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Hitting the Books: How Amazon's aggressive R&D push made it an e-commerce behemoth

Amazon is the Standard Oil of the 21st century. Its business operations and global reach dwarf those of virtually every other company on the planet — and exceed the GDP of more than a few countries — illustrating the vital importance innovation has on the modern economy. In his latest book, The Exponential Age: How Accelerating Technology is Transforming Business, Politics and Society, author Azeem Azhar examines how the ever-increasing pace of technological progress is impacting, influencing — and often rebuilding — our social, political and economic mores from the ground up.

Diversion Books

Excerpted from The Exponential Age: How Accelerating Technology is Transforming Business, Politics and Society by Azeem Azhar. Copyright © 2021 Azeem Azhar. Printed with permission of the publisher, Diversion Books. All rights reserved.


In 2020, Amazon turned twenty-six years old. Over the previous quarter of a century, the company had transformed shopping. With retail revenues in excess of $213 billion, it was larger than Germany’s Schwarz Gruppe, America’s Costco, and every British retailer. Only America’s Walmart, with more than half a trillion dollars of sales, was bigger. But Amazon was, by this time, far and away the world’s largest online retailer. Its online business was about eight times larger than Walmart’s. Amazon was more than just an online shop, however. Its huge operations in areas such as cloud computing, logistics, media, and hardware added a further $172 billion in sales.

At the heart of Amazon’s success is an annual research and development budget that reached a staggering $36 billion in 2019, and which is used to develop everything from robots to smart home assistants. This sum leaves other companies — and many governments — behind. It is not far off the UK government’s annual budget for research and development. The entire US government’s federal R&D budget for 2018 was only $134 billion. 

Amazon spent more on R&D in 2018 than the US National Institutes of Health. Roche, the global pharmaceutical company renowned for its investment in research, spent a mere $12 billion in R&D in 2018. Meanwhile Tesco, the largest retailer in Britain — with annual sales in excess of £50 billion (approximately $70 billion) — had a research lab whose budget was in the “six figures” in 2016.

Perhaps more remarkable is the rate at which Amazon grew this budget. Ten years earlier, Amazon’s research budget was $1.2 billion. Over the course of the next decade, the firm increased its annual R&D budget by about 44 percent every year. As the 2010s went on, Amazon doubled down on its investments in research. In the words of Werner Vogels, the firm’s chief technology officer, if they stopped innovating they “would be out of business in ten to fifteen years.”

In the process, Amazon created a chasm between the old world and the new. The approach of traditional business was to rely on models that succeeded yesterday. They were based on a strategy that tomorrow might be a little different, but not markedly so.

This kind of linear thinking, rooted in the assumption that change takes decades and not months, may have worked in the past—but not anymore. Amazon understood the nature of the Exponential Age. The pace of change was accelerating; the companies that could harness the technologies of the new era would take off. And those that couldn’t keep up would be undone at remarkable speed.

This divergence between the old and the new is one example of what I call the “exponential gap.” On the one hand, there are technologies that develop at an exponential pace—and the companies, institutions, and communities that adapt to or harness those developments. On the other, there are the ideas and norms of the old world. The companies, institutions, and communities that can only adapt at an incremental pace. These get left behind—and fast.

The emergence of this gap is a consequence of exponential technology. Until the early 2010s, most companies assumed the cost of their inputs would remain pretty similar from year to year, perhaps with a nudge for inflation. The raw materials might fluctuate based on commodity markets, but their planning processes, institutionalized in management orthodoxy, could manage such volatility. But in the Exponential Age, one primary input for a company is its ability to process information. One of the main costs to process that data is computation. And the cost of computation didn’t rise each year; it declined rapidly. The underlying dynamics of how companies operate had shifted.

In Chapter 1, we explored how Moore’s Law amounts to a halving of the underlying cost of computation every couple of years. It means that every ten years, the cost of the processing that can be done by a computer will decline by a factor of one hundred. But the implications of this process stretch far beyond our personal laptop use—and far beyond the interests of any one laptop manufacturer.

In general, if an organization needs to do something that uses computation, and that task is too expensive today, it probably won’t be too expensive in a couple of years. For companies, this realization has deep significance. Firms that figured out that the effective price of computation was declining, even if the notional price of what they were buying was staying the same (or even rising), could plan, practice, and experiment with the near future in mind. Even if those futuristic activities were expensive now, they would become affordable soon enough. Organizations that understood this deflation, and planned for it, became well-positioned to take advantage of the Exponential Age.

