Chime has filed a registration statement on Form S-1 with the U.S. Securities and Exchange Commission relating to the proposed initial public offering of its Class A common stock. Chime has applied to list its Class A common stock on the Nasdaq Global Select Market under the ticker symbol “CHYM.” The number of shares to be offered and the price range for the proposed offering have not yet been determined. Morgan Stanley, Goldman Sachs & Co. LLC and J.P. Morgan will act as lead book-running managers for the proposed offering. Barclays will act as an additional book-running manager. In its Form S-1, Chime said it addresses “the most critical financial needs of everyday Americans,” including spending, liquidity, credit building, savings, community, support and safety. The company added that it has 8.6 million active members, up 82% since the first quarter of 2022, and that 67% of these active members use Chime as their primary account relationship. It noted that it is a technology company, not a bank, and that its bank partners provide its FDIC-insured accounts. “Looking ahead, with less than 5% adoption in our core target market, we see an enormous opportunity to grow for years to come,” Chime Co-Founder and CEO Chris Britt and Co-Founder Ryan King wrote in the Form S-1.
Goldman Sachs to roll out AI Assistant to all its workforce to serve as backbone of other such tools- Banker Copilot, Legend AI Query, Legend Copilot and Translate AI
Goldman Sachs has been building out its generative AI toolkit. The firm aims to release one of its tools, an AI assistant, to most staff this year. Here’s a look at five such tools — the promise of what they can do, plus who’s using them and how.
- GS AI Assistant. What it does: Goldman Sachs’ in-house version of ChatGPT. Think of the GS AI Assistant as a sidekick for Goldman employees. It uses a chat interface, similar to that of ChatGPT, but can pull its responses from the bank’s confidential data repository. Right now, it’s available to about 10,000 workers; the firm is intending to get it in the hands of the rest of the bank’s workforce of over 46,000 by the end of the year. It can perform a variety of functions, helping executives draft presentations and plan off-site meetings, or serving as a “personal tutor” for quant strategists.
- Banker Copilot. What it does: Streamlines some aspects of investment bankers’ jobs. Members of Goldman’s investment banking division are also set to get an AI boost with the bank’s so-called banker copilot, which makes access to high-level, protected data about matters like deal-making available to eligible users. Only a small group numbering in the dozens has access to it right now since it’s in the early stages of development. But the promise of what the AI assistant could represent for the banking business is hard to deny. Solomon himself has acknowledged the potential for AI to automate large chunks of tedious processes, like drafting S-1 regulatory disclosures for initial public offerings, for instance.
- Legend AI Query: What it does: A search tool that uses AI to navigate the bank’s vast repository of data. Goldman uses Legend, an open-source data management and governance platform. Accessing Goldman’s vast vault of knowledge used to require users to know what they were looking for — as well as where they were looking — ahead of time, using a tool called “Legend Query.” Think of this process as being like perusing dozens of stacks in a library, but without a librarian to help. Enter Legend AI Query, a query tool that saves time by tapping artificial intelligence to serve as that librarian.
- Legend Copilot. What it does: A fast-tracked way to upload data onto Legend, and keep the system organized. Legend Copilot, which launched in October, is a tool primarily designed for use by data engineers to maintain Legend’s infrastructure, and keep its information streams organized for others to access. Legend draws on data that originates in other databases, but still needs to be routed into the centralized Legend system.
- Translate AI: What it does: In-house language translation to and from English. As a global bank, Goldman Sachs has clients worldwide. Sometimes, those clients have a preferred language that’s not English. To reach clients in their non-English speaking language, the bank would historically outsource some of this translation work, but turnaround times could stretch into days.
