Farewell from Protocol

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Farewell from Protocol
Jamie Condliffe
November 15, 2022
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.
Building this publication has not been easy; as with any small startup organization, it has often been chaotic. But it has also been hugely fulfilling for those involved. We could not be prouder of, or more grateful to, the team we have assembled here over the last three years to build the publication. They are an inspirational group of people who have gone above and beyond, week after week. Today, we thank them deeply for all the work they have done.
We also thank you, our readers, for subscribing to our newsletters and reading our stories. We hope you have enjoyed our work.
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.
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Jamie Condliffe
Jamie Condliffe ( @jme_c ) is the executive editor at Protocol, based in London. Prior to joining Protocol in 2019, he worked on the business desk at The New York Times, where he edited the DealBook newsletter and wrote Bits, the weekly tech newsletter. He has previously worked at MIT Technology Review, Gizmodo, and New Scientist, and has held lectureships at the University of Oxford and Imperial College London. He also holds a doctorate in engineering from the University of Oxford.
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
November 15, 2022
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.
November 15, 2022
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.
Nokleby, who has since left the company, said that for a long time Lily AI got by using a homegrown system, but that wasn’t cutting it anymore. And he said that while some MLops systems can manage a larger number of models, they might not have desired features such as robust data visualization capabilities or the ability to work on premises rather than in cloud environments.
As for finding an MLops platform that works for the company, Lily AI’s CTO and co-founder Sowmiya Chocka Narayanan said last week, "We're still looking.”
As companies expand their use of AI beyond running just a few ML models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, many machine learning practitioners Protocol interviewed for this story say that they have yet to find what they need from prepackaged MLops systems.
“That is the biggest gap in the tech industry right now,” said Nicola Morini Bianzino, global chief client technology officer at EY. The auditing firm has thousands of models in deployment that are used for its customers’ tax returns and other purposes, but has not come across a suitable system for managing various MLops modules, he said.
“I’m actually surprised that none of the big companies have jumped in this space because the opportunity is massive,” Morini Bianzino said.
Depending on how it is defined, projections for the global MLops platform market vary from $3 billion by 2027 to $4 billion by 2025 to $6 billion by 2028 . Companies hawking MLops platforms for building and managing machine learning models include tech giants like Amazon, Google, Microsoft, and IBM and lesser-known vendors such as Comet, Cloudera, DataRobot, and Domino Data Lab.
Although the MLops-related platforms available today are “extremely valuable,” said Danny Lange, vice president of AI and machine learning at gaming and automotive AI company Unity Technologies, “nobody right now is doing it at a level that you ideally want. It's actually a complex problem.” Right now, Unity is using a custom-built system to manage the thousands of ML models it has in deployment, Lange said
Millions of models
Like other large enterprises that have invested in ML for years, Southeast Asia’s banking giant DBS has had to build in-house to manage its data analytics and the 400-plus ML models it runs for things like personalized banking, said Sameer Gupta, group chief analytics officer and managing director.
“When DBS started our journey several years ago, the solutions available in the market primarily focused more on AI/ML activities as experiments and did not meet our requirements to iterate and operationalize quickly,” Gupta told Protocol.
“We had to leverage what was available to develop our in-house capabilities that allows us to better tailor our solutions across the bank.” The company erected its own internal analytics and AI platform, which features an operational cluster to manage data ingestion, computation, storage, and model production, as well as an analytical cluster for data scientists to experiment and develop new tools before they go into production.
Intuit also has constructed its own systems for building and monitoring the immense number of ML models it has in production, including models that are customized for each of its QuickBooks software customers. Sometimes the distinctions in each model are minimal — one company might label certain types of purchases as “office supplies” while another categorizes them with the name of their office retailer of choice, for instance. The model must recognize those distinctions.
“We actually build models that are personalized to each [customer],” said Diane Chang, director of data science at Intuit. “When you look at that, each of those individual models that we built, then we’re over millions.”
Intuit had MLops systems in place before a lot of vendors sold products for managing machine learning, said Brett Hollman, Intuit’s director of engineering and product development in machine learning.
For instance, Hollman said the company built an ML feature management platform from the ground up. “A set of features can help you train a new model. If somebody generates good features on cash flow, some other person that’s doing some other cash flow thing might come along and say, ‘Oh, well, this feature set actually fits my use case.’ We're trying to promote reuse,” he said.
