable technologies will add new continuous patient data streams to the trillions of data points already being captured. The data then flows directly into machine learning systems that consumes this raw data, with the goal of developing correlations and ultimately causations of disease linked to a patient’s interaction with the surroundings.

Integrating wearable technology data, as well as other sources of data into machine learning is a lofty goal. It will require human directed machine learning in the early stages, which is essential to triage erroneous correlations quickly from the system. And key to an efficient process will be the presentation of the data that allows the human brain to visualise these new relationships.

But one thing for sure is, the human brain and clinical professionals will never be able to review all of this data on their own. Hence, generating actionable intelligence will be essential if we are to turn the healthcare tide to better, widely accessible and more cost-effective care.

>>>>>>>>>>>>>>>>>>>>Smart Watch Battery

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What is CBRS, and how is it transforming enterprise networks?

Enterprise network deployments in the Citizens Broadband Radio Service (CBRS) band have the potential to address two of businesses’ most critical communications needs: fast, reliable and secure connectivity, and connectivity that’s available in limited, hard-to-reach areas.

With shared spectrum technology like CBRS, organizations can make use of their own private networks, particularly on campuses — where they can guarantee coverage and trust their networks’ data security.

What is CBRS?
CBRS occupies 150MHz of shared spectrum in Band 48 (otherwise known as the 3.5GHz C-Band). Following a decision by the Federal Communications Commission (FCC) in 2015, CBRS was designated as a band of spectrum that could be shared among three tiers of users.

The first tier included incumbent users, such as the U.S. Navy and satellite ground stations, which need to use the CBRS band for many different mission-critical situations. The second tier encompasses priority access license (PAL) holders, including internet service providers (ISPs), carriers and large enterprises who received licenses as part of an auction process completed in 2019. The CBRS band’s third tier, general authorized access (GAA), provides free access to the spectrum in areas where user traffic doesn’t interfere with traffic on the higher tiers.

What are the benefits of CBRS vs. Wi-Fi?
As mobile usage across the enterprise becomes more widespread, some organizations are struggling with Wi-Fi’s shortcomings — including installation and maintenance costs, insufficient coverage and network congestion, which can hinder app performance and disrupt workflows.

By contrast, OnGo deployments on the CBRS band can support twice the capacity of Wi-Fi, protects against network interference and offers four times the range suitable for large-scale deployments.

Wi-Fi networks’ open spectrum makes them a common target for hackers. On the other hand, CBRS band access is secured by a SIM card and login requirement.

Finally, OnGo makes it easy for end users to switch between access points without experiencing the issues associated with Wi-Fi, like disconnections and dropped calls.

Wi-Fi continues to offer many advantages in terms of convenience, simplicity and total cost of ownership (TCO), so organizations with smaller staff or less intense security needs will still use it. However, OnGo-certified solutions on the CBRS band offer a better alternative for many enterprise use cases.

What are the benefits of CBRS vs. public LTE?
Traditionally, public LTE networks have relied on mobile operators using spectrum publicly auctioned by regulatory bodies for the services they provide. Public LTE deployments have also tended to involve technologies such as two-way land mobile radios (LMR) and distributed antenna systems (DAS).

While those options may work initially, they lack the flexibility and efficiency of CBRS, particularly as enterprises seek to advance their network capabilities and take advantage of 5G connectivity. OnGo deployments on the CBRS band allow enterprises to enhance their capabilities, even if they continue to work with carriers, and also act as a catalyst for new companies to emerge with the broadband connectivity they need.

What does CBRS bring to enterprise LTE?
By contrast, with enterprise LTE, your organization doesn’t have to rely on carrier networks, but instead deploys its own LTE network infrastructure to support connectivity at a certain facility. This gives you complete control over your networks and your data — and allows you to dynamically customize your connectivity based on your specific applications. With these network benefits, your business can deliver fixed wireless services, point-to-multipoint offerings and last-mile fiber access. You can also supplement or replace your Wi-Fi installations with additional spectrum, whether shared or dedicated.

Beyond that, running enterprise LTE on the CBRS band confines all of your business data to the corporate network, guaranteeing the level of privacy required in sectors like financial services and healthcare.

This approach to enterprise LTE can also bring cost savings. You need fewer small cells than you need for Wi-Fi, and expenses like power, cable running and maintenance tend to be lower too.

Perhaps most importantly, with OnGo on the CBRS band, organizations can set a fixed length for data transfers — improving latency — and control how their data traffic is prioritized, boosting quality of service.

What are the use cases for CBRS?
The OnGo Alliance describes wireless spectrum as the “fourth utility,” almost as necessary as heat, water and power. OnGo certification was designed to enable deployments in diverse areas.