If Amazon’s early recognition of this trend helped transform it into one of the most valuable companies in history, they were not alone. Many of the new digital giants—from Uber to Alibaba, Spotify to TikTok—took a similar path. And following in their footsteps were firms who understand how these processes apply in other sectors. The bosses at Tesla understood that the prices of electric vehicles might decline on an exponential curve, and launched the electric vehicle revolution. The founders of Impossible Foods understood how the expensive process of precision fermentation (which involves genetically modified microorganisms) would get cheaper and cheaper. Executives at space companies like Spire and Planet Labs understood this process would drive down the cost of putting satellites in orbit. Companies that didn’t adapt to exponential technology shifts, like much of the newspaper publishing industry, didn’t stand a chance.

We can visualize the gap by returning to our now-familiar exponential curve. As we’ve seen, individual technologies develop according to an S-curve, which begins by roughly following an exponential trajectory. And as we’ve seen, it starts off looking a bit humdrum. In those early days, exponential change is distinctly boring, and most people and organizations ignore it. At this point in the curve, the industry producing an exponential technology looks exciting to those in it, but like a backwater to everyone else. But at some point, the line of exponential change crosses that of linear change. Soon it reaches an inflection point. That shift in gear, which is both sudden and subtle, is hard to fathom. 

Because, for all the visibility of exponential change, most of the institutions that make up our society follow a linear trajectory. Codified laws and unspoken social norms; legacy companies and NGOs; political systems and intergovernmental bodies—all have only ever known how to adapt incrementally. Stability is an important force within institutions. In fact, it’s built into them.

The gap between our institutions’ capacity to change and our new technologies’ accelerating speed is the defining consequence of our shift into the Exponential Age. On the one side, you have the new behaviors, relationships, and structures that are enabled by exponentially improving technologies, and the products and services built from them. On the other, you have the norms that have evolved or been designed to suit the needs of earlier configurations of technology. The gap leads to extreme tension. In the Exponential Age, this divergence is ongoing—and it is everywhere.

Spotify opens its Car Thing waitlist to all US users

Spotify is expanding US availability of its Car Thing, an $80 music and podcast player for vehicles. The company debuted the gizmo back in the spring on an invite-only basis and only charged users for shipping during a test phase.

Those who signed up for the Car Thing waitlist before now will get first dibs on the company's first hardware device. In addition, both free and Premium Spotify members in the country can now sign up for the waitlist, though the Car Thing requires a Premium subscription and a smartphone for connectivity. Everyone who signs up for the waitlist will eventually be offered a Car Thing.

Spotify worked on Car Thing for several years before it started shipping the device a few months ago. The idea is to bring infotainment features to almost any car, particularly older ones without newfangled touchscreens. Once you hook up Car Thing to your vehicle with the help of one of the included mounts, you can use it to play music and podcasts with either physical controls or "Hey Spotify" voice commands.

Facebook is using first-person videos to train future AIs

One of the obvious goals of almost every computer vision project is to enable a machine to see, and perceive, the world as a human does. Today, Facebook has started talkingabout Ego4D, its own effort in this space, for which it has created a vast new data set to train future models. In a statement, the company said that it had recruited 13 universities across nine countries, who had collected 2,200 hours of footage from 700 participants. This footage was taken from the perspective of the user, which can be used to train these future AI models. Kristen Grauman, Facebook’s lead research scientist, says that this is the largest collection of data explicitly created for this focus.

The footage was centered on a number of common experiences in human life, including social interaction, hand and object manipulation and predicting what’s going to happen. It’s, as far as the social network is concerned, a big step toward better computing experiences which, until now, have always focused on sourcing data from the bystander’s perspective. Facebook has said that the data sets will be released in November, “for researchers who sign Ego4D’s data use agreement.” And, next year, researchers from beyond this community will be challenged to better train machines to understand what exactly humans are doing in their lives.

Naturally, there is the angle that Facebook, which now has a camera glasses partnership with Ray Ban, is looking to improve its own capabilities in future. You probably already know about the perils of what this potential surveillance could entail, and why anyone might feel a little leery about the announcement.

Facebook’s latest effort to curtail leaks immediately leaked

Facebook is ramping up its fight against leakers following the disclosures of whistleblower Frances Haugen. According to The New York Times, Facebook is limiting access to some internal groups that deal with “sensitive” issues like safety and elections. That the change, which was made to prevent further leaks, immediately leaked is both highly amusing and emblematic of some of the bigger issues the company is currently facing.