Vanguard is deploying agentic AI that let users pull data from databases in natural language and conduct data lineage checks, which avoids a costly undertaking
Ryan Swann, Vanguard’s chief data analytics officer says the mutual fund giant is using data and AI not only to gain insight, but also to build enterprise-wide agility and accelerate value creation for itself and its clients. Data and analytics have a seat at the C-suite table at Vanguard, a shift that Swann said enables the company to embed intelligence into decision-making at all levels. “It is allowing us to bring insights to all of our executives about what’s happening with our clients. “It allows us to inform and influence the strategy and what we should focus on next. It also allows us to accelerate our business strategy. We’re a digital organization; we don’t have bricks and mortar, so the majority of our clients interact with us through data, through transactions, through clicking around on our website, maybe calling our call center, which is just another type of unstructured data. That data allows us to understand what our clients need and how we should respond,” the executive said. Swann’s office oversees the entire data lifecycle — from engineering and management to advanced analytics, machine learning and behavioral science. Central to Swann’s approach is a hub-and-spoke model that bridges the technical and business sides of the company. To foster cross-functional collaboration, Swann said sitting together and sharing the same objectives and key results (OKRs) matter. For example, Swann said an AI model could look through the data to coach the sales team into performing better. It could recommend the three best actions to take, the next three people to talk to, and the three topics they should talk to them about. By A/B testing these recommendations, the team tracked the performance improvements and worked with finance to quantify the gains. These and other initiatives have brought value to Vanguard. “Last year alone, we were up over $300 million of incremental value” across revenue generation, cost efficiencies, cost avoidance and risk reduction, he said. As for agentic AI, Vanguard is deploying agents that let users do things like pull data from databases in natural language and conduct data lineage checks, which avoids a costly undertaking. Swann said Vanguard has data processes going back decades, and the company must now create lineage to trace where the data comes from and where it goes.
Fed’s latest Diary of Consumer Payment Choice reveals consumers made an average of 11 payments per month with a mobile phone in 2024, up from four payments in 2018; cash remains a key backup payment method
Federal Reserve Financial Services today issued the 2025 Diary of Consumer Payment Choice (Diary), an annual survey measuring the evolving role of cash in the U.S. economy. Findings from this nationally representative survey showed that amid the increasing digitalization of payments, consumers continue to use cash and keep it handy. Cash ranked third as a top payment instrument among consumers, a position it has held for the past five years. In 2024, it accounted for 14% of consumer payments by number, while credit and debit cards accounted for 35% and 30% of payments, respectively. Overall, U.S. consumers made an average of 48 payments per month, continuing an upward trend that began in 2021. In 2024, this growth in the overall number of payments was driven by increased credit card usage, remote payments and payments made with mobile phones. The survey also revealed generational and demographic trends in payments. Households earning less than $25,000 per year and adults 55 and older relied more on cash than other cohorts. In contrast, adults aged 18 to 24 were more likely to pay with a mobile phone, using their phones for 45% of all payments. Other key findings included:
- S. consumers made an average of 11 payments per month with a mobile phone in 2024, up from four payments in 2018.
- Cash remains a key backup payment method for U.S. consumers. Of all cash payments in 2024, nearly two-thirds were made by consumers who prefer other payment methods, such as debit or credit cards.
- Nearly 80% of U.S. consumers have held cash in their pockets, purses or wallets for at least one day of the month for each Diary survey conducted since 2018. Though the value of these holdings has decreased since 2022, it remained elevated in 2024 compared to pre-pandemic levels.
- More than 90% of U.S. consumers intend to use cash as either a means of payment or store of value in the future.
MCP’s ability to let enterprises custom-configure servers for autonomous AI agents, its directionality to access information on client side and interoperability is spurring adoption in AI development workflows
Anthropic released Model Context Protocol (MCP) seems to have become the winning protocol choice for the AI industry. Despite the number of companies announcing MCP servers, MCP is technically not a standard. But many see MCP as one of the main protocols, if not the potential winner, for the agentic ecosystem. A lot of MCP’s attractiveness comes from streamlining how models interact with data and tools. Before MCP, developers pointed models and agents to data with APIs. However, APIs are imperfect connectors, especially for agents that access data to complete tasks automatically. Unlike APIs, organizations can configure their MCP servers with custom instructions laying out what agents can or cannot access. The server can “ask” an agent for its identity and determine if it can tap information on the MCP client side. Companies have more of a say on what outside agents can access on their end, giving MCP more directionality from the enterprise. Sagar Batchu, co-founder and CEO of API tooling company Speakeasy, said MCP transforms the work interface and API to a chat interface. He said MCP makes it so Speakeasy and its customers don’t need to rewrite or manually maintain APIs constantly. Yaniv Even Haim, chief technology officer of website builder Wix, told that MCP aligns with the company’s goals because it believes MCP can act as a “bridge” for its AI development workflows. “Wix chose the MCP model in particular because it aligns with the industry’s shift toward LLM-powered development, where context-rich, intelligent interfaces are key,” Haim said. For many companies, MCP will be one of many protocols they support as their customers decide which interoperability and agent communication methods to use. The growing adoption of MCP, for the varied reasons many companies have, proves that demand for standards is only growing.
