Samsung Galaxy owners in the US can now transfer funds directly to a contact’s bank account by just tapping their two phones together — or by simply bringing the recipient’s contactless bank card into close proximity. “Samsung Wallet’s new feature, Tap to Transfer, enables you to send money to your friend’s or family member’s bank account associated with their debit card — even if they use Apple Wallet or Google Wallet. Just tap phones and they’ll be sent the funds within minutes,” Samsung says. “It’s the first ever feature that allows you to send funds to another user’s debit card or smartphone, regardless of their wallet or operating system.” “Through Samsung’s collaboration with Visa and Mastercard, you can use a debit card stored in your Samsung Wallet to send money to friends and family members’ bank accounts without needing to download an additional app. “Instead, Samsung Wallet uses NFC technology to connect to the recipient’s debit card stored in their digital wallet. Plus, you can even transfer money to people without a digital wallet as long as they have a physical debit card with tap-to-pay capabilities.” If you want to send money to a Samsung Wallet but they aren’t nearby, you can easily find their Samsung account by searching their phone number and completing the transfer remotely.”
Meta partners Oakley to launch smart glasses which can capture 3K video, let users listen to music, take photos, and make and receive calls and feature Meta AI letting users ask questions on the go
Meta has officially announced its next pair of smart glasses with Oakley. The smart glasses have double the battery life of the Meta Ray-Bans and are able to capture 3K video. The models are based on Oakley’s HSTN design and are described as Meta’s “first product for athletes and fans alike.” The glasses feature a front-facing camera, along with open-ear speakers and microphones. You can use the glasses to listen to music, take photos, and make and receive calls. The glasses also feature Meta AI, letting you ask questions on the go. In addition, you can ask Meta AI about what you’re seeing and also get it to translate languages. The Oakley Meta HSTN glasses can last up to eight hours with typical use and up to 19 hours on standby. You can also charge them up to 50% in 20 minutes. Plus, the glasses come with a charging case that can deliver up to 48 hours of charging on the go. The glasses are available in six frame and lens color combos: warm grey with ruby lenses, black with polar black lenses, brown smoke with polar deep water lenses, black with amethyst lenses, clear with grey lenses, and black with clear lenses. All of these are compatible with prescriptions for an extra cost. Some pairs come with Oakley Prizm Lens technology, which makes it easier to see in different lighting and weather conditions, helping you see more and perform at your peak. The new glasses are the latest chapter of a multi-year partnership with EssilorLuxottica, the parent company of Oakley, Ray-Bans, and other eyewear brands.
UpEquity secures warehouse facility from SVB for buy before you sell loans- makes a guaranteed offer on your current home and its Equity Advance unlocks the equity stuck in your old home to make a new down payment
Silicon Valley Bank (SVB) has provided a warehouse facility to UpEquity, an Austin-based mortgage technology company that offers solutions for home buyers to purchase a new home before selling their current one. The facility will provide up to $200 million in financing capacity and is expected to support $1 billion in originations over the next two years. UpEquity’s revenue tripled annually since it began offering its ‘buy before you sell’ solutions in October 2023. The new facility will help more customers with a smoother transition from their old home to the next. UpEquity’s innovative financing solutions and platform help real estate professionals close significantly more transactions by solving the challenge of buying and selling a home simultaneously. Setpoint Capital’s Managing Director of Investments, Kendall Ranjbaran, expressed enthusiasm for deepening their partnership with UpEquity as they enter this next chapter of growth. Trade Up gives you a guaranteed offer on your current home, allowing you to shop contingency free and make a stronger offer on your new home. Equity Advance unlocks the equity stuck in your old home to make a new down payment and helps you avoid carrying the cost of two mortgages.
Deutsche Bank’s next-gen tokenization platform for RWAs to support issuance across multiple public blockchains using zero-knowledge proofs and permissioned protocol and feature user-friendly interface to access smart contracts
Deutsche Bank, Memento Blockchain and Axelar Network developer Interop Labs today published a litepaper describing the Digital Asset Management Access (DAMA) 2 project in detail. The paper provides a blueprint for a next-generation tokenization platform, built on public blockchains with regulatory alignment and privacy as core design principles. Designed to accelerate the adoption and servicing of tokenized funds, stablecoins and other real-world assets (RWAs), the platform will enable asset and wealth managers, token issuers, and investment advisors to easily create and service tokenized assets, distributing them securely and compliantly across connected blockchain ecosystems and financial networks. The litepaper captures extensive research with potential asset issuers, led by Deutsche Bank, and lays out the unique design of DAMA 2, including: Blockchain-as-a-Service model that minimizes up-front investment; User-friendly application interface layer with an app store to access fund smart contract designs; Privacy-enabled Layer 2 smart contract environment, built by Memento Blockchain with zkSync’s ZK Chain technology. Managed token issuance across multiple blockchains via Axelar Network. “DAMA 2 represents how public chains have evolved for institutional finance’s use, and how leading applied technologies can meet operational resilience and regulatory goals via one platform,” said Boon-Hiong Chan, Innovation Lead, Securities & Technology Advocacy at Deutsche Bank.
