After a slight blunder with an American retailer, Sonos has officially made its two new speakers official. 

Alongside the Sonos Play, which is positioned as one of the brand’s most flexible speakers, is the Sonos Era 100 SL. But how does the Era 100 SL compare to the similarly titled Era 100? 

Considering we awarded the Sonos Era 100 a 4.5-star rating, why should you buy the Era 100 SL?

To help you decide, we’ve compared the specs of the Sonos Era 100 SL to the Era 100 and pointed out the key differences and noteworthy similarities between the two below. Keep reading to see which speaker is likely to suit you best.

Not sold on either? Visit our list of the best Bluetooth speakers and best outdoor speakers to find your new favourite model.

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Price and Availability

At the time of writing, the Sonos Era 100 SL is available for pre-order and will officially launch in stores on March 31st. With an RRP of $189/£169, it’s hailed as being Sonos’ “most cost-effective way to build” a home setup.

Instead, the Sonos Era 100 has an RRP of £199/$219. However, as it’s an older speaker, it is possible to find the device with a price cut, so make sure you keep an eye out during sales events.

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Sonos Era 100 supports voice control

One of the biggest differences between the Sonos Era 100 SL and Era 100 is that the latter has a microphone and, therefore, supports voice control. You can either use Sonos Voice Control to manage music, or you can also rely on Amazon Alexa for answering questions, setting timers and the like. 

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On the other hand, the Sonos Era 100 SL isn’t equipped with any voice control or assistants, as it lacks a microphone. Sonos explains that the decision to not equip the Era 100 SL with built-in voice control was to ensure the speaker is more affordable than the 100. However, if you pair the Era 100 SL with a voice-enabled soundbar then you’ll still benefit from voice control, even though the Era 100 SL doesn’t actually support it.

Android users won’t be able to use Trueplay tuning technology on the Sonos Era 100 SL

Following on from the above, the Era 100 features Sonos’ clever Trueplay technology which measures how sound reflects off walls and furnishings in a room and tunes the speaker accordingly. While the Sonos Era 100 SL does also support Trueplay, it will only work with an iOS device. This is because the Era 100 SL doesn’t have a microphone, which Android devices need to activate Trueplay. 

With this in mind, if you’re sporting one of the best Android phones and want optimised sound for your room, then the Sonos Era 100 SL might not be the top choice for you. 

Both have the same sonic architecture

Under their respective hoods, the Sonos Era 100 SL and Era 100 sport the same sonic architecture. In fact, Sonos promises that the more affordable Era 100 SL will have “no compromises on sound quality”. 

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Considering we concluded that the Era 100’s provides a weightier performance across the frequency range, this certainly bodes well for the Era 100 SL. We also found the Era 100 sported an increase in bass over its predecessor that gave music genres such as R&B, Hip Hop and Pop more impact and excitement too.

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Having said that, we’d encourage users to play around with the EQ to perfect the bass and treble levels to best suit your personal listening preferences. Although we haven’t reviewed the Era 100 SL yet, we expect this will be the case for the new speaker too.

Sonos Era 100 SL is designed to fit into your existing speaker set-up

Although you can listen to the Era 100 SL on its own, Sonos explains it’s designed to slot into your existing home entertainment set-up. For example, you can pair two Era 100 SLs to a Sonos soundbar, such as the Sonos Beam or Sonos Arc Ultra, to create a surround sound system.

Alternatively, Sonos does state that you can use the Era 100 SL as a stand-alone speaker too.

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It’s a similar situation with the Era 100, which can be paired with another Era 100 SL and a soundbar too.

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Both share similar designs, although the Era 100 SL is slightly lighter

At first glance, you’d be forgiven for thinking the Era 100 and Era 100 SL were the same speakers, as both measure in at 7.19 x 4.72 x 5.14 inches and come in a choice of Black or White. However, unsurprisingly as it lacks a microphone, the Era 100 SL weighs slightly less at 1.95kg compared to 2.02kg. 

Early Verdict

As we haven’t reviewed the Sonos Era 100 SL yet, we’ll hold off from giving a conclusive verdict. However, as it’s slightly more affordable than the Era 100 and promises the same brilliant sound quality and sleek design, the Era 100 SL is certainly an appealing option for many – as long as you’re an iOS user and won’t miss voice control.

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Every GPU cluster has dead time. Training jobs finish, workloads shift and hardware sits dark while power and cooling costs keep running. For neocloud operators, those empty cycles are lost margin.

