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Your old phone is a better security camera than CCTV, says Manything CEO

What did you do with your old phone? If you’re anything like us, it’s currently sat in a drawer, thrilled that someone is remembering that it exists. Yeah, you tried to sell it, but the guy in the store said you needed the box, and the cable. And you wanted to keep that cable. Plus, it was worth 0.5% of what you paid for it, so you took it home with the intention of trying somewhere else and never did.

The good news is, it could have a second life – as a security camera. And we don’t just mean pointing your phone’s camera at something terrible happening like an extra in a Marvel movie. 

If you download and use Manything, your old trusty handset could works as a real Wi-Fi security camera, like the Nest Cam IQ[1], but iPhone 5[2] shaped.

Like this

We sat down with the CEO of Manything James West to talk about where the idea came from, and some of the unexpected things he’s seen since setting up Manything.

“In 2012 there was something extraordinary happening in smartphones which was that the smartphone was already higher resolution, packed with more sensors than your standard video monitoring camera,” says West.

“If you were wanting to do video monitoring of your house, or a shop, or an airport, that security camera is lower resolution than your smartphone. 

“It was pretty clear to us – even back then, by the end of 2013 – there were going to be a billion spare old generation smartphones in the market that were all of the higher specification than any CCTV cameras out there.”

From thought experiment to home security

It’s all well and good realizing that a device is higher spec, but how do you go from that to having a security business?

“It was really just a sort of mad thought-experiment at the beginning which is ‘what if we could write some code to turn them into home security cameras?’. And what if that would cater to a market that previously didn’t exist which is people who need a video monitoring camera now. Not tomorrow, not having read all the reviews, that want it now.”

Many people that have a security camera use it half as a method of observation, half as a deterrent. But if you need a camera now, there’s a good chance you either know something bad’s about to happen, or something bad is already happening. 

“We have a very high rate of people needing us and bad things happening. Many of our users have a benign need which is ‘puppy and parcel cam’ but we’ve also got a whole bunch of users who have an immediate threat to their safety, so it might be domestic violence, it might be bad neighbors. It’s the only security camera that they can have now.’

Not all doom and gloom

But luckily it’s not just the worst side of live that Manything captures, and one of the cool features of Manything is that users can share clips of the interesting or funny things that they have caught with their cameras. 

The clips fall into a range of different categories, and West was telling us about some of the more unique uses of the Manything system that he’s seen: 

“When something’s happened you wanna send us, you can you can choose a category of whatever it is and these kind of reflect our user breakdown. We actually have an alien’s category because we’ve got enough people that think they see aliens. 

“We had a very cool one which was that Arizona meteor that lit up the whole driveway. We’ve got one guy who’s a Potter who watches his furnace with it. We’ve got someone who’s got a wind turbine who wants to see if it trips.”

If you want to see some of the clips Manything users have shared, check out the video below:

[embedded content]

Manything is free to download and use, with subscriptions starting from $ 3.99 (£2.99) that allow you to add more cameras and watch more video recorded to the Manything cloud. 

If you’re interested in setting yourself up a camera (as old as an iPhone[3] 3GS, or Android device running 4.2), check out our guide: How to turn an old smartphone into a security camera[4].

References

  1. ^ Nest Cam IQ (www.techradar.com)
  2. ^ iPhone 5 (www.techradar.com)
  3. ^ iPhone (www.techradar.com)
  4. ^ How to turn an old smartphone into a security camera (www.techradar.com)
  5. ^ Best security camera: keep an eye on your home from your smartphone (www.techradar.com)

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The birth of fertility tracking tech

From thermometers to charts to apps to complicated maths, for women, tracking their cycle to work out when best to conceive, and when to avoid conceiving, is nothing new. 

And now, thanks to the rise in tech designed to make fertility tracking at home easier and more accurate than ever, more and more women are entrusting the planning and prevention of pregnancy to an app and a thermometer.

In many ways this is a hugely positive development, providing women all over the globe with more knowledge and insights into how their bodies work. Not only is this empowering, it gives them a better chance of making good decisions without the need to sit in a doctor’s waiting room, wait ages for tests, or pay for advice. 

Rebecca Simmons, Assistant Professor and Sexual & Reproductive Health Researcher, explains: “Personalized medicine – this idea that we can tailor broader health information to ourselves for better outcomes – is really driving people to have a better understanding of their own bodies with respect to everything, from fitness to nutrition to chronic disease.” 