Open or closed
For companies that have been forced to go DIY, building these platforms themselves does not always require forging parts from raw materials. DBS has incorporated open-source tools for coding and application security purposes such as Nexus, Jenkins, Bitbucket, and Confluence to ensure the smooth integration and delivery of ML models, Gupta said.
Intuit has also used open-source tools or components sold by vendors to improve existing in-house systems or solve a particular problem, Hollman said. However, he emphasized the need to be selective about which route to take.
“A vendor may not have all the capabilities [we] need. Looking at an open-source solution and extending an open-source solution might be a better way of approaching that particular component versus going with a vendor,” he said. “If you go with a vendor, you drive their road map, you work with them and drive their road map, but you’re dependent upon their road map versus your own internal software development lifecycle.”
The age-old “build or buy” question is the wrong one to ask, said Zoe Hillenmeyer, chief commercial officer at Peak, which sells an AI decision intelligence platform and related services. When it comes to MLops, she said, “There’s a false dichotomy between build versus buy. That’s an incorrect strategy. I think that the best AI will be a build plus buy.”
If you go with a vendor, you drive their road map, you work with them and drive their road map, but you’re dependent upon their road map versus your own internal software development lifecycle.”
However, creating consistency through the ML lifecycle from model training to deployment to monitoring becomes increasingly difficult as companies cobble together open-source or vendor-built machine learning components, said John Thomas, vice president and distinguished engineer at IBM.
“The enterprise might try to force everyone to use a single development platform. The reality is most people are not there, so you have a whole bunch of different tools. People fight over it — it’s a religious thing,” Thomas said.
IBM has responded to that reality by allowing clients to use its MLops pipelines in conjunction with non-IBM technology, an approach that Thomas said is “new” for IBM.
Engineering talent crunch
Companies struggling to find suitable off-the-shelf MLops platforms are up against another major challenge, too: finding engineering talent.
Many companies do not have software engineers on staff with the level of expertise necessary to architect systems that can handle large numbers of models or accommodate millions of split-second decision requests, said Abhishek Gupta, founder and principal researcher at Montreal AI Ethics Institute and senior responsible AI leader and expert at Boston Consulting Group.
“A lot of these places that are attempting to do this are just not tech-native or tech-first companies,” BCG’s Gupta said. For one thing, smaller companies are competing for talent against big tech firms that offer higher salaries and better resources. “There is a lack of technical talent to a significant degree that hinders the implementation of scalable MLops systems because that knowledge is locked up in those tech-first firms,” he said.
Despite the obstacles, Intuit’s Hollman said it makes sense for companies that have graduated to more sophisticated ML efforts to build for themselves. “If you’re somebody that’s been in AI for a long time and has maturity in it and are doing things that are at the cutting edge of AI, then there’s [a] reason for you to have built some of your own solutions to do some of those things,” he said.
For companies with less-advanced AI operations, shopping at the existing MLops platform marketplace may be good enough, Hollman said.
“If you’re a new entrant into the machine learning space, those platforms are the best place to start. They’re going to have a soup-to-nuts experience,” he said. “Trying to build your own ML platform from scratch is a big undertaking.”
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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.
November 14, 2022
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 .
Penny Lee, Chief Executive Officer, Financial Technology Association
Financial technology is breaking down barriers to financial services and delivering value to consumers, small businesses, and the economy. Financial technology or “fintech” innovations use technology to transform traditional financial services, making them more accessible, lower-cost, and easier to use.
Fintech puts American consumers at the center of their finances and helps them manage their money responsibly. From payment apps to budgeting and investing tools and alternative credit options, fintech makes it easier for consumers to pay for their purchases and build better financial habits.
Nearly half of fintech users say their finances are better due to fintech and save more than $50 a month on interest and fees. Fintech also arms small businesses with the financial tools for success, including low-cost banking services, digital accounting services, and expanded access to capital.
The Financial Technology Association represents the innovators shaping the future of finance, whether it’s streamlining online payments, expanding access to affordable credit, giving small businesses and creators the tools for success, or empowering everyday investors to build wealth. We advocate for modernized financial policies and regulations that allow fintech innovation to drive competition in the economy and expand consumer choice.
Join FTA’s inaugural Fintech Summit in partnership with Protocol on November 16 as we discuss these themes. Spots are still available for this hybrid event, and you can RSVP here to save your seat . Join us as we discuss how to shape the future of finance.
Alex Marsh, Global Head of Policy, Klarna
In its broadest sense, Open Banking has created a secure and connected ecosystem that has led to an explosion of new and innovative solutions that benefit the customer, rapidly revolutionizing not just the banking industry but the way all companies do business. Target benefits are delivered through speed, transparency, and security, and their impact can be seen across a diverse range of use cases.