The obvious workaround is spot GPU markets — renting spare capacity to whoever needs it. But spot instances mean the cloud vendor is still the one doing the renting, and engineers buying that capacity are still paying for raw compute with no inference stack attached.

FriendliAI’s answer is different: run inference directly on the unused hardware, optimize for token throughput, and split the revenue with the operator. FriendliAI was founded by Byung-Gon Chun, the researcher whose paper on continuous batching became foundational to vLLM, the open source inference engine used across most production deployments today.

Chun spent over a decade as a professor at Seoul National University studying efficient execution of machine learning models at scale. That research produced a paper called Orca, which introduced continuous batching. The technique processes inference requests dynamically rather than waiting to fill a fixed batch before executing. It is now industry standard and is the core mechanism inside vLLM.

This week, FriendliAI is launching a new platform called InferenceSense. Just as publishers use Google AdSense to monetize unsold ad inventory, neocloud operators can use InferenceSense to fill unused GPU cycles with paid AI inference workloads and collect a share of the token revenue. The operator’s own jobs always take priority — the moment a scheduler reclaims a GPU, InferenceSense yields.

“What we are providing is that instead of letting GPUs be idle, by running inferences they can monetize those idle GPUs,” Chun told VentureBeat.

How a Seoul National University lab built the engine inside vLLM

Chun founded FriendliAI in 2021, before most of the industry had shifted attention from training to inference. The company’s primary product is a dedicated inference endpoint service for AI startups and enterprises running open-weight models. FriendliAI also appears as a deployment option on Hugging Face alongside Azure, AWS and GCP, and currently supports more than 500,000 open-weight models from the platform.

InferenceSense now extends that inference engine to the capacity problem GPU operators face between workloads.

How it works

InferenceSense runs on top of Kubernetes, which most neocloud operators are already using for resource orchestration. An operator allocates a pool of GPUs to a Kubernetes cluster managed by FriendliAI — declaring which nodes are available and under what conditions they can be reclaimed. Idle detection runs through Kubernetes itself.

“We have our own orchestrator that runs on the GPUs of these neocloud — or just cloud — vendors,” Chun said. “We definitely take advantage of Kubernetes, but the software running on top is a really highly optimized inference stack.”

When GPUs are unused, InferenceSense spins up isolated containers serving paid inference workloads on open-weight models including DeepSeek, Qwen, Kimi, GLM and MiniMax. When the operator’s scheduler needs hardware back, the inference workloads are preempted and GPUs are returned. FriendliAI says the handoff happens within seconds.

Demand is aggregated through FriendliAI’s direct clients and through inference aggregators like OpenRouter. The operator supplies the capacity; FriendliAI handles the demand pipeline, model optimization and serving stack. There are no upfront fees and no minimum commitments. A real-time dashboard shows operators which models are running, tokens being processed and revenue accrued.

Why token throughput beats raw capacity rental

Spot GPU markets from providers like CoreWeave, Lambda Labs and RunPod involve the cloud vendor renting out its own hardware to a third party. InferenceSense runs on hardware the neocloud operator already owns, with the operator defining which nodes participate and setting scheduling agreements with FriendliAI in advance. The distinction matters: spot markets monetize capacity, InferenceSense monetizes tokens.

Token throughput per GPU-hour determines how much InferenceSense can actually earn during unused windows. FriendliAI claims its engine delivers two to three times the throughput of a standard vLLM deployment, though Chun notes the figure varies by workload type.

Most competing inference stacks are built on Python-based open source frameworks. FriendliAI’s engine is written in C++ and uses custom GPU kernels rather than Nvidia’s cuDNN library. The company has built its own model representation layer for partitioning and executing models across hardware, with its own implementations of speculative decoding, quantization and KV-cache management.

Since FriendliAI’s engine processes more tokens per GPU-hour than a standard vLLM stack, operators should generate more revenue per unused cycle than they could by standing up their own inference service. 

What AI engineers evaluating inference costs should watch

For AI engineers evaluating where to run inference workloads, the neocloud versus hyperscaler decision has typically come down to price and availability.

InferenceSense adds a new consideration: if neoclouds can monetize idle capacity through inference, they have more economic incentive to keep token prices competitive.

That is not a reason to change infrastructure decisions today — it is still early. But engineers tracking total inference cost should watch whether neocloud adoption of platforms like InferenceSense puts downward pressure on API pricing for models like DeepSeek and Qwen over the next 12 months.

