Collibra survey found that 86% of respondents cite protecting data privacy as a top concern with 76% of respondents citing ROI on data privacy and AI initiatives across their organization. Notably, eight in 10 decision makers also said that data ownership has changed over the last year with the emergence of AI (85%). Despite concerns around data privacy and ROI, the survey indicates a strong overall momentum towards AI adoption, with 86% of organizations planning to proceed with their AI initiatives. However, this enthusiasm varies by company size. While nearly all large companies (96%) intend to forge ahead with their AI plans despite the evolving landscape, smaller (78%) and medium-sized (79%) organizations are exhibiting a more measured approach. On a positive note, the new survey also found that nearly nine in 10 decision-makers say that they have a lot or a great deal of trust in their own companies’ approach [88%] to shaping the future of AI , with three quarters [75%] agreeing that their company prioritizes AI training and upskilling, with decision-makers at large companies (1000+ employees) more likely than those at small companies (1-99 employees) to agree (87% vs. 55%).
Postman’s agent framework enables developers to build AI agents by discovering the right APIs and LLMs, evaluating them across providers and testing them, and keeping them running reliably
In this exclusive episode of DEMO, Keith Shaw discusses the platform Postman, the world’s leading API collaboration platform. Postman is designed for developers and enterprises to build intelligent AI agents, simplifying the agent-building process, reducing platform sprawl, and unlocking the full potential of APIs and large language models. One key benefit of Postman is its suite to discover the right APIs and LLMs to use in agents, allowing users to test functionality, integrate, and build through the Flows experience all in one platform. Postman leverages internal APIs and connects to hundreds of thousands of public APIs, enabling agents to access tools like Slack, Notion, UPS, and more. The agent framework involves building agents, discovering APIs and models, evaluating and testing them, and keeping them running reliably. Postman’s core workspace includes a made-up company called ShelfWise, which stores all APIs used by the company. Postman supports multiple protocols like HTTP, GraphQL, and gRPC, and has introduced a new request type: LLMs. With the rise of AI, Postman offers options like OpenAI, Google, and Anthropic. Postman also allows users to evaluate multiple models across providers using a collection runner, which can be run manually or integrated into their CI/CD pipeline. It also provides visualization tools to help teams make smarter decisions. Postman AI Agent Builder is available on postman.com, where users can find collections, examples, and Flows to fork and use right away.
Apple and Anthropic are building AI-powered coding platform that generates code through a chat interface, tests user interfaces and manages the process of finding and fixing bugs
Apple and Anthropic have reportedly partnered to create a platform that will use AI to write, edit and test code for programmers. Apple has started rolling out the coding software to its own engineers. The company hasn’t decided whether to make it available to third-party app developers. The tool generates code or alterations in response to requests made by programmers through a chat interface. It also tests user interfaces and manages the process of finding and fixing bugs. Amazon, Meta, Google and several startups have also built AI assistants for writing and editing code. McKinsey said in 2023 that AI could boost the productivity of software engineering by 20% to 45%. This increased efficiency has far-reaching implications for businesses across industries, CPO and CTO Bob Rogers of Oii.ai told. AI-powered tools enable developers to create software and applications faster and with fewer resources. “Simple tasks such as building landing pages, basic website design, report generation, etc., can all be done with AI, freeing up time for programmers to focus on less tedious, more complex tasks,” Rogers said. “It’s important to remember that while generative AI can augment skills and help folks learn to code, it cannot yet directly replace programmers — someone still needs to design the system.”