Sharing financial data across providers can enable a customer (individual or business) to have real-time access to multiple bank accounts across multiple institutions all in one platform, saving time and helping consumers get a more accurate picture of their own finances before taking on debt, providing a more reliable indication than most lending guidelines currently do.
Open Banking can also widen the net of prospective lenders by providing an immediate and accurate understanding of a customer’s financial history, allowing more lenders to better understand the specific risk profile and hence drive a more competitive loan product for the end customer.
Companies can also create carefully refined marketing profiles and therefore, finely tune their services to the specific need. Open Banking platforms like Klarna Kosma also provide a unique opportunity for businesses to overlay additional tools that add real value for users and deepen their customer relationships.
The increased transparency brought about by Open Banking brings a vast array of additional benefits, such as helping fraud detection companies better monitor customer accounts and identify problems much earlier. The list of new value-add solutions continues to grow.
Todd Denbo, Commercial Leader of Money & CEO of Intuit Financing, Inc., Intuit
The speed of business has never been faster than it is today. For small business owners, time is at a premium as they are wearing multiple hats every day. Macroeconomic challenges like inflation and supply chain issues are making successful money and cash flow management even more challenging. In fact, according to a recent Intuit QuickBooks survey, 99% of small businesses are concerned about inflation.
This presents a tremendous opportunity that innovation in fintech can solve by speeding up money movement, increasing access to capital, and making it easier to manage business operations in a central place. Fintech offers innovative products and services where outdated practices and processes offer limited options.
For example, fintech is enabling increased access to capital for business owners from diverse and varying backgrounds by leveraging alternative data to evaluate creditworthiness and risk models. This can positively impact all types of business owners, but especially those underserved by traditional financial service models.
When we look across the Intuit QuickBooks platform and the overall fintech ecosystem, we see a variety of innovations fueled by AI and data science that are helping small businesses succeed. By efficiently embedding and connecting financial services like banking, payments, and lending to help small businesses, we can reinvent how SMBs get paid and enable greater access to the vital funds they need at critical points in their journey.
Overall, we see fintech as empowering people who have been left behind by antiquated financial systems, giving them real-time insights, tips, and tools they need to turn their financial dreams into a reality.
Mahesh Kedia VP, GTM Strategy, New Market Entry and Revenue Operations, Marqeta
Innovations in payments and financial technologies have helped transform daily life for millions of people. Despite these technological advances, 22% of American adults fall in the unbanked or underbanked category (source: Federal Reserve ). People who are unbanked often rely on more expensive alternative financial products (AFPs) such as payday loans, money orders, and other expensive credit facilities that typically charge higher fees and interest rates, making it more likely that people have to dip into their savings to stay afloat. Now that more of the under/unbanked population has access to web-enabled smartphones, there are many advances in fintech that can help them access banking services. A few examples include:
Mobile wallets - The unbanked may not have traditional bank accounts but can have verified mobile wallet accounts for shopping and bill payments. Their mobile wallet identity can be used to open a virtual bank account for secure and convenient online banking.
Minimal to no-fee banking services - Fintech companies typically have much lower acquisition and operating costs than traditional financial institutions. They are then able to pass on these savings in the form of no-fee or no-minimum-balance products to their customers.
Help building credit - Some fintech companies provide a credit line to the under/unbanked against a portion of their personal savings, allowing them to build a credit history over time.This enables immigrants and other populations that may be underbanked to move up the credit lifecycle to get additional forms of credit such as auto, home and education loans, etc.
By providing access to banking services such as fee-free savings and checking accounts, remittances, credit services, and mobile payments, fintech companies can help the under/unbanked population to achieve greater financial stability and wellbeing.
Katherine Carroll, Global Head of Policy and Regulation, Stripe
Entrepreneurs from every background, in every part of the world, should be empowered to start and scale global businesses.
Most businesses still face daunting challenges with very basic matters. Incorporation. Tax. Payments. These are still very manually intensive processes, and they are barriers to entrepreneurship in the form of paperwork, PDFs, faxes, and forms. Stripe is working to solve these rather mundane and boring challenges, almost always with an application programming interface that simplifies complex processes into a few clicks.