Adoption of developer-focused AI tools surging at the expense of , freelance platforms such as Fiverr and Upwork; AI writing tools, crowdsourcing and search are fading fast
A new report released by the publicly traded market research and intelligence firm SimilarWeb—covering global web traffic patterns for AI-related platforms for 12 weeks through May 9, 2025—offers a helpful look for enterprises and interested users into the current landscape of generative AI usage online. Using proprietary analytics based on site visits, the report tracks trends across sectors including general-purpose AI tools, coding assistants, content generators, and more. Here are five key findings from the report: 1) Usage of developer AI and coding tools is rising fast: Developer-focused AI tools are surging in adoption, with traffic to the category up 75% over the past 12 weeks. That growth includes Lovable, which exploded with a jaw-dropping +17,600% spike, and Cursor, which grew steadily month over month. 2) We all know DeepSeek had a moment earlier this year — but so did Grok — and now both have fallen back into low plateaus: Grok traffic skyrocketed more than 1,000,000% in March—driven by its branding as an uncensored yet powerfully intelligent platform and Elon Musk association—before falling more than 5,200% by early May. DeepSeek saw a similar arc, peaking at +17,701% growth before crashing -41%. The takeaway: virality can’t replace retention, especially compared to AI leader OpenAI and also legacy tech brand Google. 3) AI writing tools are fading fast: Category traffic fell 11% overall, with platforms like Wordtune (-35%), Jasper (-19%), and Rytr (-23%) all trending downward. Only Originality.ai bucked the trend with steady traffic gains, likely due to its focus on AI detection rather than generation. This plateau suggests content saturation and possibly growing skepticism over quality or usefulness. 4) AI image generators and design tools show extreme volatility: Design-focused AI remains a mixed bag. While overall category usage dipped slightly (-6% over the 12-week window), some platforms made outsized gains. The erratic pattern may reflect a crowded landscape of tools that offer similar functionality but compete on novelty or aesthetics. 5) AI is eating up legacy tech such as crowdsourcing and search: Freelance platforms such as Fiverr (-17%) and Upwork (-19%) are losing traffic, possibly as users turn to AI tools for tasks like design, writing, and code. Search engines such as Yahoo (-12%) and Bing (-14%) continue a multi-quarter drop in visits, while consumer EdTech companies like Chegg (-62%) and CourseHero (-68%) are in free fall. The signs point to early-stage AI disruption beginning to erode the utility of some legacy platforms. It also offers a hint to enterprises that either leverage or create such services — the time may be coming to reduce dependency on them, either from a revenue generation, marketing, or overall business perspective.
Boomi and AWS partner to offer a centralized management solution for deploying, monitoring, and governing AI agents across hybrid and multi-cloud environments with built-in support for MCP via a single API
Boomi announced a multi-year Strategic Collaboration Agreement (SCA) with AWS to help customers build, manage, monitor and govern Gen AI agents across enterprise operations. Additionally, the SCA will aim to help customers accelerate SAP migrations from on-premises to AWS. By integrating Amazon Bedrock with the Boomi Agent Control Tower, a centralized management solution for deploying, monitoring, and governing AI agents across hybrid and multi-cloud environments, customers can easily discover, build, and manage agents executing in their AWS accounts, while also maintaining visibility and control over agents running in other cloud provider or third-party environments. Through a single API, Amazon Bedrock provides a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI in mind, including support for Model Context Protocol (MCP), a new open standard that enables developers to build secure, two-way connections between their data and AI-powered tools. MCP enables agents to effectively interpret and work with ERP data while complying with data governance and security requirements. Steve Lucas, Chairman and CEO at Boomi. “By integrating Amazon Bedrock’s powerful generative AI capabilities with Boomi’s Agent Control Tower, we’re giving organizations unprecedented visibility and control across their entire AI ecosystem while simultaneously accelerating their critical SAP workload migrations to AWS. This partnership enables enterprises to confidently scale their AI initiatives with the security, compliance, and operational excellence their business demands.” Apart from Agent Control Tower, the collaboration will introduce several strategic joint initiatives, including: Enhanced Agent Designer; and New Native AWS Connectors and Boomi for SAP.