StarTree integrates Model Context Protocol (MCP) support to its data platform to allow AI agents to dynamically analyze live, structured enterprise data and make micro-decisions in real time
StarTree announced two new powerful AI-native innovations to its real-time data platform for enterprise workloads: Model Context Protocol (MCP) support: MCP is a standardized way for AI applications to connect with and interact with external data sources and tools. It allows Large Language Models (LLMs) to access real-time insights in StarTree in order to take actions beyond their built-in knowledge. Vector Auto Embedding: Simplifies and accelerates the vector embedding generation and ingestion for real-time RAG use cases based on Amazon Bedrock. These capabilities enable StarTree to power agent-facing applications, real-time Retrieval-Augmented Generation (RAG), and conversational querying at the speed, freshness, and scale enterprise AI systems demand. The StarTree platform now supports: 1) Agent-Facing Applications: By supporting the emerging Model Context Protocol (MCP), StarTree allows AI agents to dynamically analyze live, structured enterprise data. With StarTree’s high-concurrency architecture, enterprises can support millions of autonomous agents making micro-decisions in real time—whether optimizing delivery routes, adjusting pricing, or preventing service disruptions. 2) Conversational Querying: MCP simplifies and standardizes the integration between LLMs and databases, making natural language to SQL (NL2SQL) far easier and less brittle to deploy. Enterprises can now empower users to ask questions via voice or text and receive instant answers, with each question building on the last. This kind of seamless, conversational flow requires not just language understanding, but a data platform that can deliver real-time responses with context. 3) Real-Time RAG: StarTree’s new vector auto embedding enables pluggable vector embedding models to streamline the continuous flow of data from source to embedding creation to ingestion. This simplifies the deployment of Retrieval-Augmented Generation pipelines, making it easier to build and scale AI-driven use cases like financial market monitoring and system observability—without complex, stitched-together workflows.
Apple Pay’s integration with Mesh to enable merchants to accept stablecoin payments without building their own crypto infrastructure through a plug-and-play solution
Mesh, the first truly global crypto payments network, today unveiled its Apple Pay integration live on stage at Token2049 during Co-Founder and CEO Bam Azizi’s keynote address. This marks the first public demonstration of the new capability – available later in Q2 – that will enable merchants partnered with Mesh to accept crypto payments through Apple Pay without building their own crypto infrastructure. The new Apple Pay integration leverages Mesh’s proprietary SmartFunding technology, which allows users to pay with the crypto of their choice, such as BTC, ETH, or SOL, while merchants settle in the stablecoin of their choice, such as USDC, USDT, PYUSD, and others. Breaking down this inherent misalignment of incentives between consumers and merchants topples the largest barrier preventing crypto payments from becoming a mass market product to date. Users simply select the Apple Pay option at checkout, authenticate with Face ID, and complete the transaction as they would with any fiat payment. “We believe that as soon as crypto payments are as seamless as fiat payments, nothing is left to stop the mass migration of global commerce onto blockchain rails. Crypto already offers countless benefits over fiat, and Mesh is solving the UX and convenience pieces,” said Bam Azizi, CEO and Co-Founder of Mesh. “With our Apple Pay integration, we’re solving crypto’s existential last-mile problem, bringing to life a plug-and-play solution that turns on global crypto payments through our existing partners.” As demonstrated live moments ago by Azizi, Merchants with physical retail locations will now be able to leverage Apple Pay’s NFC capabilities, offering customers the same frictionless experience in-store as they experience online. And this innovation isn’t limited to point-of-sale terminals – it extends to e-commerce, too. Mesh’s latest innovation comes on the heels of its $82 million Series B fundraise, led by Paradigm, with participation from Consensys, QuantumLight Capital, Yolo Investments, and others. With over 300 integrations – including Coinbase, Binance, MetaMask, Phantom, and more – Mesh’s infrastructure ensures broad access and seamless connectivity across the crypto payments ecosystem.
Rain to offer closed loop financing utilizing stablecoins by fully tokenizing its credit card receivables to lower the total cost of capital and need for collateral for fintechs
Rain, a global card issuing platform built for stablecoins, has joined Visa’s pilot program for stablecoin settlement. Rain has fully tokenized its credit card receivables and has transitioned all settlement transactions for its Visa cards to USDC, to now be able to settle with Visa 7 days a week, 365 days a year. Rain provides backend infrastructure – APIs, compliance layers and settlement logic – that enables fintechs and wallets to build and launch stablecoin-linked card programs. Rain’s technology stack allows for card transactions on the Visa network to be interoperable with stablecoins across multiple blockchains. When a user makes a payment with a Rain-issued Visa card, Visa settles with the merchant acquirer as usual. Rain’s platform has also fully tokenized its credit card receivables, enabling more efficient capital management and transparency across the system. These capabilities help fintechs go to market faster with new products. While giving consumers access to digital-first globally interoperable payment experiences. Rain also announced a world first: closed loop credit card receivable financing utilizing stablecoins. By borrowing from and programmatically repaying lenders Rain has been able to reduce the total cost of capital for consumer and b2b credit programs while providing lenders access to superior collateral and programmatic repayments powered by smart contracts. This powerful construct has the potential to unlock credit access for users in underdeveloped financial markets, all while unlocking significant operational and capital efficiencies for Rain and Rain powered programs. “USDC settlement allows us to be more capital efficient – helping to reduce the need for collateral while providing our counterparties the same level of protection. This sets a new standard for issuers and further enhances digital asset utility,” said Farooq Malik, CEO & Co-founder of Rain.