Whether it’s making it easy for businesses to accept payments from around the world, helping anyone, anywhere incorporate correctly in a matter of hours, or tailoring loans to businesses’ needs, Stripe services are making it possible for businesses of all sizes to use the tools that formerly were reserved for big companies in big cities. Of the companies that incorporated using Stripe, 92% are outside of Silicon Valley; 28% of founders identify as a minority; 43% are first-time entrepreneurs. Stripe powers nearly half a million businesses in rural America. Collectively, they outpace urban business revenue by 30%.
The internet economy is just beginning to make a real difference for businesses of all sizes in all kinds of places. We are excited about this future.
Teddy Flo, Chief Legal Officer, Zest AI
What I believe is most important — and what we have honed in on at Zest AI — is the fact that you can’t change anything for the better if equitable access to capital isn't available for everyone. The way we make decisions on credit should be fair and inclusive and done in a way that takes into account a greater picture of a person. Lenders can better serve their borrowers with more data and better math. Zest AI has successfully built a compliant, consistent, and equitable AI-automated underwriting technology that lenders can utilize to help make their credit decisions. Through Zest AI, lenders can score underbanked borrowers that traditional scoring systems would deem as “unscorable.” We’ve proven that lenders can dig into their lower credit tier borrowers and lend to them without changing their risk tolerance.
Andrew Gray, Partner, Morgan Lewis
While artificial intelligence (AI) systems have been a tool historically used by sophisticated investors to maximize their returns, newer and more advanced AI systems will be the key innovation to democratize access to financial systems in the future. Despite privacy, ethics, and bias issues that remain to be resolved with AI systems, the good news is that as larger datasets become progressively easier to interconnect, AI and related natural language processing (NLP) technology innovations are increasingly able to equalize access. The even better news is that this democratization is taking multiple forms.
AI can be used to provide risk assessments necessary to bank those under-served or denied access. AI systems can also retrieve troves of data not used in traditional credit reports, including personal cash flow, payment applications usage, on-time utility payments, and other data buried within large datasets, to create fair and more accurate risk assessments essential to obtain credit and other financial services. By expanding credit availability to historically underserved communities, AI enables them to gain credit and build wealth.
Additionally, personalized portfolio management will become available to more people with the implementation and advancement of AI. Sophisticated financial advice and routine oversight, typically reserved for traditional investors, will allow individuals, including marginalized and low-income people, to maximize the value of their financial portfolios. Moreover, when coupled with NLP technologies, even greater democratization can result as inexperienced investors can interact with AI systems in plain English, while providing an easier interface to financial markets than existing execution tools.
John Pitts, Global Head of Policy at Plaid
Open finance technology enables millions of people to use the apps and services that they rely on to manage their financial lives – from overdraft protection, to money management, investing for retirement, or building credit. More than 8 in 10 Americans are now using digital finance tools powered by open finance. This is because consumers see something they like or want – a new choice, more options, or lower costs.
What is open finance? At its core, it is about putting consumers in control of their own data and allowing them to use it to get a better deal.
When people can easily switch to another company and bring their financial history with them, that presents real competition to legacy services and forces everyone to improve, with positive results for consumers. For example, we see the impact this is having on large players being forced to drop overdraft fees or to compete to deliver products consumers want.
We see the benefits of open finance first hand at Plaid, as we support thousands of companies, from the biggest fintechs, to startups, to large and small banks. All are building products that depend on one thing - consumers' ability to securely share their data to use different services.
Open finance has supported more inclusive, competitive financial systems for consumers and small businesses in the U.S. and across the globe – and there is room to do much more. As an example, the National Consumer Law Consumer recently put out a new report that looked at consumers providing access to their bank account data so their rent payments could inform their mortgage underwriting and help build credit. This is part of the promise of open finance.
At Plaid, we believe a consumer should have a right to their own data, and agency over that data, no matter where it sits. The CFPB's recent kick off of its 1033 rulemaking was particularly encouraging as is the agency’s commitment to strong consumer data rights and emphasis on promoting competition. This will be essential to securing benefits of open finance for consumers for many years to come.
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The SEC chair has been criticized for failing to offer regulatory clarity. But the crisis vindicates his approach to the controversial industry, others say.
Gensler and the SEC are facing a "can't-win situation."
Photo: Tom Williams/CQ-Roll Call, Inc via Getty Images
November 14, 2022
Benjamin Pimentel
Benjamin Pimentel ( @benpimentel ) covers crypto and fintech from San Francisco. He has reported on many of the biggest tech stories over the past 20 years for the San Francisco Chronicle, Dow Jones MarketWatch and Business Insider, from the dot-com crash, the rise of cloud computing, social networking and AI to the impact of the Great Recession and the COVID crisis on Silicon Valley and beyond. He can be reached at bpimentel@protocol.com or via Google Voice at (925) 307-9342.