“I think that fertility technology and fertility-awareness-based methods really align with this larger trend.”

But, as you may expect, this new wave of fertility tracking tech doesn’t come without its issues, from lack of regulation and steep prices through to dubious claims and even unwanted pregnancies.

For example, popular fertility tracking app Natural Cycles[1], which is claimed to be able to plan and prevent pregnancy, has come under fire[2] for allegedly leading to a number of unplanned pregnancies.

So do the benefits outweigh the risks? Or are people jumping on board this particular quantified self[3] bandwagon far too early? 

The Natural Cycles app highlights red fertile days or green infertile days

(Image: © Natural Cycles)

The current state of fertility tracking 

Fertility tracking tech is a fast-growing space, and there are a number of options readily available, from in-ear wearables through to simple apps. 

Most of the devices collect data about Basal Body Temperature (BBT), which is your body’s temperature when at rest and has long been used as an indicator of fertility because it fluctuates throughout a woman’s cycle. 

The approach to taking your BBT is varied. For example, Ava[4] is a wrist-bound wearable aimed at those looking to plan pregnancy, which tracks temperature as well as a range of other physiological markers, from stress to sleep.

Similarly, TempDrop[5] is a wearable that can be worn with an armband or directly on the skin of your arm throughout the night and, like Ava, it collects a range of readings. In comparison, Yono[6] is an in-ear basal thermometer that’s worn all night to continually track BBT.

(Image: © Ava)

Then there are oral thermometer methods, with many (but not all) claiming they can be used to plan as well as prevent pregnancy. For example, Daysy[7] is a thermometer that teams up with the Daysy app to tell you when you’re likely to be fertile and infertile. The Wink[8] is an oral thermometer that pairs with the Kindara app and sends information to it via Bluetooth, and is claimed to be a good indicator for those wishing to plan and prevent pregnancy.

Then there’s Natural Cycles[9], which is a popular app and thermometer combo that’s used to both plan and prevent pregnancy. Importantly, Natural Cycles is the only product mentioned here that’s certified as a valid method of contraception in Europe (outside of Europe it’s only intended to be used as a form of fertility monitoring).

Then there’s Dot[10], which also claims to be able to plan and prevent pregnancy just by tracking the dates of a woman’s period and not by taking their temperature.

(Image: © Dot)

Finally, there are also a few really popular apps, like Clue[11] and Glow[12], that don’t require the woman to take her temperature and don’t promise to be solid options for planning or preventing pregnancy, but they do allow users to track their cycle and prompt them to learn more about how their body behaves throughout the month, from moods to reaction to medications.

But that’s just the beginning. More apps are hitting the market all the time, more startups are producing wearables, and more BBT-based solutions are trying to drum up mainstream appeal. It’s a fascinating, fast-growing space. But with such a huge range of products racing to market, can we really trust them?

Can an app really replace the pill?

While some of these apps and wearables claim to be able to keep track of infertile days, only a few state that they can confidently be used to prevent pregnancy. Even then the small print ensures that most can’t be held accountable for any unplanned pregnancies, and should only be used as a guide. 

And although this space is still largely unregulated, the experts we spoke to expect it to continue to grow. Simmons explains that “demand for app-based methods is occurring because existing methods aren’t meeting the needs of all women”. 

“The vast majority of development around contraception has been mostly tinkering with the hormonal dosages/delivery mechanisms of existing contraceptive methods, which is fine, but doesn’t address the needs of the subset of women for whom hormonal methods either aren’t possible or desired,” Simmons adds. 

“As more research emerges on some of the potential negative side effects of hormonal contraception (for example depression, decreased sexual libido), women and their partners are looking for other ways to prevent pregnancy. These apps are, for better or worse, filling some of that existing demand.”

Natural Cycles faced criticism after being blamed for a number of unplanned pregnancies in Sweden[13]. But the team behind the app have explained that as user numbers rise, so will unplanned pregnancies. 

That’s because it’s 99% effective with ‘perfect use’ and 93% effective with ‘typical use’ according to the Pearl Index, which is a commonly used indicator that estimates the number of unwanted pregnancies with a contraceptive method if 100 women use it over a year. So with typical use you’d expect seven women using Natural Cycles to become pregnant over 12 months. 