For many organizations, improved in-building connectivity enhances employee and customer experiences alike. Early adopters of CBRS include the hospitality sector and multifamily residential spaces. The same connectivity will be vital in large public spaces like stadiums and shopping malls as consumers gradually come back. Behind the scenes in larger organizations, CBRS may unleash even greater innovation — with internet of things (IoT) devices automating industrial processes on factory floors and in warehouses.

When the pandemic first started, millions of students were abruptly sent home from school, and educators immediately faced the challenge of enabling at-home learning. Many institutions have continued to offer a combination of in-person and virtual lessons, but such a model is difficult to maintain for students in rural or remote areas. OnGo-certified solutions on the CBRS band offer a natural solution: fast connectivity, with the reliability that sophisticated educational applications demand.

In the utility sector, companies are adopting enterprise LTE to connect smart meters in residential neighborhoods. The added connectivity allows them to alert customers when an outage occurs, and to inform them of how much money they could save by altering their energy usage.

Markets like agriculture see similar use cases. Today, farmers are beginning to use sensors on tractors, detecting upcoming repair needs before they’re emergencies. Some farmers are adding sensors to their heaters and fans to detect moisture changes, ultimately increasing their yields and cutting costs.

OnGo solutions on the CBRS band are also paving the way for the future of transportation. Autonomous vehicles, for example, are still under development, so they need to be tested in safe areas. The companies that work on them need connectivity that can extend to more remote areas and allow quick upload and download speeds.

But these scenarios are just the tip of the iceberg. CBRS has equally compelling use cases in areas including — but not limited to — mining, manufacturing and the development of smart cities.

How will CBRS adoption evolve?
Given how recently the spectrum became available for commercial use, we’re only in the early days with shared spectrum and the way organizations could use it as part of enterprise network developments.

For example, OnGo can easily be software-upgraded to 5G, putting organizations in an even better position to take advantage of 5G’s network slicing, low latency and increased bandwidth capabilities. Connectivity and bandwidth in rural areas will also likely improve following the conclusion of the 3.7-4.2GHz auction, or C-band auction, that’s expected to resume this year.

This along with the OnGo Alliance’s ongoing work to coordinate industry efforts around CBRS band specifications demonstrates the ongoing shift toward cellular-style capabilities in the enterprise.

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At what price does a console become better than a gaming PC?

To pinpoint it further than that, you’ll need to compare the performance of equivalently priced consoles and gaming PCs, then factor in the genres you play and your general computing needs. So for example, let’s say you only ever play single-player AAA titles, and you like to play them as soon as they come out. You also already have a device that you use for everyday tasks like web browsing and video calling, like an older laptop or PC. So long as you don’t need universal mouse and keyboard support in games, an Xbox Series S, Series X, or PlayStation 5 would be better for gaming. In that price range, the consoles clobber the PC. Moreover, they’ll play everything that comes out during their lifespan, including all big blockbuster games. The last two console generations lasted between seven and eight years—a graphics card you buy today won’t be able to play 2028’s AAA titles at the same graphical fidelity as it does now, but a console will.

However, perhaps you’re instead extremely into multiplayer games, and you need access to online play. Then you’ll need to factor another $60 per year for an online membership that enables that functionality—Xbox Live Gold for Microsoft consoles, and PlayStation Plus for Sony consoles. (You can pay less if you catch the memberships on sale, but we’ll work with list prices across the board.) Depending on how long you usually wait before upgrading a GPU in a gaming PC, that could notably increase the budget of an equivalent computer, as online multiplayer access is free on PC. For example, someone with a upgrade cycle of four years could add that $240 to a PC budget when making a comparison against a gaming console. That amount of cash would buy a much nicer GPU.

The value of a console versus a PC changes in every scenario—to throw in a couple more examples, someone who only ever plays lightweight indie games might actually be better off with a low-cost gaming PC. Or maybe you don’t already have another PC or laptop and would benefit from a new, modern desktop PC to work from.

Making this calculation gets even hairier when computer parts have insane markups and/or very limited availability as they do now. You have to weigh your willingness to wait for prices and availability to improve against your budget in the short- and medium-term, as well as your willingness to fight for a console. The new Xboxes and the PlayStation 5 are only moderately easier to obtain than graphics cards right now.

You also have to take into account what you already have on hand—maybe your existing gaming PC can keep on trucking with the aid of GeForce Now. Or perhaps you can make do with older gaming hardware in a pre-built PC, because that’s all you can easily get at a decent price. You might also be someone who has $1,500 to throw at an RTX 3090, but you’re so irritated by the scalpers that buying an Xbox Series X to tide you over until prices drop below MSRP is the cheaper, more satisfying move.

Hopefully, we won’t have to wait too much longer for this question to once again be a fun theoretical bomb to lob at people for debate, instead of having to consider it as a real option when your budget would normally allow you to buy a graphics card that runs laps around consoles.

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