“When we have more efficient suppliers, the overall cost will go down,” Chun said. “With InferenceSense we can contribute to making those models cheaper.”

Amazon’s AI assistant Alexa+ is getting another new personality. On Thursday, the company announced it’s expanding its lineup of personality styles for users to choose from to include a “Sassy” option, which is for adults only. Notes Amazon, before opting to use the Sassy personality, users will be required to go through additional security checks in the Alexa app.

The personality style will also not be available when Amazon Kids is enabled, Amazon says.

The new option joins others like Brief, Chill, and Sweet, launched last month.

When you toggle on the option for Sassy in the Alexa mobile app, you’re warned that the Sassy style uses explicit language, which is why it requires a security check. On iOS, this involved a Face ID scan.

The AI assistant explained its style to us like this: “The Sassy style is built on one premise: help first, judge always. Every answer comes wrapped in wit and a well-placed roast — it’ll answer your question; it’ll just make you feel something about it first. Expect reality checks delivered with charm, compliments that somehow sting, and warmth you didn’t see coming. Equal-opportunity irreverence, zero apologies. Honest, sharp, and funny — and somehow that’s more helpful than helpful.”

Alexa’s app also had warned that the style could contain “mature subject matter.”

However, further investigation discovered this is not Amazon’s version of something like Grok’s adult AI companions. The AI assistant said the new option won’t get into areas like explicit sexual content, hate speech, illegal activities, personal attacks, or anything that could cause harm to oneself or others.

The move is the latest example of how Amazon is trying to make Alexa+ more customizable, as it revamps the assistant for the generative AI era. By offering the assistant different personalities — including one positioned as more adult — Amazon is borrowing from a broader trend in AI, where companies have been experimenting with tone, style, and personas to make their assistants more engaging and personalized to the individual users’ choices.

from the the-truth-business dept

We’ve already all seen what the Ellison family’s version of “editorial independence” looks like over at CBS, where contrarian troll Bari Weiss has turned the already very Republican friendly news giant into a safe space for right wing zealots and autocrats. All overseen by a Brendan Carr chosen censor tasked with ensuring the channel always makes Donald Trump happy.

As always with authoritarian regimes (and corporate ownership), this is all presented to the public as an effort to restore balance, eliminate (nonexistent) “liberal bias,” and reach out to real Americans. As if billionaires and their useful idiots could care less about everyday Americana.

After being gifted two Hollywood studios and two major news empires by daddy and Donald Trump, fail-upward nepobaby David Ellison made the rounds last week to insist that CNN’s “editorial independence” would be retained under Paramount/CBS ownership. His evidence? CBS:

“So, look, I’ve said this since the beginning, which is, you know, for — when it really comes to — editorial independence will absolutely be maintained. It’s maintained at CBS. It’ll be maintained at CNN. And, really, who we want to talk to is the 70% of Americans and really around the world that identify as center-left, as center-right. And we want to be in the truth business. We want to be in the trust business. And that’s not going to change.”

Of course, if anybody had actually been paying attention to CBS, they’d see how the network under Weiss has already tried to repeatedly kill stories that aren’t favorable to Donald Trump, gone out of its way to normalize right wing opportunists like Erika Kirk, and has driven away a lot of remaining CBS journalists with Weiss’ obvious efforts to pander to Trump and Netanyahu.

Like CBS, CNN already goes well out of its way to be extra friendly to authoritarians. The network has routinely faced criticism for consistently airing sneering MAGA devotee Scott Jennings. Under Ellison ownership there’s zero serious doubt, by anyone, that CNN will become even more friendly to autocrats. After they get done firing untold thousands of people to try and pay down the deal’s immense debt.

Traditionally there’s only one editorial direction U.S. journalism usually goes under consolidated corporate ownership. U.S. media owners like tax cuts, deregulation, subsidies, access, and merger approvals, so corporate media’s editorial slant generally follows the financial interests of ownership. The pretense that U.S. media suffers from widespread “liberal bias,” or the belief that there are still functional firewalls between ownership and editorial, are long-deceased relics.

Larry Ellison clearly wants to hoover up what’s left of corporate media (including CBS, CNN, HBO) — and fuse it with his co-ownership of TikTok to create a sort of Hungary-esque autocratic state media, where administration allies praise dear leader while the government strangles independent and public media just out of frame.