And while 93% may not sound particularly comforting, according to a recent study of contraceptive methods[14], the Pearl Index for the male condom ranges from 98% effectiveness with perfect use to 82% with typical use over time, and the combined pill ranges from more than 99% effectiveness with perfect use to 91% with typical use.

A detailed look at the Natural Cycles app and the data it provides

(Image: © Natural Cycles)

Although this points to Natural Cycles being more effective than the male condom (although bear in mind this is based on limited studies, as the space is still so new), tech-based contraception does need to be approached with caution, largely because we’re just not used to using it yet. 

For example, the ‘perfect use’ of Natural Cycles requires a woman to take her temperature each morning at a similar time before they get up, and works best for those with regular cycles; and if you’re ill or hungover that may affect your results. This means that while in theory ‘perfect use’ sounds easy, in practice it may not be. 

That doesn’t mean to say Natural Cycles isn’t a valid option for those who’ve tried other methods and are committed to sticking to the instructions, but it’s not perfect and, crucially, won’t protect against STDs. 

We asked Rebecca Simmons what she thinks of using an app instead of the pill. “There’s very little research right now on the efficacy of existing fertility apps and other technologies. For better or worse, science is slow and technology is fast,” she explained.

“There needs to be a better balance between the two fields, to prevent women from being harmed and to improve consumer confidence in this field. For now, women who are choosing to use fertility technology as a way to prevent pregnancy should be extremely careful in choosing which apps to trust with that type of responsibility.”

Weighing up the opportunities and the challenges

Although we can’t ignore the fact that this tech is by no means perfect or designed for everyone, that shouldn’t detract from its huge potential. 

While large-scale numbers being hard to come by at this point, user stories from many of the fertility tech companies we spoke to point to huge success rates in using these apps and devices to plan for pregnancy. We spoke to Lea Von Bidder, the CEO and Co-founder of Ava, who explained that because the Ava wearable tracks nine different physiological parameters it’s become a highly effective way to pinpoint fertile days. 

“The Ava bracelet was proven in a recently concluded clinical study at the University Hospital of Zurich to detect an average of 5.3 fertile days per cycle with 89 percent accuracy,” Bidder told us. “Furthermore, since Ava measures multiple parameters besides temperature, it is able to detect the fertile window in real time, which is critical in order to improve the chances of conceiving.”

It’s not just early research and anecdotal evidence that points to a bright future for fertility tracking tech, but what it means for healthcare, women’s bodies and user confidence. 

“Fertility technology is reducing stigma,” Simmons told us. “Typically, aspects of women’s bodies – things like cervical mucus and menstrual bleeding – have been sources of confusion and shame for women all over the world. The broad reach of these technologies is empowering because women can see that not only are these things absolutely normal, they are valuable health vital signs.”

And not only is the technology reducing stigma, it’s empowering because it takes a largely unknowable aspect of women’s biology and makes it as knowable as ordering an Uber or checking Facebook. 

“The underlying message behind this new technology is that women’s bodies are ‘knowable’ – that you can understand a lot about your fertility, and overall health broadly, by looking for certain signs that your own body gives you each month,” Simmons says.

“Fertility technology is allowing women to do this more easily, in real time, with aspects of behavioral theory, such as feedback, community, and reminder systems. This is immensely empowering for women and can really impact their health.” 

It’s not only personally empowering, but the data can also be used to inform health care professionals, providing them with cycle data that can be exported and downloaded. If there’s a joined up approach between healthcare providers and tech companies in future, this could prove to be incredibly useful in diagnosing, tracking and treating health problems. 

At this stage, a lot of the tech we’ve talked about here is aimed at women who want more control over their bodies and fertility and are likely early adopters. But the bigger picture is that easily accessible tech for fertility could have a big impact on those in developing countries without easy access to healthcare.

“One particularly important opportunity with this tech is expanding access to infertility diagnosis and treatment – something that’s generally been mostly available to rich, white people with insurance coverage,” Simmons told us. 

The Dot app displays a simple graph of your cycle

(Image: © Dot app)

Leslie Heyer, CEO of Cycle Technologies[15] and creator of the Dot app has been ensuring its tech reaches far and wide. “We made a commitment to FP2020, a global consortium of governments, organizations and the private sector, to make our contraceptive technologies available for free to 10 million women around the world, with a particular focus on places with high unmet family planning need,” Heyer told us. 