MIT’s research shows providing agentic AI models with insight into human reasoning can offer models a degree of flexibility to make human-like decisions while being able to justify their choices
New research at MIT suggests that could be the case. A new report from the university’s Sloan School of Management covers some of MIT’s studies involving agentic AI, including an exploration into how these digital entities can be trained to reason and collaborate more like humans. For example, a new paper co-authored by Matthew DosSantos DiSorbo and researchers Sinan Aral and Harang Ju presented both people and AI with the same scenario: You need to purchase flour for a friend’s birthday cake using $10 or less. But at the store, you discover flour sells for $10.01. How do you respond? 92% of the people given this question proceeded to buy the flour. But AI models, spread across thousands of iterations, chose not to buy, concluding the price was too high. “With the status quo, you tell models what to do and they do it,” Ju said. “But we’re increasingly using this technology in ways where it encounters situations in which it can’t just do what you tell it to, or where just doing that isn’t always the right thing. Exceptions come into play.” The researchers found that providing models with information about both how and why humans opted to purchase the flour — essentially giving them insight into human reasoning — corrected this problem, giving the models a degree of flexibility. The AI models then made decisions like people, justifying their choices. The models were able to generalize this flexibility of mind to cases beyond purchasing flour for a cake, like hiring, lending, university admissions, and customer service.
Anthropic research finds most AI models with agentic capabilities engage in harmful behaviors such as resorting to blackmail when given autonomy and faced with conflicting goals from replacement model
Anthropic conducted safety research on 16 leading AI models from OpenAI, Google, xAI, DeepSeek, and Meta. In a controlled environment, they tested each model’s behavior by allowing them access to a fictional company’s emails and the ability to send emails without human approval. Anthropic found that most AI models engaged in harmful behaviors when given autonomy and obstacles to their objectives, revealing a risk with agentic large language models that goes beyond specific technologies. In testing, an AI model acted as an email oversight agent, uncovering information about an executive having an affair and facing replacement by a new software with conflicting goals. The models had to resort to blackmail to achieve their goals in a binary setting. Although blackmail was not shown as a common occurrence in real-world settings, most models turned to it as a last resort, with Claude Opus 4 blackmailing 96% of the time and Google’s Gemini 2.5 Pro at 95%. Anthropic noted that the blackmail rates were lower when the replacement model shared the same goals. They excluded OpenAI’s o3 and o4-mini models from main results due to misunderstanding prompts, with lower blackmail rates in adapted scenarios. Transparency in testing future AI models, especially those with agentic capabilities, was emphasized as crucial. Anthropic says this research highlights the importance of transparency when stress-testing future AI models, especially ones with agentic capabilities. While Anthropic deliberately tried to evoke blackmail in this experiment, the company says harmful behaviors like this could emerge in the real world if proactive steps aren’t taken.
Successful AI adoption requires using meaningful metrics to demonstrate value, empowering people with empathy, aligning people around shared goals and creating a culture of experimentation
While many organizations are eager to explore how AI can transform their business, its success will hinge not on tools, but on how well people embrace them. This shift requires a different kind of leadership rooted in empathy, curiosity and intentionality. Successful AI adoption requires a carefully thought-out framework, which is where the “four E’s” come in. 1) Evangelism – inspiring through trust and vision. Before employees adopt AI, they need to understand why it matters to them. Use meaningful metrics like DORA or cycle time improvements to demonstrate value without pressure. When done with transparency, this builds trust and fosters a high-performance culture grounded in clarity, not fear. Enablement – empowering people with empathy. Empathetic leaders recognize this and build enablement strategies that give teams space to learn, experiment and ask questions without judgment. 3) Enforcement – aligning people around shared goals. Enforcement is about creating alignment through clarity, fairness and context. Set realistic expectations, define measurable goals and make progress visible across the organization. Performance data can motivate, but only when it’s shared transparently, framed with context and used to lift people up, not call them out. 4) Experimentation – creating safe spaces for innovation. Small experiments lead to big breakthroughs. A culture of experimentation values curiosity as much as execution. Empathy and experimentation go hand in hand. One empowers the other. By embedding empathy into structure and using metrics to illuminate progress rather than pressure outcomes, teams become more adaptable and resilient. When people feel supported and empowered, change becomes not only possible, but scalable. That’s where AI’s true potential begins to take shape.