November 14, 2022
FTX’s controversial founder, Sam Bankman-Fried, has been tagged as the main culprit for the latest crypto meltdown. But crypto industry leaders are also pointing a finger at another surprising target: Gary Gensler.
The argument goes, the SEC, under Gensler’s leadership, has done such a terrible job in providing regulatory clarity to crypto companies in the U.S. that it forces companies such as FTX to set up shop in other countries known for loose regulations — which, in turn, encouraged SBF to do really bad things.
“Part of the reason FTX was able to do what it did was because it operates in the Bahamas, a tiny island country with very little regulatory oversight and ability to oversee financial services businesses,” Coinbase CEO Brian Armstrong said in an op-ed Friday.
“Did regulators force FTX to conduct itself in the way it did? No. But they did create a situation where FTX could take dangerous risks with no repercussions.”
One wild and sinister conspiracy theory being bandied about on crypto Twitter suggests that Gensler had secret dealings with now-disgraced Bankman-Fried. Minnesota Rep. Tom Emmer , who’s been critical of Gensler, said in a tweet that his office is looking into allegations that the SEC chair was “helping SBF and FTX work on legal loopholes to obtain regulatory monopoly.”
In a tweet tagging Gensler, Ripple general counsel Stuart Alderoty also asked if the SEC chair was “acting alone when meeting with SBF? Would SBF have ended up with even more consumer assets under his control?”
No evidence has been presented to back up these allegations. The SEC did not immediately respond to requests for comment.
But the attacks on Gensler have been met with intense pushback from other industry observers who stress a different argument: The FTX crash actually proves that Gensler’s approach to crypto was correct. By embracing what the crypto industry denounced as unreasonable and rigid policies, Gensler actually minimized the harm the FTX meltdown had on U.S. consumers, they argue.
John Reed Stark , a staunch crypto critic and founding chief of the SEC’s Office of Internet Enforcement , said Gensler “saved millions, perhaps even billions, in investor crypto-losses” by taking on the industry “despite mammoth political opposition and rogue defendants with infinite financial resources.”
Marc Fagel, former SEC regional director for San Francisco who has represented crypto companies in his private practice, downplayed speculation that the SEC colluded with FTX simply because Gensler’s staff had meetings with the company.
“Plenty of players in the crypto industry have met with various members of the SEC,” Fagel told Protocol. “Indeed, I would be a little worried if the SEC didn’t take meetings with players as large as this.”
And FTX was huge: The company ran the third-largest crypto exchange after Binance and Coinbase. Like Binance, FTX is not allowed to operate in the U.S. due to regulatory restrictions, though FTX has been in the crypto lobby in Washington.
FTX and Binance are also relatively new players in the crypto industry. Binance launched in 2017, while FTX began in 2019. But their growth rates have been astronomical. Binance outpaced Coinbase, which launched 10 years ago, to emerge as crypto’s largest marketplace. FTX became the third-largest crypto exchange in just three years.
Critics argue that the rapid growth was based on a key advantage: FTX didn’t have to worry about U.S. regulations, including strict disclosure requirements. And that, critics argue, was what led to the FTX debacle.
Jonah Crane, a partner at Klaros Group, told Protocol, “the issues that took down FTX vindicate Gensler’s focus on conflicts of interest and the risks of a vertically integrated model that exists across the crypto sector.”
In fact, the whole industry is so interconnected that the FTX meltdown has inevitably affected other crypto companies and investors, including several in the U.S.
Gensler last week described crypto as “a field that’s significantly non-compliant” featuring a “very interconnected world” with “a few concentrated players in the middle.” Like the Terra-luna crash earlier this year, the FTX meltdown involved a major player with “toxic combinations of lack of disclosure, customer money, a lot of leverage, and then trying to invest with that.”
Those interconnections have enabled the contagion triggered by the FTX crash to ripple across the industry, including companies in the U.S. That’s why “there has to be unified approaches to this around the world,” Circle CEO Jeremy Allaire said.
“These are common markets,” he told Protocol. “They're deeply interconnected.”
Allaire said the U.S. Congress’ failure to pass new laws for crypto led to the tough situation that U.S. crypto companies face in the wake of the FTX crash. But he also assigned some blame to the SEC under Gensler, who has stressed that crypto companies must be more transparent through disclosures.