Although it’s easy to get excited about the possibilities more accessible fertility tech will open up, there are plenty of challenges, and reasons to be concerned, too. 

As is the case with the larger health tech space, privacy and accuracy are the main concerns, especially as more companies rush to bring products to market. The answer here is investing in development of platforms to ensure more privacy, and investing in research. But that’s not always easy.

“I’ve seen many fertility tech companies who employ scientific advisors and doctors as part of their development process,” Simmons told us. “This is excellent, but that costs money, and if you’re a startup or just a little company trying to push out an app, that might not be in your purview.”

“it is important that innovators, investors, and users do their research,” Heyer explained. “I do have concerns that there are a number of fertility technologies that are making misleading and/or bold claims without having significant evidence to support these claims. This has the potential to undermine the whole industry, and does a real disservice to end users.”

(Image: © Natural Cycles)

The future of fertility tracking

Women have long needed different options for both fertility tracking and contraception that don’t rely heavily on hormones, access to expensive healthcare or methods that give them little to no visibility of their own bodies. 

But the future success of the industry relies on a number of factors. For starters, companies should be required to take on a responsibility to educate users so they can make informed decisions. And at the same time, everyone considering these methods needs to be wary about bold claims, do their research, and consider whether relying on tech that requires their input and attention is for them.

Most of the experts and brands we spoke to also pointed to the need for a more joined up approach between companies, users and academics. “Reproductive health needs champions; from startups like ours, to doctors and researchers, and of course app users themselves,” Ida Tin, CEO and Co-founder of Clue told us.

“When we look at past studies on women’s health, the sample size has been very limited. Now that we have massive amounts of data, we can look at trends on a much larger scale and really move the field forward.”

We may not have perfect solutions yet for preventing or planning pregnancy, but tech that empowers women and gives them more insights into their bodies is promising. It’s also wise to look at the bigger picture. If this tech can help women all over the globe feel more confident about their bodies and how they work, it could have a hugely positive impact on fertility and healthcare worldwide. 

References

  1. ^ Natural Cycles (www.naturalcycles.com)
  2. ^ has come under fire (www.telegraph.co.uk)
  3. ^ quantified self (en.wikipedia.org)
  4. ^ Ava (www.avawomen.com)
  5. ^ TempDrop (tempdrop.xyz)
  6. ^ Yono (www.yonolabs.com)
  7. ^ Daysy (uk.daysy.me)
  8. ^ Wink (www.kindara.com)
  9. ^ Natural Cycles (www.naturalcycles.com)
  10. ^ Dot (itunes.apple.com)
  11. ^ Clue (www.helloclue.com)
  12. ^ Glow (glowing.com)
  13. ^ blamed for a number of unplanned pregnancies in Sweden (www.telegraph.co.uk)
  14. ^ a recent study of contraceptive methods (www.gp-update.co.uk)
  15. ^ Cycle Technologies (www.cycletechnologies.com)

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Lenovo Miix 520 review

There are a number of Surface Pro (£679.99 at Amazon.com) clones on the market such as the Acer Switch 5, Samsung Galaxy Book and HP Spectre x2, but Lenovo’s Miix series continues to impress us the most with its design, features and included accessories. The midrange Miix 520 sticks to that script and also doesn’t change much from 2016’s excellent Miix 510 (£778.62 at Amazon.com). At a glance, it’s still a dead ringer for Microsoft’s tablet PC and also looks just like its predecessor.

Centered around a 12.2-inch, 1,920 by 1,200-pixel responsive touchscreen, the detachable two-in-one is updated on the inside with an eighth-generation GBP1,000 in the UK.

The cost roughly converts to AU£1,260.

It’s a good price for what you’re getting and, as long as you don’t need all-day battery life, the Miix would make a fine pick for a student, home office or other undemanding work use.

Windows 10 S is becoming Windows 10 S Mode

Changes are coming to the stripped-down, lightweight operating system Microsoft produces and which has up until now been known as Windows 10 S[1]: it’s getting a new name for a start, and will become Windows 10 S Mode in the not-too-distant future.

