Google has announced that Android now natively supports OpenID4VP and OpenID4VCI for digital credential presentation and issuance. Digital Credentials are cryptographically verifiable documents, such as driver’s licenses, passports, or national IDs. Android apps can incorporate and submit more digital documents like education certifications, insurance policies, and permits in the near future. Currently, supported digital documents can be stored in “credential holders” apps like Google Wallet and Samsung Wallet. Users can store multiple credentials across apps using OpenID4VP requests from websites or the Android Credential Manager API. The process involves a verifier sending an OpenID4VP request to the Digital Credential API, prompting the user to select a credential. Android redirects the request to the app holding the credential, which can perform additional due diligence before releasing the credential. Google Wallet will soon allow users to use digital credentials to recover Amazon accounts, access online health services, and verify profiles or identity on platforms like Uber and Bumble.
ServiceNow’s new AI Control Tower lets AI systems administrators and other AI stakeholders monitor and manage every AI agent, model or workflow in their system
ServiceNow’s new AI Control Tower, offers a holistic view of the entire AI ecosystem. AI Control Tower acts as a “command center” to help enterprise customers govern and manage all their AI workflows, including agents and models. The AI Control Tower lets AI systems administrators and other AI stakeholders monitor and manage every AI agent, model or workflow in their system — even third-party agents. It also provides end-to-end lifecycle management, real-time reporting for different metrics, and embedded compliance and AI governance. The idea around AI Control Tower is to give users a central location to see where all of the AI in the enterprise is. “I can go to a single place to see all the AI systems, how many were onboarded or are currently deployed, which ones are an AI agent or classic machine learning,” said Dorit Zilbershot, ServiceNow’s Group Vice President of AI Experiences and Innovation. “I could be managing these in a single place, making sure that I have full governance and understanding of what’s going on across my enterprise.” She added that the platform helps users “really drill down to understand the different systems by the provider and by type,” to understand risk and compliance better. The company’s agent library allows customers to choose the agent that best fits their workflows, and it has built-in orchestration features to help manage agent actions. ServiceNow also unveiled its AI Agent Fabric, a way for its agent to communicate with other agents or tools. Zilbershot said ServiceNow will still support other protocols and will continue working with other companies to develop standards for agentic communication.
Fifth Third Bank is surprising families with babies born at certain hospitals in Detroit on May 3 with a special voucher to open a college savings account
Fifth Third Bank announced that it is surprising families with babies born at certain hospitals in Detroit on May 3 with a special voucher to open a college savings account. Each year, Fifth Third celebrates May 3 (5/3) with community service and giving activities. According to the bank, this year, they are bringing the program to Detroit and partnering with the hospitals affiliated with Henry Ford Health, Detroit Medical Center and McLaren Health. The families that have babies born on May 3 will receive a $1,053 voucher for a 529 College Savings Plan, a DoorDash gift card and baby gifts, the bank says. Local labor and delivery nurses will also receive gifts. The bank will also do the giveaways at hospitals in Fort Myers and Naples, Florida.
Gyan is an alternative AI architecture built on a neuro-symbolic architecture, not transformer based, to create hallucination-free models by design
Gyan is a fundamentally new AI architecture built for Enterprises with low or zero tolerance for hallucinations, IP risks, or energy-hungry models. Gyan gives businesses full control over their data, keeping it private and secure — making it the trusted partner for enterprises in situations where reliability and accuracy are mandatory. Unlike with LLM’s, with Gyan, businesses can use an AI model without worrying about it making things up. Built on a neuro-symbolic architecture, not transformer based, Gyan is a ground-up hallucination-free model by design. “If the cost of a mistake is high, you certainly don’t want your AI causing it,” says Joy Dasgupta, CEO, at Gyan. “We built Gyan for companies and processes with zero tolerance for hallucination and privacy risks, with compute and energy requirements orders of magnitude lower than that of current LLM’s.” Gyan’s State of the Art performance in two key life sciences benchmarks (PubMedQA and MMLU) is proof of efficacy of its language model. Every inference by Gyan is traceable with full reasoning to exact ideas and arguments in the result, making them readily verifiable. This is not the case for any of the others on the Leaderboard. Gyan provides precise and accurate analysis which users can depend on.