“We can't just say we have the rules, follow them,” he said. “What is it? That's what a lot of people have been asking for. There has to be tailored rules.”
It’s a tough bind for the SEC, which Fagel said faces “a can’t-win situation.”
“The same people shouting about the SEC’s interference in crypto markets, which they contend should not be within the SEC’s jurisdiction, are now blaming the SEC for not doing more,” he said.
“The same people who have fought hardest to keep crypto unregulated, and who made the decision to trade unregistered cryptocurrencies on a Caribbean-based exchange, are now screaming at the SEC for not protecting them. I’m not sure if that’s irony or schadenfreude.”
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AWS is 'not done building' as cloud computing matures
New ways to help enterprises exploit data are set to take center stage at re:Invent this month, the second with CEO Adam Selipsky at the helm. His goal? To help customers use the cloud to operate more efficiently and solve their business problems amid a challenging economic environment.
AWS CEO Adam Selipsky suggested that the worst of times often are the best time when it comes to enterprises investing in new services or modernizing their IT approach.
Photo: AWS
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.
November 14, 2022
AWS re:Invent starts two weeks from now, an end-of-year showcase typically reserved for the dominant cloud provider’s biggest service announcements, technology sessions, and customer success stories.
This year’s event, however, comes amid global economic pain marked by soaring prices, months of tech layoffs, and a general belt-tightening among some enterprises that includes curtailing their cloud spending. And even AWS’ own growth, while still strong, has slowed.
But CEO Adam Selipsky suggested that the worst of times often are the best time when it comes to enterprises investing in new services or modernizing their IT approach. When a challenge or crisis hits, companies that are prepared and able to move fast will gain advantage, he told Protocol in a recent interview in Boston.
“So we see a lot of customers actually leaning into their cloud journeys during these uncertain economic times,” Selipsky said. “We saw it during the pandemic in early 2020, and we're seeing it again now, which is, the benefits of the cloud only magnify in times of uncertainty.”
Amid that uncertainty, and with enterprises taking a closer look at their ROI on cloud spending, Protocol has learned that AWS is experimenting with some new approaches to billing its customers by tying its fees to whether they realize predetermined results from the cloud.
And as AWS looks to further help enterprises operate more efficiently and solve their business problems, data will be a big focus at the 11th annual session of re:Invent starting Nov. 28 in Las Vegas, along with a deeper push into industry verticals.
“Succeeding with data in today's world really requires taking the end-to-end view of your data and not looking at point solutions along the journey,” Selipsky said. “A lot of people are drowning in their data and don't know how to use it to make decisions.”
The spotlight on data brings to bear Selipsky’s experience leading Tableau Software and being immersed in the world of data, analytics, and business intelligence there for more than four years before returning to AWS last year. The amount of data available to companies continues to explode, and it's both a huge opportunity and huge problem, Selipsky told Protocol.
“I'm able to bring back a real insider's view, if you will, about where that world is heading – data, analytics, databases, machine learning, and how all those things come together,” he said. “It's not about having a point solution for a database or an analytics service, it's really about understanding the flow of data from when it comes into your organization all the way through the other end, where people are collaborating and sharing, and making decisions based on that data.”
Over the last 16 years AWS has churned out new cloud services, which now number more than 200, and Selipsky is adept at communicating how that technology can translate into better business outcomes for customers, according to Gartner distinguished analyst Ed Anderson, who focuses on the cloud services market.
“Adam has certainly … brought a leadership perspective that is really all his own, in fact, probably described best as really humanizing the AWS experience, really talking about benefits to businesses and benefits to people,” Anderson said. “It's reflective of the time in the market and then the type of buyers AWS is approaching. What the C-suite is looking for is, ‘How do I take all these capabilities and translate them into business solutions or business value outcomes?’”
AWS’ cloud conversations with customers are increasingly happening with organizations’ highest-ranking executives, rather than lower-level tech leaders. It’s a dynamic that most surprised Selipsky upon his return to AWS, where, up until 2016, he was the equivalent of AWS’ chief operating officer, a direct report to predecessor Andy Jassy and one of two senior executives in place since the cloud platform’s launch.
The change is indicative of the depth and sophistication of organizations’ use of the cloud now in every facet of their businesses — running core enterprise IT applications, tapping new analytics, and deploying end-customer applications — and how fundamental it is to their success, according to Selipsky.