Ever since Haugen revealed herself as the whistleblower, one of the more noteworthy aspects of her story is that the documents she provided to Congress and the Securities and Exchange Commission were widely accessible to employees. The documents included slides detailing the company’s research into teen mental health, as well as numerous memos about how the company has handled rules for VIPs, misinformation and other thorny issues.

As The Times points out, the reason these documents were so readily available is because Facebook has long had an open culture that promotes sharing. And employees themselves often take to its internal communication platform, Workplace, to discuss controversial issues facing the company.

But now the social network is moving away from that openness. The company is making some internal groups private, and will remove employees “whose work isn’t related to safety and security,” according to the report. “Sensitive Integrity discussions will happen in closed, curated forums in the future,” the company told employees in a memo.

On one hand, the fact that news of the change immediately leaked would seem to back up that the company is in fact more leaky than it has been in years past. But it could also signal increasing unrest among employees, some of whom are reportedly concerned that walling off teams that work on important issues could ultimately do more harm than good.

It also underscores just how much Facebook is still reeling from Haugen’s disclosures. In addition to the Senate hearing last week, Haugen is expected to brief the select committee investigating the Jan. 6th insurrection, as well as European lawmakers investigating the company. The SEC also appears to be investigating her claims.

Instagram is testing in-app notifications for service outages

One week after a massive Facebook outage that took all of the social network’s apps offline for more than six hours, Instagram says it’s testing notifications that will alert users to “temporary issues” like outages or other technical issues.

The new alerts would appear in users’ Activity Feed, alongside other in-app notifications. The messages could be used to let users know about specific issues, like Story uploads not working, or a more widespread problem, like the two outages last week. Importantly, Instagram says it doesn’t plan to alert users to every issue, but ones that may be a source of widespread confusion.

“We won’t send a notification every single time there is an outage, but when we see that people are confused and looking for answers, we’ll determine if something like this could help make things clearer,” Instagram wrote in a blog post. The company added that it’s testing the feature in the US “for the next few months.”

Instagram

Separately, Instagram also showed off a new “account status” section of its app, which is meant to alert users to “what's going on with your account” more generally. Instagram says it’s starting with notifications about posts that are removed and when an account “is at risk of being disabled” due to rule violations.

According to Instagram, the feature is meant to make it easier for users to understand why a post may have been removed, and whether or not they may be in danger of losing an account altogether. While the app has notified users in the past when a post is labeled or removed, the company hasn’t always done a good job letting people know which policy they violated. The Oversight Board has repeatedly told Facebook it needs to do a better job at explaining rules to users, and account status could help them do just that.

Account status could also help the app address a more Instagram-specific issue: concerns over “shadowbanning.” Instagram says that “in the coming months” it plans to update account status to let people know “how their content is being distributed and recommended across different parts of Instagram.” 

T-Mobile wireless home internet service now costs $10 less

T-Mobile has slashed $10 off the wireless home internet service it launched in April. From $60, it now costs $50 a month, which is the same price it charged customers during the product's pilot program that started back in 2019. The service gives customers access to a gateway router/modem device that converts T-Mobile's 4G LTE and 5G networks into WiFi with typical download speeds of 35 to 115 Mbps. It has no annual contract, no data caps and, as the carrier keeps repeating in its announcement, no hidden fees and charges.

That $50 a month includes taxes and rental for the gateway, which customers have to return if they decide to cancel. They'd have to install it themselves, but the carrier says it will take them as little as 15 minutes. T-Mobile started testing the wireless home internet service in rural and underserved areas a couple of years ago in an invite-only trial for 50,000 homes. It rolled out access to the pilot program to over 130 cities across the US before the service's official launch.

Those interested will have to take note, however, that the price only applies if they pay via AutoPay. Without automatic billing, the price goes up to $55, which is still $10 less than the $65 it used to cost. 

Amazon is reportedly working on a smart fridge that tracks what's inside

Amazon is reportedly aiming to bring some of the tech it uses at cashierless Amazon Go stores to your kitchen. According to Insider, the company has been working on a smart fridge that can monitor items and help you order replacements if you're running low on something.