OpenAI’s Shopify partnership to make online shopping a more personalized experience direct integration of product details, pricing and ‘Buy Now’ button into the UI
OpenAI’s integration with Shopify is expected to revolutionize online shopping, transforming the internet into a more personalized experience. The integration will allow digital personal shoppers to know customers’ size, style, and preferences, allowing them to make more informed decisions about their purchases. This could lead to a shift from traditional storefronts to full-service consultants and lifestyle experts. The adoption of Gen AI will result in lower return rates, reduced bounce rates, and a rise in’shopper loyalty’ as consumers build an affinity with stores that make their lives easier and feel special. To optimize the integration, brands should focus on user-generated content, build a real community, and train their assistants cleverly. The partnership between OpenAI and Shopify could mark an unprecedented step forward in using Gen AI as a shopping tool. By integrating product details, pricing, reviews, and even a ‘Buy Now’ button directly into the UI, the future of online shopping will be significantly changed. The winners will be those that think beyond the transaction and create experiences that feel truly personal.
Morgan Stanley research shows Apple Intelligence platform has been downloaded and engaged with by 80% of eligible U.S. iPhone owners in the last six months and has an above average NPS of 53
Consumers’ perception of Apple’s AI platform is more favorable than that of investors, Morgan Stanley said in a research note. Morgan Stanley said it found that the Apple Intelligence platform has been downloaded and engaged with by 80% of eligible U.S. iPhone owners in the last six months, has an above average net promoter score of 53, and is characterized by iPhone users as “easy to use, innovative, and something that improves their user experience.” “While much of the public critique of Apple Intelligence is warranted, and investor sentiment and expectations on Apple’s AI platform couldn’t be lower, our survey of iPhone owners paints a more positive picture,” Morgan Stanley said in the note. Since September, the share of iPhone owners who believe it is extremely or very important to have Apple Intelligence support on their next iPhone rose 15 points to reach 42%. Among iPhone owners who are likely to upgrade their device in the next 12 months, the percentage saying that about the AI platform rose 20 points to reach 54%, according to the note. Morgan Stanley also found that consumers are willing to pay more for Apple Intelligence than they were in September. Those who have used the AI platform are now willing to pay an average of $9.11 per month for it, a figure that’s 11% higher than the $8.17 average seen in September, per the note. While we don’t expect Apple to put Apple Intelligence behind a paywall until the platform is more built out, the potential long-term monetization of an Apple Intelligence subscription could reach tens of billions of dollars annually when considering a 1.4B global iPhone installed base, 32% (and growing) of US iPhone owners have an Apple Intelligence support iPhone, and users are willing to pay up to $9.11/month for Apple Intelligence,” Morgan Stanley said in the note.
Upwind’s ML cloud platform collects multi-layer telemetry data of the networking stack for real-time detection of threats to APIs, enabling 7X reduction in the mean time to respond
Upwind has added a feature to its cloud application detection and response (CADR) platform, allowing real-time detection of threats to application programming interfaces (APIs). The platform uses machine learning algorithms to collect telemetry data from Layers 3, 4, and 7 of the networking stack, enabling the identification of deviations and anomalous behavior in API traffic. The goal is to reduce the time required to investigate API security incidents by up to 10 times and mean time to response times by up to seven times. In the age of generative artificial intelligence (AI), there is a growing focus on API security. Many organizations are discovering that sensitive data is being shared inadvertently with AI models. Historically, responsibility for securing APIs has been unclear, with many cybersecurity teams assuming that application development teams are securing them as they are developed. However, this can lead to thousands of APIs that cybercriminals can exploit to exfiltrate data or modify business logic. Over the next 12-18 months, organizations plan to increase software security spend on APIs, DevOps toolchains, incident response, open source software, software bill of materials, and software composition analysis tools. Advancements in AI and eBPF technologies could simplify the entire software development lifecycle by streamlining the collection and analysis of telemetry data.