“The cloud and our relationship with these enterprises is now very much a C-suite agenda,” Selipsky said. “There was a time years ago where there were not that many enterprise CEOs who were well-versed in the cloud. And then you reached the stage where they knew they had to have a cloud strategy, and they were more asking their team, their CIOs, 'OK, do we have a cloud strategy?' Now it's actually something that they're, in many cases, steeped in and involved in, and driving personally.”
While the technology is sophisticated, deploying the technology is arguably the lesser challenge compared with, how do you mold and shape the organization to best take advantage of all the benefits that the cloud is providing.
The conversation with CEOs typically focuses on organizational transformation: how customers can put data at the center of their decision-making and use the cloud to innovate more quickly and drive speed into their organizations, Selipsky said.
“Those are cultural characteristics, not technology characteristics, and those have organizational implications about how they organize and what teams they need to have,” he said. “It turns out that while the technology is sophisticated, deploying the technology is arguably the lesser challenge compared with, how do you mold and shape the organization to best take advantage of all the benefits that the cloud is providing.”
‘Not done building’
AWS’ pioneering entrance into cloud computing in 2006 and rapid pace of innovation catapulted it ahead of its subsequent cloud competitors. Today, it has an industry-leading 34% share of the cloud infrastructure services market. Microsoft follows at 21% and Google Cloud at 11% , according to the most recent data from Synergy Research Group .
There’s no one-size-fits-all solution to what customers want, Selipsky said, and that's why AWS will continue to develop products and services at all levels of its stack and fill out existing services with new features.
“We're not done building yet, and I don't know when we ever will be,” he said. “And one of our focuses now is to make sure that we're really helping customers to connect and integrate between our different services.”
Customers continue to want basic AWS building blocks — or so-called “primitives” — to operate in the cloud, according to Selipsky.
Adam Selipsky speaking at GSMA's 2022 Mobile World Congress in Barcelona
Photo: Joan Cros/NurPhoto via Getty Images
“We absolutely have customers who very much want to have their hands 'on the wheel,' if you will, and to be working with our services at the deepest layer, at the most primitive level — so EC2 for compute, S3 for storage, one or more of our database services — and they want to be interacting with those services directly,” he said. “It is interesting, and I will say somewhat surprising to me, how much basic capabilities, such as price performance of compute, are still absolutely vital to our customers.”
But AWS is also seeing more and more customers who want to interact with its cloud at a higher level of abstraction — more at the application layer or with broader solutions such as Amazon Connect, its customer contact center service, Amazon HealthLake, or IoT services to monitor industrial equipment for maintenance.
In August, Dilip Kumar , who was vice president of physical retail and technology at parent company Amazon, moved over to AWS as vice president of applications, reporting to Selipsky. While at Amazon, Kumar oversaw the development of technologies including Just Walk Out, which enables checkout-free stores, and Amazon One, a biometric identity and payment service used at Amazon stores. He also had a stint as technical adviser to Amazon founder and former CEO Jeff Bezos, which is also how Jassy rose through the Amazon ranks to become the first CEO of AWS.
“We have lots of capabilities we're building that are either for … horizontal use cases like [Amazon Connect] or industry verticals like automotive, health care, financial services,” Selipsky said. “We see more and more demand for those, so Dilip has come in to really coalesce a lot of teams' capabilities who will be focusing on those [areas]. You can expect to see us invest significantly in those areas and to come out with some really exciting innovations.”
Supporting hybrid environments
“Multicloud” might not be a term in its regular vocabulary , but Selispky said AWS is also committed to supporting customers in their hybrid infrastructure environments — which include other clouds as well as on-premises data centers — with a caveat as to where he says they’ll find the most success.
“In general, when we look across our worldwide customer base, we see time after time that the most innovation and the most efficient cost structure happens when customers choose one provider — when they're running predominantly on AWS,” Selipsky said. “[There are] a lot of benefits of scale for our customers, including the expertise that they develop on learning one stack and really getting expert , rather than dividing up their expertise and having to go back to basics on the next parallel stack.”
That said, Selipsky acknowledged many customers operate in a hybrid state, running their IT in different environments whether by choice or due to acquisitions and inherited technology.
“We understand and embrace the fact that it's a messy world in IT, and that many of our customers for years are going to have some of their resources on premises, some on AWS,” he said. “Some may have resources that run in other clouds. We want to make that entire hybrid environment as easy and as powerful for customers as possible, so we've actually invested and continue to invest very heavily in these hybrid capabilities.”
Those include visibility and management capabilities, according to Selipsky.
We understand and embrace the fact that it's a messy world in IT, and that many of our customers for years are going to have some of their resources on premises, some on AWS.