MIT researchers demonstrate the strongest nonlinear light-matter coupling in a quantum system that could help reach the fault-tolerant quantum computing stage with 10X faster operations and readout
MIT researchers have demonstrated what they believe is the strongest nonlinear light-matter coupling ever achieved in a quantum system. Their experiment is a step toward realizing quantum operations and readout that could be performed in a few nanoseconds. The researchers used a novel superconducting circuit architecture to show nonlinear light-matter coupling that is about an order of magnitude stronger than prior demonstrations, which could enable a quantum processor to run about 10 times faster. “This would really eliminate one of the bottlenecks in quantum computing. Usually, you have to measure the results of your computations in between rounds of error correction. This could accelerate how quickly we can reach the fault-tolerant quantum computing stage and be able to get real-world applications and value out of our quantum computers,” says Yufeng “Bright” Ye, lead author of a paper on this research. The new architecture, based on a superconducting “quarton” coupler, achieved coupling strengths roughly ten times higher than previous designs, potentially allowing quantum processors to run ten times faster. Faster readout and operations are critical to reducing errors in quantum computation, which depend on performing error correction within the limited lifespans of qubits. Researchers demonstrated extremely strong nonlinear light-matter coupling in a quantum circuit. Stronger coupling enables faster readout and operations using qubits, which are the fundamental units of information in quantum computing. (Christine Daniloff, MIT)
Google enables launching AI Mode with one-tap search on Android and iOS that does away with the homepage; adds slick animation with color glows to encompass entire screen for iOS
Besides the widget shortcut, Google is making AI Mode faster to access with one-tap search on Android and iOS. Previously, launching AI Mode from the shortcut beneath the Search bar in the Google app or widget would bring you to an introductory homepage. You’d then have to touch the “Ask AI Mode” field before you could start typing. Opening AI Mode now immediately takes you to the input box with the keyboard open. The header just shows the ‘G’ logo (and close button), while the suggested queries carousel disappears after you enter text for a minimalist look. With the previous homepage no longer available, you cannot quickly access conversation history. Google tells us to soon expect direct access from the text field. One-tap AI Mode access is live on both Google for Android and iOS. On the latter platform, Google has introduced a very slick animation. Tapping the AI Mode button will expand the usual Search field to encompass your entire screen as the keyboard pops up. As this occurs, there’s a four-color glow around the expanding perimeter that looks very nice. It fades out just as everything settles, while closing AI Mode also results in a visual effect. There’s no equivalent animation on Android right now, but there are other colorful touches.
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.
Survey shows 78% consumers think in-aisle ads being the most effective at driving future purchase consideration followed by storefront screens (76%)
According to a new survey from technology solutions provider Vistar Media and consumer research firm MFour, 95% of consumers felt either positive or neutral toward retail media ads. Visual formats are the most effective, according to the survey, with 72% of shoppers approving of parking lot screens as the first point of contact with the brand. In-aisle screens (68%) and storefront/entrance screens (64%) also have strong approval, which Vistar Media says proves their value in “guiding decisions and providing relevant product information” to shoppers. Only 4% of consumers reported that in-store ads detracted from their shopping experience. 50% of those who felt the ads improved their experience cited their visual appeal, while 34% valued the product information and 27% enjoyed the entertainment factor. 44% of shoppers surveyed said they made a purchase because of an in-store ad. Engagement was even stronger in specific placements, as 58% shoppers who viewed front entrance ads bought the advertised product immediately, and 31% of those who saw in-aisle ads redeemed a coupon or discount code. Among those exposed to parking lot ads, 32% went on to visit the brand’s website, and 19% of in-aisle viewers interacted with QR codes or digital links. 71% consumers said they were more likely to consider a brand they saw advertised, with in-aisle (78%) and storefront (76%) ads being the most effective at driving future purchase consideration.