Monday, January 13, 2020

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Inside of each of our services – you can pick any example – we're just adding new capabilities all the time. One of our focuses now is to make sure that we're really helping customers to connect and integrate between our different services. So those kinds of capabilities — both building new services, deepening our feature set within existing services, and integrating across our services – are all really important areas that we'll continue to invest in. 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. Fintech puts American consumers at the center of their finances and helps them manage their money responsibly.

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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.

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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. In other cases, just the fact that we have things like our Graviton processors and … run such large capabilities across multiple customers, our use of resources is so much more efficient than others.

We talked about Connect, our contact center solution, and we've also built services specifically for the healthcare industry like a data lake for healthcare records called HealthLake. We've built a lot of industrial services like IoT services for industrial settings, for example, to monitor industrial equipment to understand when it needs preventive maintenance. We have a lot of capabilities we're building that are either for … horizontal use cases like or industry verticals like automotive, healthcare, financial services. We see more and more demand for those, and Dilip has come in to really coalesce a lot of teams' capabilities, who will be focusing on those . You can expect to see us invest significantly in those areas and to come out with some really exciting innovations.

Teddy Flo, Chief Legal Officer, Zest AI

If you'd asked me 15 years ago, “hey in 2022, how much of the cutting edge of innovation do you think would be around raw performance or price performance of a unit of compute,” I wouldn't have necessarily guessed that was still as important as it is. Part of that is because of the size of datasets and because of the machine learning capabilities which are now being created. They require vast amounts of compute, but nobody will be able to do that compute unless we keep dramatically improving the price performance. The conversation that I most end up having with CEOs is about organizational transformation. It is about how they can put data at the center of their decision-making in a way that most organizations have never actually done in their history.

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That way, in the Obama administration’s view, the agency could avoid political influence and be funded similarly to other banking regulators. But Republicans have chafed at what they view as anti-business practices and a lack of oversight. The important thing for our customers is the value we provide them compared to what they're used to.

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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. 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. 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.

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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. 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. 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. 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.

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And it's about using the cloud to innovate more quickly and to drive speed into their organizations. Those are cultural characteristics, not technology characteristics, and those have organizational implications about how they organize and what teams they need to have. 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.

For instance, Hollman said the company built an ML feature management platform from the ground up. 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. 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.

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Attorney’s office in Washington, D.C., that called themselves the “Bitcoin Strikeforce,” and worked with agencies like the IRS and FBI in federal investigations. There, Faruqui prosecuted cases that involved terrorism, child pornography, and weapons proliferation. Particularly well known was a case involving a dark-web site called “Welcome to Video,” which had facilitated some 360,000 downloads of sexually exploitative videos of children to 1.28 million members worldwide using bitcoin.

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But of course, 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. We're signing more long-term commitments than ever these days. Now's the time to lean into the cloud more than ever, precisely because of the uncertainty. 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. But cost-cutting is a reality for many customers given the worldwide economic turmoil, and AWS has seen an increase in customers looking to control their cloud spending. 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.

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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. That being said, many customers are in a hybrid state, where they run IT in different environments.

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