The only thing saving us from the full and terrible vision of this outcome to date is the fact that very few of the weird nepobabies and brunchlords being tasked with its creation have anything you’d mistake for competence.

Filed Under: authoritarian, bari weiss, consolidation, david ellison, journalism, layoffs, media, propaganda, state media

Companies: cbs, cnn, paramount, warner bros. discovery

Ever since 3D printing has become a popular tool, the question of waste has been looming in the background. The sad reality of rapid prototyping is that you’re going to generate a lot of prints that just don’t aren’t fit for purpose, even if your printer runs them off perfectly every time. Creality has some products on the way aimed at solving that problem, and [Embrace Making] on YouTube has got his hands on a pre-production prototype of the Creality M1 Filament Maker to give the community a first look.

The M1 is actually only half of the system; Creality is also working on an R1 shredder to reduce your prints into re-usable shreds. [Embrace Making] hasn’t gotten his hands on that, but shredding prints isn’t the hard part. We’ve featured plenty of DIY shredders in the past. Extruding filament reliably at home has traditionally proven much more difficult, which is why we mostly outsource it to professionals.

Lacking the matching shredder, and wanting to give the M1 the fairest possible shake, [Embrace] tests the machine out first using Creality-supplied PLA pellets. The filament diameter isn’t as stable as we’ve gotten used to, and the spool rolling setup needs a bit more work.

Again, this is an early prototype. Creality says they’re working on it and claims they’ll get to ±0.05 mm precision in the production models. Doubtless they’ll also fix the errors that led to [Embrace]’s messy spool. That’s probably just software given that the winding mechanism did a pretty good job on the Creality-supplied spool.

Most importantly, the M1-produced filament does print. The prints aren’t perfect due to the variation in diameter, but they turn out surprisingly well for home-made filament. [Embrace] also shows off the ability to mix custom colors and gradients, but, again, using raw PLA rather than shredded material. Hopefully Creality lets him test drive the R1 shredder once its design is further along.

This is hardly the first time we’ve seen a filament extruder. The goal of this product is to pair with a shredder and use it for recycling, but if you’re going to stick with raw plastic pellets, you may as well print them directly.

Dennis Choo is a travel industry veteran who’s spent decades building connections across airlines & tourism networks

In the 1990s, the airline industry underwent a dramatic shift. Across Asia, deregulation and rising middle-class demand were transforming air travel from a luxury into something far more accessible.

Budget airlines were beginning to emerge, promising cheaper fares and simpler service models. Traditional carriers still dominated major routes, but a new generation of low-cost airlines was challenging the status quo.

For many entrepreneurs, it was an opportunity.

One of them was Dennis Choo—a Singaporean travel industry veteran who had spent decades quietly building connections across airlines and tourism networks.

While his name rarely appeared in headlines, Choo would eventually make one of the boldest moves in Singapore’s aviation scene: buying out Temasek Holdings to take majority control of Jetstar Asia.

But his story began long before that.

It all started with a small travel agency

In 1972, Choo founded Holiday Tours & Travel Group (HTT Group) as a modest airline ticketing agency in Singapore.

At the time, travel agencies played a critical role in airline distribution. Before the era of the Internet, booking flights typically meant visiting an agent who handled ticketing, reservations, and itineraries.

Choo saw opportunity in this system and, over the years, expanded into parallel verticals, diversifying his business across tours, airline representation, cruise operations, and hospitality.

Holiday Tours eventually started acting as a General Sales Agent (GSA) for several international carriers in the region, handling sales, marketing, and distribution in markets where airlines lacked a strong local presence.

More importantly, the group cultivated deep relationships with airlines, giving Choo unique insight into how carriers operated behind the scenes. In 1984, these ties were formalised when Qantas acquired a majority stake in HTT Group’s holding company. Company ownership information from the airline’s 2025 financial report shows that Qantas now holds a significant stake in the group (about 75%).

This helped cement Choo’s reputation within the travel industry. It also gave him something even more valuable: insight into how airlines worked behind the scenes.

Moving from selling seats to owning airlines

By the early 2000s, the aviation landscape in Asia was changing rapidly. Low-cost carriers (LCCs) were gaining momentum, inspired by models like Southwest Airlines in the United States and Ryanair in Europe.

Singapore’s aviation sector began seeing new entrants in 2004. Alongside established players like Singapore Airlines, several budget carriers were launching to tap into regional demand.