The team behind the Amazon Go systems is said to be heading the charge on the project, which has been in the works for at least two years. The Just Walk Out tech used at Go stores tracks what shoppers put in their carts and automatically charges them when they leave. Members of the Amazon Fresh and Lab126 hardware teams are reportedly involved with the fridge project too.

The fridge would monitor the items inside and keep tabs on your purchasing habits, according to the report. If you run low on something you buy frequently, the fridge would notify you and make it easier to order more from Whole Foods or Amazon Fresh, which could give the company's grocery division a boost. The fridge could offer recipe suggestions too, which may prove useful if you forget about an item that's about to expire.

Amazon wouldn't make the fridges itself, Insider's sources said. It's looking to team up with an appliance manufacturer. There's a possibility that Alexa voice control could be included. That's said to not be a major concern, but given Amazon's propensity for stuffing Alexa into nearly every other type of product, including home robots and its own TVs, it wouldn't be a surprise if the fridge has voice assistant support.

The company has reportedly spent upwards of $50 million per year on the project so far. Even so, there's no guarantee that the fridge will come to market as it's possible Amazon will shelve the plans. If the fridge does come to market, it likely won't come cheap. An Amazon spokesperson told Engadget the company doesn't comment “on rumors or speculation.”

The concept isn't entirely new. In 2016, Samsung revealed a fridge that can help you keep track of what's inside without having to open the door. You can even order groceries using the built-in touchscreen. Amazon's fridge would take the idea a little further, though, since it would flag items that you're about to run out of and help you order more through the company's own grocery ecosystem.

AirPods Pro drop back down to $179 on Amazon

Amazon is having a huge sale on AirPods right now, slashing up to 35 percent off some models. Of note are the AirPods Pro, Apple's best sounding earbuds, which are back down to $179. That's $70 off their normal price and only $10 more than the record low that we saw during the holiday shopping season last year. Also discounted are AirPods with the wireless charging case, which are down to an all-time low of $129, and AirPods with the standard case, which are on sale for $109. Amazon claims these are "limited time" sales, so it's unclear if these discounts will be available after today.

Buy AirPods Pro at Amazon - $179Buy AirPods (wireless charging case) at Amazon - $129Buy AirPods (standard case) at Amazon - $109

While we thought we might hear about new AirPods during Apple's event last month, the tech giant didn't announce anything new in that department. That means all of these models are a few years old at this point, but they remain some of the best true wireless earbuds you can get if you live within the Apple ecosystem. AirPods Pro earned a score of 87 from us for their improved sound quality, better fitting design with IPX4 water resistance and convenient features like hands-free Siri access. They're far and away the best sounding Apple earbuds you can get, and they do a good job of blocking out surrounding noises with active noise cancellation and Transparency Mode.

Regular AirPods are better for those who already liked the fit of Apple's EarPods, which used to come with each new iPhone. They have decent sound and good wireless range, plus a solid five-hour battery life, too. But what sets any pair of AirPods apart is their fast pairing and switching between Apple devices. The H1 chip inside allows them to recognize which device you're actively using and switch to it, so you can go form taking a call on your iPhone to listening to music from your Mac.

Aside from the AirPods Pro, the kicker in Amazon's sale is the wireless charging case — they originally cost $199 but have been hovering at $159 for months. The last time we saw them close to this $129 record low was in early August. And that means you're only paying $20 extra for the wireless charging case, which is a great deal.

Follow @EngadgetDeals on Twitter for the latest tech deals and buying advice.

Hitting the Books: Why that one uncle of yours continually refuses to believe in climate change

The holidays are fast approaching and you know what that means: pumpkin spice everything, seasonal cheer, and family gatherings — all while avoiding your QAnon adherent relatives like the plague. But when you do eventually get cornered by them, come prepared. 

In his latest book, How to Talk to a Science Denier, author Lee McIntyre examines the phenomenon of denialism, exploring the conspiracy theories that drive it, and explains how you can most effectively address your relatives' misplaced concerns over everything from mRNA vaccines to why the Earth isn't actually flat.

The MIT Press

How to Talk to a Science Denier: Conversations with Flat Earthers, Climate Deniers, and Other Who Defy Reason, by Lee McIntyre, published by The MIT Press.


Belief in conspiracy theories is one of the most toxic forms of human reasoning. This is not to say that real conspiracies do not exist. Watergate, the tobacco companies’ collusion to obfuscate the link between cigarette smoking and cancer, and the George W. Bush–era NSA program to secretly spy on civilian Internet users are all examples of real-life conspiracies, which were discovered through evidence and exposed after exhaustive investigation.

