Entertainment

New Wi-Fi data shows why Peloton is in trouble

Smart speakers and smart TVs continue to see strong momentum, according to new data from Wi-Fi router software maker Plume.

Image of a female fitness instructor on a smart bike screen

As people leave their pandemic cocoons, they’re increasingly ditching their smart bikes.

Photo: Peloton

Home workouts are so 2021: As people leave their pandemic cocoons, they’re increasingly ditching their Peloton classes, according to new data from Wi-Fi networking startup Plume Design.

During the first six months of this year, the average amount of data streamed to at-home fitness bikes was down 23% when compared to the same time span a year ago, Plume revealed as part of its IQ Smart Home Market Report released Wednesday.

It’s the single biggest contraction among home Wi-Fi devices that Plume was able to measure. Fitness bikes were followed by media players (Blu-ray players, iPods and similar devices), which saw a decline of 14%, and PCs, which were down 7% year-over-year. The picture looks notably different for modern home entertainment devices. Smart TVs saw data consumption increase by 34% year-over-year, with smart speaker data usage up 27% year-over-year.

The bleak picture for Peloton comes after the company announced plans to lay off 780 employees and close a yet-to-be-determined number of stores earlier this month. Last week, Peloton told investors it had losses of $1.2 billion during the most recent quarter, with revenues down 28% year-over-year.

Peloton also saw its member numbers decline by 2% quarter-over-quarter and added close to zero new connected fitness subscribers in its most recent quarter. What’s more, even subscribers who are sticking with the company aren’t working out nearly as much as they used to. The number of average monthly Peloton workouts per subscriber was down 26% year-over-year.

Plume’s data not only corroborates those trends but also shows that connected fitness as a whole is still a pretty small phenomenon when compared to other types of entertainment. On average, households with fitness bikes consumed just 0.13 GB of data per month via those devices during the first half of this year. For comparison’s sake, households with smart TVs streamed nearly 85 GB of content per month during the same time frame.

Smart TVs also surpassed set-top boxes, which include streaming devices like Apple TV and those made by Roku and Amazon, in data consumption this year. Households streamed an average of 84.62 GB of data per month to smart TVs during the first half of the year, compared to 75.15 GB streamed to set-top boxes. During the first six months of 2021, external streaming devices were still slightly ahead of smart TVs when it came to data consumption (70.2 GB vs. 63.24 GB).

Plume measures this kind of data both through its own mesh routers as well as third-party hardware running its software. The company has partnerships with ISPs like Comcast, Charter and Vodafone, and it has insights into the data usage of more than 41 million homes worldwide.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

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Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

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FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

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Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

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Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

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Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

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