That’s according to the Microsoft watchers at Thurrott[2] and Neowin[3], who say the company wants to rebrand the software so it fits better into its portfolio of products. The new S Mode OS will soon be available on most versions of Windows, limiting users to apps downloaded through the Windows Store, with an unlock option available for the full version of the software.

Apparently if you’re running Windows 10 Home in S Mode you’ll be able to upgrade to the full desktop experience for free, while those with Windows 10 Pro in S Mode are going to have to stump up $ 49 for the privilege of unlocking, though all this is yet to be confirmed by Microsoft itself.

To switch or not to switch

We don’t have a timetable for when this rejigged Windows approach is going to arrive, but it seems that Microsoft is planning to refresh its prices sometime in April, so it makes sense for the company to make an announcement on this switch at the same time.

Thurrott is also reporting[4] that 60 percent of users who buy a computer with Windows 10 S on it don’t upgrade to the full-fat version of the operating system. Of those who do upgrade, 60 percent do so in the first 24 hours, while those who don’t unlock Windows 10 in the first seven days are 83 percent likely to stick with Windows 10 S.

We also have a hint[5] that the next big update for Windows, Windows 10 Redstone 4, is going to be labelled the Spring Creators Update. It wouldn’t be the most original of names, but we’re expecting more details about the next iteration of the software in the coming weeks.

Via The Verge[7]

References

  1. ^ Windows 10 S (www.techradar.com)
  2. ^ Thurrott (www.thurrott.com)
  3. ^ Neowin (www.neowin.net)
  4. ^ is also reporting (www.thurrott.com)
  5. ^ have a hint (twitter.com)
  6. ^ Microsoft tells us about its high hopes for Windows 10 S (www.techradar.com)
  7. ^ The Verge (www.theverge.com)

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A.I. perfectly predicted last year’s Super Bowl score. What happens to betting?

Competitive sports are ultimately numbers games. Whether it’s a gymnast racking up points on a balance beam, a tennis player acing her opponent, or a football team scoring on a last second Hail Mary, all matches are won and lost by numbers. There are upsets, comebacks, and situations when the losing team still seems to outperform the other — but, even then, victory distills into digits.

As such, it’s obvious that many sports lend themselves nicely to the type of mathematical analyses that let keen-eyed statisticians predict outcomes — maybe even exact scores — just by crunching a bunch of numbers. After all, that’s the basis of sports betting, and it’s helped baseball managers craft winning teams on a tight budget just by considering little more than batting average, runs batted in, and stolen bases. But what happens when artificial intelligence algorithms are used to do what they do best — pick out patterns in data that human eyes typically can’t catch?

Could these algorithms undermine the “house” and turn sports betting on its head? The prediction predicament Athletic events are chock full of juicy data that A.I. developers would probably love to feed to their algorithms.

A power forward’s field goal percentage, a running back’s rushing yards, and a midfielder’s assists are obvious example of this kind of data.

But there are other, less apparent data that can give a more nuanced and complete overview, for example, a player’s “sweet spot” (where he most often makes his shots) or the paths and distance a given player travels during a game. But not all sports are created equal when it comes to quantity and quality of data. Some, like baseball, readily release their players’ stats.

Tennis organizations, on the other hand, collect high-resolution datasets that include things as specific as ball trajectory throughout a match, making the sport rife for predictive analysis. If these organization didn’t keep their hi-res data under lock and key, tennis would be prime for predictive analytics. But for algorithms to identify patterns and provide actionable outputs, they need access to abundant data.

“A lot of the early sports betting in the US using computer algorithms and predictive models was focused on stuff like college football and basketball,” Adam Kucharski, a researcher and author of The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling, tells Digital Trends. “They’d have so many matches and each match had so many scoring events, which gave you a really big data set so you could get a good understanding of what was driving a team performance. And then you’d have enough games throughout the rest of the season to put that insight into practice.” Access to data isn’t the only constraint keeping A.I. from fully infiltrating betting.

The circumstances surrounding this data also needs to be relatively consistent. And since players and team rosters often change from season to season, finding patterns can become difficult, if not futile. Early sports betting [used] computer algorithms and predictive models focused on stuff like college football and basketball.

Furthermore, sports aren’t just about the stats. There are plenty of unseen influencers that can bring a team to victory. Player dynamics, for example, can cause certain squads to “click” and play well together, despite the data suggesting otherwise.