First to take off was Valuair, a Singapore-based low-cost airline launched in May that year, backed by a group of local investors and led by former Singapore Airlines executive Lim Chin Beng.

But unlike many LCCs of the time, Valuair offered perks such as free hot meals, assigned seating and generous baggage allowances while still charging fares significantly lower than full-service airlines—a model that would ultimately struggle in an intensifying aviation scene.

It made the airline more expensive to operate than the leaner low-cost carriers that were entering the market, including Tiger Airways and Jetstar Asia. Both were backed by deep-pocketed investors—Singapore Airlines and Qantas, respectively—bringing intense price competition to the region.

On top of this, Valuair faced rising fuel costs and limited regional traffic rights, making it difficult to maintain profitability.

Left with few options, the airline turned to consolidation as a solution.

In Jul 2005, Valuair agreed to merge with Jetstar Asia, forming a new holding company called Orange Star, whose shareholders included Qantas, Temasek, and private investors in Singapore, with the former two holding the largest stakes—approximately 45% and 33.5%, respectively. The two airlines continued operating as separate brands under the same parent company.

Choo would come into the picture in 2009.

Despite the merger and additional funding, Valuair’s operations continued to face challenges, and the airline was ultimately struggling to remain profitable. Furthermore, Temasek’s decision to take an 11% stake in rival Tiger Airways had created an awkward dynamic—Qantas found itself sharing an ownership structure with an investor that was simultaneously backing its direct competitor.

This led to a restructuring of Orangestar, creating an opportunity for new investors.

The restructuring resulted in the creation of Newstar Investment Holdings, a new holding company to consolidate ownership of Jetstar Asia. Through his wholly-owned private investment company, Westbrook Investments, Choo acquired a 51% majority stake in Newstar, including Temasek’s shares, while Qantas retained a 49% minority stake.

And just like that, the man who had spent decades selling other airlines’ seats was now in control of two major low-cost carriers in the region.

Overseeing the development of two low-cost carriers

As chairman of Jetstar Asia, Choo oversaw the development of the airline, as well as Valuair, as regional low-cost carriers.

Operating out of Singapore’s Changi Airport, both airlines connected travellers to cities across Southeast Asia, East Asia, and beyond. For many travellers in the region, they became synonymous with affordable flights.

Like most airlines, however, Valuair and Jetstar faced a volatile industry environment.

Low-cost carriers operate on razor-thin margins, and competition in Southeast Asia only intensified over the years with the rise of new players. Eventually, Valuair was fully absorbed into Jetstar Asia in 2014, with its flights and routes integrated under the Jetstar brand.

Jetstar Asia continued operating for more than a decade afterwards—until it reached its final chapter in 2025. It ceased operations on Jul 31, 2025, citing rising costs and mounting competitive pressures.

Beyond Jetstar Asia

Throughout these developments, Dennis Choo has remained a relatively low-profile figure compared with many other business leaders in Singapore, despite his influence in aviation and travel.

Current information on his activities is scarce, but his company’s website still lists him as Group CEO, and under his leadership, Holiday Tours & Travel Group has grown to 10 entities across nine countries and territories in the Asia Pacific region.

With over 150 employees, these operations span China, Indonesia, Korea, Malaysia, the Philippines, Taiwan, Thailand, and Vietnam.

It is an impressive reach, and despite Jetstar Asia eventually closing down, Choo remains a notable presence in the region’s travel and airline sector.

He didn’t get there overnight.

Choo spent 37 years building relationships in the travel industry before making his biggest move—acquiring Temasek’s shares to take majority control of Jetstar Asia, proving that steady experience and long-term vision can open doors in a competitive sector.

• Read other articles we’ve written on Singaporean businesses here.

Featured Image Credit: Bandaranaike International Airport/ Getty Images

Released in 2016, Pokemon Go quickly became a worldwide phenomenon. Even folks who weren’t traditionally interested in the monster-taming franchise were wandering around with their smartphones out, on the hunt for virtual creatures that would appear via augmented reality. Although the number of active users has dropped over the years, it’s estimated that more than 50 million users currently log in and play every month.

From a gameplay standpoint, Go is brilliant. Although the Pokemon that players seek out obviously aren’t real, searching for them closely approximates the in-game experience that the franchise has been known for since its introduction on the Game Boy back in 1996.

But now, instead of moving a character through a virtual landscape in search of the elusive “pocket monsters”, players find them dotted throughout the real world. To be successful, players need to leave their homes and travel to where the Pokemon are physically located — which often happens to be a high-traffic area or other point of interest.