By contrast, what makes conspiracy theory reasoning so odious is that whether or not there is any evidence, the theory is asserted as true, which puts it beyond all reach of being tested or refuted by scientists and other debunkers. The distinction, therefore, should be between actual conspiracies (for which there should be some evidence) and conspiracy theories (which customarily have no credible evidence). We might define a conspiracy theory as an “explanation that makes reference to hidden, malevolent forces seeking to advance some nefarious aim.” Crucially, we need to add that these tend to be “highly speculative [and] based on no evidence. They are pure conjecture, without any basis in reality.”

When we talk about the danger of conspiracy theories for scientific reasoning, our focus should therefore be on their nonempirical nature, which means that they are not even capable of being tested in the first place. What is wrong with conspiracy theories is not normally that they have already been refuted (though many have), but that thousands of gullible people will continue to believe them even when they have been debunked.

If you scratch a science denier, chances are you’ll find a conspiracy theorist. Sadly, conspiracy theories seem to be quite common in the general population as well. In a recent study by Eric Oliver and Thomas Wood they found that 50 percent of Americans believed in at least one conspiracy theory.

This included the 9/11 truther and Obama birther conspiracies, but also the idea that the Food and Drug Administration (FDA) is deliberately withholding a cure for cancer, and that the Federal Reserve intentionally orchestrated the 2008 recession. (Notably, the JFK assassination conspiracy was so widely held that it was excluded from the study.)

Other common conspiracy theories — which run the range of popularity and outlandishness — are that “chemtrails” left by planes are part of a secret government mind-control spraying program, that the school shootings at Sandy Hook and Parkland were “false flag” operations, that the government is covering up the truth about UFOs, and of course the more “science-related” ones that the Earth is flat, that global warming is a hoax, that some corporations are intentionally creating toxic GMOs, and that COVID-19 is caused by 5G cell phone towers.

In its most basic form, a conspiracy theory is a non-evidentially justified belief that some tremendously unlikely thing is nonetheless true, but we just don’t realize it because there is a coordinated campaign run by powerful people to cover it up. Some have contended that conspiracy theories are especially prevalent in times of great societal upheaval. And, of course, this explains why conspiracy theories are not unique to modern times. As far back as the great fire of Rome in 64 AD, we saw conspiracy theories at work, when the citizens of Rome became suspicious over a weeklong blaze that consumed almost the entire city — while the emperor Nero was conveniently out of town. Rumors began to spread that Nero had started it in order to rebuild the city in his own design. While there was no evidence that this was true (nor for the legend that Nero sang while the city burned), Nero was apparently so upset by the accusation that he started his own conspiracy theory that it was in fact the Christians who were responsible, which led to the prevalence of burning them alive.

Here one understands immediately why conspiracy theories are anathema to scientific reasoning. In science, we test our beliefs against reality by looking for disconfirming evidence. If we find only evidence that fits our theory, then it might be true. But if we find any evidence that disconfirms our theory, it must be ruled out. With conspiracy theories, however, they don’t change their views even in the face of disconfirming evidence (nor do they seem to require much evidence, beyond gut instinct, that their views are true in the first place). Instead, conspiracy theorists tend to use the conspiracy itself as a way to explain any lack of evidence (because the clever conspirators must be hiding it) or the presence of evidence that disconfirms it (because the shills must be faking it). Thus, lack of evidence in favor of a conspiracy theory is in part explained by the conspiracy itself, which means that its adherents can count both evidence and lack of evidence in their favor.

Virtually all conspiracy theorists are what I call “cafeteria skeptics.” Although they profess to uphold the highest standards of reasoning, they do so inconsistently. Conspiracy theorists are famous for their double standard of evidence: they insist on an absurd standard of proof when it concerns something they do not want to believe, while accepting with scant to nonexistent evidence whatever they do want to believe. We have already seen the weakness of this type of selective reasoning with cherry-picking evidence. Add to this a predilection for the kind of paranoid suspicion that underlies most conspiracy-minded thinking, and we face an almost impenetrable wall of doubt. When a conspiracy theorist indulges their suspicions about the alleged dangers of vaccines, chemtrails, or fluoride — but then takes any contrary or debunking information as itself proof of a cover-up — they lock themselves in a hermetically sealed box of doubt that no amount of facts could ever get them out of. For all of their protests of skepticism, most conspiracy theorists are in fact quite gullible.