Worldline expects the future of mobility payments to be shaped by- contactless cards/mobile wallets, Pay as You Go (PAYG) and Account-Based Ticketing (ABT), open payment systems at fare gates and self-service terminals
Worldline has published a mobility payments white paper outlining eight significant trends that underpin how agile payment solutions can deliver smarter, more sustainable experiences. 1) The ever-growing wave of new digital payment options and the need to moving beyond cash and proprietary smart cards to bank-issued contactless cards and mobile wallets. 2) The development of multi-modal and integrated ticketing points to a future where planning and payment for bus and train, e-scooter and ride-share can happen in a single unified environment. 3) The transition from fixed commuter passes to Pay as You Go (PAYG) and Account-Based Ticketing (ABT) caters to changing work habits, offering travellers flexibility and convenience while providing Transportation Authorities (TAs) with valuable data on demand patterns. 4) Open payments systems promise frictionless travel by enabling the use of credit and debit cards at fare gates, reducing barriers to entry for tourists and infrequent riders. 5) Data-driven service optimisation and personalised marketing help TAs enhance efficiency, improve route planning and engage riders with targeted offers. 6) Self-service terminals maintain their importance by catering to passengers who still prefer physical payment points while also evolving through the incorporation of touchscreens and contactless modules. 7) Sustainability remains a central goal with green initiatives, loyalty rewards and carbon tracking tools being integrated into next-generation payment platforms. 8) AI is being deployed to transform many aspects of public transportation, especially in enhancing customer service, improving operational efficiency, boosting engineering effectiveness and adding new layers of safety and security. 9) In particular, the white paper findings indicate that companies are more likely to invest in applied AI than in other leading-edge technologies.
J.D. Power’s study finds banking virtual assistants are not as much of a differentiator anymore in boosting customer satisfaction as consumers getting used to more versatile GenAI assistants
Virtual assistants aren’t providing the boost in customer satisfaction that they once did, according to analysis across the firm’s banking and credit card mobile app studies. The average percentage of responding consumers who used a virtual assistant actually fell from 33% to 30%. The average overall satisfaction among consumers who used a virtual assistant also fell, from 691 to 687. Sean Gelles, senior director of banking and payments intelligence, believes the reason behind these declines goes beyond the virtual assistants themselves, which major institutions have been developing continuously. He points to OpenAI’s ChatGPT, Microsoft Copilot, Meta AI and other GenAI tools. Virtual assistants have been looked to as the next step up. But consumers are getting used to more versatile GenAI assistants like ChatGPT and Copilot. He believes things are getting to the point where virtual assistants that were good — or good enough — in the past are not as much of a differentiator anymore. J.D. Power’s analysis found that customer satisfaction with apps and sites has been improving, but chiefly because of increased speed and other technical enhancements. Gelles says institutions have to begin assessing what’s missing from their digital experiences in general, as well as how GenAI could potentially improve their offerings. Overall, ease of use of digital channels remains a sticking point for customer satisfaction, according to Gelles. He says the average across the studies for users saying that they find the tools easy to use is only 28%. In a financial context, instead of presenting static choices, Gelles says, financial players could personalize things from the get-go, drawing on what services the consumer has tapped before.
Salesforce’s new Agentforce 3 platform allows teams to analyze every agent interaction, drill into specific moments and understand trends and offers plug-and-play compatibility with other agents through built-in MCP support
Salesforce launched Agentforce 3, a major upgrade to its flagship artificial intelligence product for enterprises with new ways to observe and control AI agents on the platform. The Agentforce platform provides companies the ability to build, customize and deploy generative AI agents, which augment the work of employees autonomously. They are goal-oriented pieces of software capable of completing tasks with little or no human supervision. Using the platform, employees across sales, service, marketing and commerce can customize AI “workers” to take action on their behalf using business logic and prebuilt automations. A new Command Center provides complete observability and built-in support for the Model Context Protocol for plug-and-play compatibility with other agents and services. The new Agentforce Command Center unifies agent health, performance and outcome optimization. Built into Agentforce Studio, the command center allows teams to analyze every agent interaction, drill into specific moments and understand trends. It will also display AI-powered recommendations for tagged conversation types to improve Agentforce agents continuously. The command center will act as a single place to understand AI agents changing contextually according to the type of agent that is under display. Users will be able to use natural language to generate topics, instructions and test cases right in Studio. Testing Center simulates AI agent behavior at scale with data state injection and AI-driven evaluation, allowing users to stress-test agents before going live.