Data governance platform Relyance AI allows organizations to precisely detect bias by examining not just the immediate dataset used to train a model, but by tracing the potential bias to its source
Relyance AI, a data governance platform provider that secured $32.1 million in Series B funding last October, is launching a new solution aimed at solving one of the most pressing challenges in enterprise AI adoption: understanding exactly how data moves through complex systems. The company’s new Data Journeys platform addresses a critical blind spot for organizations implementing AI — tracking not just where data resides, but how and why it’s being used across applications, cloud services, and third-party systems. Data Journeys provides comprehensive view, showing the complete data lifecycle from original collection through every transformation and use case. The system starts with code analysis rather than simply connecting to data repositories, giving it context about why data is being processed in specific ways. Data Journeys delivers value in four critical areas: First, compliance and risk management: The platform enables organizations to prove the integrity of their data practices when facing regulatory scrutiny. Second, precise bias detection: Rather than just examining the immediate dataset used to train a model, companies can trace potential bias to its source. Third, explainability and accountability: For high-stakes AI decisions like loan approvals or medical diagnoses, understanding the complete data provenance becomes essential. Finally, regulatory compliance: The platform provides a “mathematical proof point” that companies are using data appropriately, helping them navigate increasingly complex global regulations. Customers have seen 70-80% time savings in compliance documentation and evidence gathering.
Alacriti’s next-gen ACH solution provides a unified payments infrastructure to process wires and real-time payments through multiple rails while allowing configurable exception handling, posting and settlement
Alacriti has launched its enhanced version of Orbipay Payments Hub for ACH, bringing automation-first design and intelligent processing to the ACH payment lifecycle. By incorporating automation, intelligent routing, and real-time insights, Orbipay Payments Hub for ACH helps financial institutions reduce processing costs, improve transaction accuracy, and enhance customer experiences while maintaining compliance with Nacha operating rules and regulatory standards. This modern ACH processing solution provides seamless integration with the Federal Reserve’s clearing systems, supporting a full range of ACH transactions, including consumer payments, corporate disbursements, bill payments, and Same Day ACH. Designed with advanced automation, configurable exception handling, and embedded compliance tools, Orbipay Payments Hub for ACH helps financial institutions modernize operations and gain full visibility of their ACH performance while keeping their existing core banking systems or without changing their other existing systems. Beyond ACH, Orbipay Payments Hub provides a unified payments infrastructure to process wires and real-time payments through the RTP® network, the FedNow Service, and Visa Direct. By bringing these payment rails together under a single platform, financial institutions can optimize, report, and manage their operations today while preparing for future payment innovations. Key Features and Benefits of Orbipay Payments Hub for ACH: Automated exception handling, Seamless ecosystem integration, Configurable posting and settlement , Advanced fraud prevention and compliance, and Unified reporting and analytics.
Affirm expands beyond Experian to begin reporting all its pay-over-time loans to TransUnion but transactions will not be factored into traditional credit scores nor visible to lenders in the near-term
Affirm is expanding the credit reporting of its pay-over-time products to TransUnion. All Affirm pay-over-time loans issued from May 1, 2025 onward, including Pay in 4 and longer-term monthly installments, will be reported to TransUnion. Consumers will see details about all Affirm transactions on their TransUnion credit files, though these transactions will not be factored into traditional credit scores nor visible to lenders in the near-term. As more pay-over-time providers report account information to the credit bureaus, lenders who request TransUnion credit reports will also be able to view consumers’ pay-over-time history. In the future, as new credit scoring models are developed, this information may factor into consumers’ scores, with the aim of supporting more informed lending decisions and helping consumers build their credit histories. TransUnion research found nearly 40% of consumers who haven’t used buy now, pay later are likely or very likely to use them in the future. Notably, a higher 53% of non-users would be likely or very likely to use them if it had the potential to have a positive impact on credit scores.