And you can’t trust stats to elucidate a defensive player’s overall skill. “In some team sports, very good players don’t do much that’s measurable,” Kucharski says. “A very good player might just get into a good position. Tackle rates won’t show that.

It’s their positioning and intuitive behavior that is having an influence.” That’s why Kucharski found that most betting institutions combine data-driven predictions with human behavior and intuition. The most accurate prediction might lie somewhere between raw data and input from the crowd.

“You can only shove things into an algorithm if they’re measurable,” he adds. “It might be that there are subtleties or other combinations of factors that humans can spot and process patterns in which is much harder to explicitly put into computing algorithms.” The business of betting There are a handful of companies looking to capitalize on A.I. in betting, such as Stratagem: a London-based startup that’s pairing deep neural networks with dozens of human analysts to predict the outcome of soccer matches, hoping to make money with wagers along the way.

Interestingly, one of the best examples of how A.I. can influence betting doesn’t rely exclusively on machine intelligence.

Instead, it uses the technology as a guide to help humans leverage their collective brainpower more effectively and use it to make more accurate predictions. That’s the approach at Unanimous A.I., a startup that leverages A.I. and “swarm intelligence” to make astoundingly accurate predictions. The startup made headlines last February when users on its platform, UNU, successfully predicted the Super Bowl results down to the exact score.

Then they predicted eleven out of fifteen Oscar winners, besting the New York Times’ film buffs by eighteen percent. Before that, UNU performed an even more unlikely prediction by placing the winners of the Kentucky Derby in their exact order, a feat known as a superfecta, which last year came with 540 to 1 odds. For comparison, none of the experts at Churchill Downs predicted a superfecta.

Meanwhile, Unanimous A.I. founder Louis Rosenberg turned his £20 bet into £11,000. But Rosenberg isn’t in it for the money or the sport of it. In fact, he admits he wasn’t even much of a sports fan before his company started making these predictions.

Adam Glanzman/Getty Images Bill Greene/Getty Images

Ethan Miller/Getty Images Nick Wosika/Getty Images)

Getty Images

“For us it’s always fun to do these sports predictions,” Rosenberg tells Digital Trends. “But we get involved with sports predictions because it’s a great test bed to quantify intelligence.” Rosenberg is a proponent of the hive mind, or human swarm intelligence: the idea that a group of people working together has more intellect than an individual working alone. This isn’t just crowdsourced knowledge, Rosenberg says, but systems that are interconnected with feedback loops to manifest emergent intelligences.

In UNU, Rosenberg has created a platform that enables users to collaborate on predictions in real-time by moving a magnet to pull a “puck” towards their desired answer. By running these swarm trials and comparing their predictions to the real world, Rosenberg and his team hope to get enough statistically significant data to refine their platform and help make predictions even more accurate. “For us it’s always fun to do these sports predictions.”

“We’ve shown we can take average [sports] fans, create them as a swarm intelligence, and amplify their intelligence to make them very good at sports forecasts,” Rosenberg says. In multiple studies, researchers have used UNU to test the theory of swarm intelligence — with tantalizing results. In one study conducted by researchers at Oxford University, American soccer fans were asked to predict outcomes in the English Premier League.

When they acted as individuals, their average accuracy was about 55 percent. When they collaborated as a swarm, their accuracy jumped to 72 percent. “This wasn’t just a single victory,” Rosenberg says, “It was fifty games over five weeks!”

The A.I. aspect of UNU comes in as algorithms at the back end. These algorithms monitor how users engage in the platform, whether their interactions display confidence, overconfidence, or uncertainty, and tries to guide the cursor towards the prediction that best represents their combined knowledge.

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“The people possess the knowledge, wisdom, insight, and intuition, and the A.I. algorithms figure out the optimal way to combine their diverse views as they’re working together as a swarm,” Rosenberg says. If you’re wondering (and we know you are) Unanimous A.I. ran a swarm for this Super Bowl.

According to the swarm’s predictions, the Patriots will win by between 4 and 6 points, with the game’s total point count exceeding 48.5. Whether or not this prediction is accurate, profits garnered from sports betting aren’t part of UNU’s business plan. Nonetheless, the company’s approach of combining algorithms with human intelligence in many ways mirrors the one used by betting syndicates and startups like Stratagem.

So, although A.I. may someday power the sports gambling world, humans still seem to make the best bets.

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