Apple Vision Pro’s brain interface could leapfrog Neuralink; non-invasive methods could accelerate mainstream adoption of neural interfaces
Apple is developing brain-computer interface (BCI) capabilities that would allow users to control their Apple Vision Pro headset using only their thoughts. This is one of the most significant advances in Apple’s human-computer interaction strategy since the introduction of touch screens on the original iPhone. The technology would use external sensors to detect and interpret neural signals, allowing users to navigate the Vision Pro interface through mental commands. Apple is preparing to launch mind control support for its spatial computing device, though the timeline remains uncertain. The implications extend beyond the Vision Pro, as the same technology could eventually be applied to iPhones and other Apple devices. Apple is implementing strict data protections to ensure the security and privacy of neural data. The development puts Apple in direct competition with companies like Neuralink and Meta, but its focus on non-invasive methods could accelerate mainstream adoption of neural interfaces.
DoorDash expands Wing drone delivery to Charlotte, N.C. partnering Alphabet, Panera Bread and local restaurant
DoorDash is introducing drone delivery to Charlotte, N.C. for the first time. Starting Wednesday, May 14, 2025, eligible DoorDash customers within about four miles of The Arboretum Shopping Center in southern Charlotte can order from a selection of local and national restaurants and choose to have their items delivered by a drone from Wing, the on-demand drone delivery provider supported by Google parent company Alphabet. Participating restaurants include Panera Bread, the city’s first national partner available for drone delivery, as well as local banners such as Curry Junction, Matcha Cafe Maiko, and Joa Korean food. In addition to food delivery, Charlotte residents in select locations can now obtain drone delivery from DashMart by Drone, a specialized offering of the DoorDash DashMart banner which operates online storefronts with inventory provided by third-party partners. Eligible residents browsing the DoorDash app can tap the “Drone” icon on the homepage to browse restaurants eligible for drone delivery. If the items they choose meet the size and weight criteria, shoppers will have the option to select drone delivery during checkout. After confirming their delivery location, they will receive live tracking updates as the drone approaches. Charlotte consumers who aren’t currently eligible can join the waitlist to be notified when drone delivery expands to their neighborhood.
Tensor9 helps vendors deploy their software into any environment using digital twins to help with remote monitoring
Tensor9 looks to help software companies land more enterprise customers by helping them deploy their software directly into a customer’s tech stack. Tensor9 converts a software vendor’s code into the format needed to deploy into their customer’s tech environment. Tensor9 then makes a digital twin of the deployed software, or a miniaturized model of the deployed software’s infrastructure, so Tensor9’s customers can monitor how the software is working in their customer’s environment. Tensor9 can help companies deploy into any premise ranging from cloud to bare metal servers. Michael Ten-Pow, Tensor9’s co-founder and CEO, told TechCrunch that Tensor9’s ability to transfer software to any premise, and its use of digital twin technology to help with remote monitoring, helps Tensor9 stand out from other companies, like Octopus Deploy or Nuon, that also help companies deploy software into a customer’s environment. He said the timing is right for Tensor9’s tech due to tailwinds from the rise of AI. “An enterprise search vendor might go to, let’s say, J.P. Morgan and say, ‘hey, I need access to all your six petabytes of data to build an intelligent search layer on top of it so that your internal employees can have a conversation with their company’s data,’ there’s no way that’s going to work,” Ten-Pow said. “We have a simple model but underneath the covers there’s a lot of complexity that makes that happen, hard technical challenges that we’ve solved to make that happen,” Ten-Pow said.