As a game, it’s hard to imagine Pokemon Go being a bigger success. At the peak of its popularity, throngs of players were literally causing traffic jams as they roamed the streets in search of invisible creatures. But what players may not have realized as they scanned the world around them through the game was that they were helping developer Niantic build something even more valuable.

The Imaginary Gig Economy

The game has used augmented reality (AR) to bring the world of Pokemon to life since day one, but it wasn’t until the fall of 2020 that Niantic introduced AR Mapping. With this new feature, players could scan real-world locations and objects by walking around them while the software captured images from their smartphone’s camera. This was presented to the player as “Field Research”, and once completed, it would unlock various rewards in the game.

For those with a technical mindset, the implications of this are immediately obvious. Through the Research system, Niantic could direct Pokemon Go players anywhere they wished. Once the imagery from these Research scans were uploaded, they could be used to create detailed 3D models through the use of photogrammetry. The more players that perform Field Research on a particular location, the more accurate the results.

If Niantic wanted to create a 3D model of a statue in a park or the front of a building, they simply needed to assign it a Field Research task and the players would rush out to collect the data. Forget Google’s Street View — rather than sending a camera-laden car out once every year or so to grab new images, Niantic could sit back while millions of players uploaded high resolution pictures of the world around them in exchange for in-game trinkets that have no physical value.

No Such Thing as a Free Pokemon

In the tech world there’s a common saying: “If something is free, you’re the product.”

The idea being that if you’re using some service without paying for it, there’s an excellent chance that the company providing said service is somehow making money off of the situation. So for example when a user looks up a particular topic with a search engine, they can be presented with contextually appropriate advertisements. By selling this ad space to companies, the search engine provider generates a profit for each “free” search performed by its users. The personal relevancy offered by such bespoke advertisements can be more effective than traditional TV or print ads, which in turn means the search engine provider can charge a premium for them.

Just as in our hypothetical search engine example, Pokemon Go is offered up to players on Android and iOS free of charge. To date, it’s been downloaded by over a billion total users. To make the game financially viable, Niantic eventually needed to find a way to turn all those free downloads into a revenue stream.

The answer is Niantic Spatial. This spin-off company was announced in March of 2025, and offers a Visual Positioning System (VPS) created in part using the photogrammetry data collected by Pokemon Go. Through this service Niantic Spatial offers centimeter-scale positioning for millions of high-traffic locations all over the globe, even in areas where GPS may be inaccurate.

Earlier this week, Niantic Spatial announced they had entered into an agreement with Coco Robotics to provide VPS for their fleet of delivery robots. Images captured by the robot’s onboard cameras can be fed into the VPS to provide a more accurate position than is possible with GPS, even in the best of conditions. This is particularly important for a robot that not only needs to navigate an ever-changing urban landscape, but must arrive at a precise location to successfully complete its delivery.

Always Read the Fine Print

At this point, you may be thinking to yourself that this all seems a bit shady. Can Niantic really take the data that was provided to them by Pokemon Go players and spin that off into a commercial venture that monetizes it? Of course they can, because that’s precisely what players agreed to when they installed the game.

Section 5.2 of the Niantic Terms of Service, titled “Rights Granted by You – AR Content”, states that the company retains wide-ranging rights over anything that users upload through the AR functions of their products:

In short, not only can Niantic do anything they want with player submitted data, but they can pass that freedom on to other entities as they see fit. So while Coco Robotics didn’t even exist when the AR Mapping feature was added to Pokemon Go, all of the imagery that players captured since that time — plus any images that they continue to capture — is fair game.

In the end, it’s unlikely that many players will lose any sleep over the fact that they have unwittingly been collecting training data to help robots more effectively deliver pizzas. But it’s also not hard to imagine a scenario in which that data ends up getting licensed out for some purpose they aren’t comfortable with.

If that happens, their options may be limited. A reading of Niantic’s Privacy Policy would seem to indicate that uploaded AR imagery is anonymized during processing, and as such doesn’t need to be treated in the same way that personally identifiable information would be. As such, players have the right to opt-out of uploading additional data going forward, but can’t remove what’s already been pushed into the system.

Regardless of whether or not this situation impacts you directly, it’s an important cautionary tale in an interconnected world where more and more of what users do online is tracked, filtered, processed, and sold off to the highest bidder. Perhaps something to keep in mind before clicking “I Agree.”