“The first thing that customers ask for is, ‘We want to be able to see and have visibility into and in some cases manage resources on AWS, on my own premises and in some cases on other clouds,’” he said. “So we've built capabilities, many of our management services, to see and in some cases control what's going on across those environments.”
Selipsky singled out Amazon EKS Anywhere as an example. It became generally available last September as a deployment option for Amazon Elastic Kubernetes Service, which allows customers to run Kubernetes on AWS without dealing with their own Kubernetes control plane or nodes.
“[EKS Anywhere is a] distribution of Kubernetes that customers can take and run on their own premises and even use to boot up resources in another public cloud and have all that be done in a consistent fashion and be able to observe and manage across all those environments,” Selipsky said. “So we're very committed to providing hybrid capabilities — including running on premises, including running in other clouds — and making the world as easy and as cost-efficient as possible for customers.”
Customer cost-cutting and experimental billing
Cost-efficiency is front and center now for some AWS customers, thanks to the state of the economy. During Amazon’s earnings call last month, chief financial officer Brian Olsavsky acknowledged an uptick in AWS customers focused on controlling costs. Customers are looking to save money versus their committed spend, and AWS is proactively working to help them cost-optimize, “just as we've done throughout AWS’ history, especially in periods of economic uncertainty,” he said.
“There are some industries that have lower demand that's showing up in our volumes,” Olsavsky said, highlighting financial services, the mortgage industry, and the cryptocurrency market. “We're very strong in some of those industries, and that's part of it.”
AWS revenue slowed in the last quarter, growing 27% year-over-year to $20.5 billion, compared with 39% growth from the same quarter a year earlier.
“We're an $82-billion-a-year company last quarter … so we have, of course, every use case and customers in every situation that you could imagine,” Selipsky said. “Some customers are doing some belt-tightening. What we see a lot of is folks just being really focused on optimizing their resources, making sure that they're shutting down resources which they're not consuming. You do see some discretionary projects which are being not canceled, but pushed out.”
AWS continues to see a strong customer appetite for signing longer-term commitments, according to Selipsky, which was part of a big push under the last several years of Jassy’s tenure as CEO.
“Many of our larger customers want to make longer-term commitments, want to have a deeper relationship with us, want the economics that come with that commitment,” he said. “But every customer is welcome to purely 'pay by the drink' and to use our services completely on demand.”
AWS has been open to renegotiating long-term contracts for customers with multiyear commitments through AWS’ Enterprise Discount Program, or EDP, according to Simon Anderson, founder and CEO of Mission Cloud Services, a managed cloud services provider and AWS consulting partner. Anderson attributes that flexibility to Amazon’s “customer obsession” leadership principle. Under an EDP, customers commit to a predetermined amount of high-volume annual AWS spending in return for contractually outlined discounts.
Fees are tied to the client realizing the benefits. If you told me you’re going to save me a million bucks, I'll pay you when I see the million bucks.
“We have renegotiated those deals,” Anderson said. “Typically they involve, as you would expect, an extension of the term of the new deal beyond the term of the old deal. For example, if someone has one year to go on their EDP, if the customer is prepared to make a forward commitment for two years or three years from that point in time, then there's definitely room to accommodate the customer’s current situation from a financial perspective.”
AWS has also been experimenting with Deloitte Consulting, its largest global systems integrator partner, on new customer contracting approaches that involve value-based billing, according to Jonathan Bauer, Deloitte’s lead U.S. AWS alliance partner.
“We're starting to talk to AWS about, and they are exploring, new contracting approaches that focus on value creation,” Bauer told Protocol. “Fees are tied to the client realizing the benefits. If you told me you’re going to save me a million bucks, I'll pay you when I see the million bucks. It's sort of like saying, do you really stand behind what you're selling. It's something that we use, and it's been enormously successful.”
Several such deals have been consummated between customers, Deloitte, and AWS, according to Bauer.
“I have good faith that we'll make some progress,” he said. “As deals get larger and larger, clients are demanding more than just 'yeah, we'll deliver it for you.’ They want some skin in the game. It's a three-way conversation. Deloitte has to make some commitments; AWS has to make some commitments that perhaps they weren't accustomed to making five years ago. That’s exactly what an environment like this needs.”
Customers ultimately care most about the value they get from AWS, according to Selipsky.
“Those benefits have been dramatic for years, as evidenced by customers’ adoption of AWS and the fact that we're still growing at the rate we are given the size business that we are,” he said. “That adoption speaks louder than any other voice.”
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