Belief in the flatness of the Earth is a great example. Time and again at FEIC 2018, I heard presenters say that any scientific evidence in favor of the curvature of the Earth had been faked. “There was no Moon landing; it happened on a Hollywood set.” “All the airline pilots and astronauts are in on the hoax.” “Those pictures from space are Photoshopped.” Not only did disconfirming evidence of these claims not cause the Flat Earthers to give up their beliefs, it was used as more evidence for the conspiracy! And of course to claim that the devil is behind the whole cover-up about Flat Earth could there be a bigger conspiracy theory? Indeed, most Flat Earthers would admit that themselves. A similar chain of reasoning is often used in climate change denial. President Trump has long held that global warming is a “Chinese hoax” meant to undermine the competitiveness of American manufacturing.

Others have contended that climate scientists are fudging the data or that they are biased because they are profiting from the money and attention being paid to their work. Some would argue that the plot is even more nefarious — that climate change is being used as a ruse to justify more government regulation or takeover of the world economy. Whatever evidence is presented to debunk these claims is explained as part of a conspiracy: it was faked, biased, or at least incomplete, and the real truth is being covered up. No amount of evidence can ever convince a hardcore science denier because they distrust the people who are gathering the evidence. So what is the explanation? Why do some people (like science deniers) engage in conspiracy theory thinking while others do not?

Various psychological theories have been offered, involving factors such as inflated self-confidence, narcissism, or low self-esteem. A more popular consensus seems to be that conspiracy theories are a coping mechanism that some people use to deal with feelings of anxiety and loss of control in the face of large, upsetting events. The human brain does not like random events, because we cannot learn from and therefore cannot plan for them. When we feel helpless (due to lack of understanding, the scale of an event, its personal impact on us, or our social position), we may feel drawn to explanations that identify an enemy we can confront. This is not a rational process, and researchers who have studied conspiracy theories note that those who tend to “go with their gut” are the most likely to indulge in conspiracy-based thinking. This is why ignorance is highly correlated with belief in conspiracy theories. When we are less able to understand something on the basis of our analytical faculties, we may feel more threatened by it.

There is also the fact that many are attracted to the idea of “hidden knowledge,” because it serves their ego to think that they are one of the few people to understand something that others don’t know. In one of the most fascinating studies of conspiracy-based thinking, Roland Imhoff invented a fictitious conspiracy theory, then measured how many subjects would believe it, depending on the epistemological context within which it was presented. Imhoff’s conspiracy was a doozy: he claimed that there was a German manufacturer of smoke alarms that emitted high-pitched sounds that made people feel nauseous and depressed. He alleged that the manufacturer knew about the problem but refused to fix it. When subjects thought that this was secret knowledge, they were much more likely to believe it. When Imhoff presented it as common knowledge, people were less likely to think that it was true.

One can’t help here but think of the six hundred cognoscenti in that ballroom in Denver. Out of six billion people on the planet, they were the self-appointed elite of the elite: the few who knew the “truth” about the flatness of the Earth and were now called upon to wake the others.

What is the harm from conspiracy theories? Some may seem benign, but note that the most likely factor in predicting belief in a conspiracy theory is belief in another one. And not all of those will be harmless. What about the anti-vaxxer who thinks that there is a government cover-

up of the data on thimerosal, whose child gives another measles? Or the belief that anthropogenic (human- caused) climate change is just a hoax, so our leaders in government feel justified in delay? As the clock ticks on averting disaster, the human consequences of the latter may end up being incalculable.

Spotify's quiz will help you find a new podcast based on your listening habits

In the last year alone, almost 1.5 million podcasts have been added to Spotify. Fishing out something good from that ocean of content might not be easy, but Spotify wants to help you find a keeper. To mark International Podcast Day, it created a quiz to help listeners discover a show that matches their taste.

Users in the US, UK, Germany and Australia can now check out the Find The One tool. It asks questions such how a podcast can win you over — perhaps you prefer a conversational show or a narrative-driven murder mystery one — and how serious you like things to be. Spotify will then make a recommendation that's partly based on your listening habits.

The company says it found correlations between some artists and podcasts. Lil Nas X, for instance, has a lot of gamer fans who also listen to the likes of the TommyInnit Podcast, while Olivia Rodrigo and Call Her Daddy have a shared audience. Spotify also discovered that many BTS and Queen fans listen to podcasts about... BTS and Queen.