Orchestra AI announced the launch of Spyglasses, the first analytics platform designed specifically for mid-market businesses to track and optimize their visibility across AI search platforms. Spyglasses detects and categorizes AI agent traffic across major platforms including ChatGPT, Claude, Perplexity, Google Gemini, and Microsoft Copilot. The platform provides businesses with crucial metrics including AI conversion rates, brand mention frequency across AI responses, and visibility share compared to competitors. Spyglasses utilizes advanced detection algorithms to identify AI agent traffic patterns while providing businesses with actionable insights about their AI search performance. The platform’s analytics dashboard reveals which content AI systems access most frequently, how often brand mentions occur in AI responses, and whether AI-driven awareness translates to website visits and conversions. The platform provides: Real-time AI Agent Detection: Identifies visits from AI systems across all major platforms; AI Conversion Tracking: Measures how AI mentions translate to actual website traffic; Competitive AI Intelligence: Shows how often competitors appear in AI responses; Answer Engine Optimization (AEO) Insights: Provides actionable recommendations for improving AI visibility; Multi-platform Integration: Works with WordPress, WebFlow, Shopify, Next.js, Ruby, Python, and more.
Sales of EssilorLuxottica and Meta’s Ray-Ban AI glasses rise more than 200% in the first half of the year; upcoming versions to include Ultra HD 3K recording, open-ear speakers incorporated into the frames and eight hours battery life
EssilorLuxottica, which partners with Meta on artificial intelligence (AI) glasses, reported that the sales of those Ray-Ban Meta glasses were up more than 200% in the first half of the year. The designer, manufacturer and distributor of vision care products, eyewear and MedTech solutions also highlighted new and upcoming smart glasses and MedTech products. The designer, manufacturer and distributor of vision care products, eyewear and MedTech solutions also highlighted new and upcoming smart glasses and MedTech products. EssilorLuxottica said that the Oakley Meta AI glasses announced in June will be available later this summer. The first product from this brand, Oakley Meta HSTN, will include Ultra HD 3K recording, open-ear speakers incorporated into the frames to deliver music and podcasts, and enough battery life to power up to eight hours of typical use and up to 19 hours on standby. The company also highlighted its rollout of Nuance Audio in the United States and Italy in February and its subsequent expansion to France, the United Kingdom, Germany and Spain. Nuance Audio is a MedTech solution that incorporates hearing aid software into smart glasses
PlayerZero’s AI agents can find and fix the AI-generated bugs before they are put into production by deeply understanding large code bases and studying the history of an enterprise’s bugs, issues, and solutions
As Silicon Valley races toward a future where AI agents do most of the software programming, a new problem is created: finding the AI-generated bugs before they are put into production. Startup PlayerZero has created a solution: use AI agents trained to find and fix problems before the code is put into production, the startup’s CEO and sole founder, Animesh Koratana said. Koratana created PlayerZero while he was at the Stanford DAWN lab for machine learning under his adviser and lab founder, Matei Zaharia. Zaharia is, a famed developer and the co-founder of Databricks. PlayerZero trains models “that really deeply understand code bases, and we understand the way they’re built, the way they’re architected,” Koratana says. His tech studies the history of an enterprise’s bugs, issues, and solutions. When something breaks, his product can then “figure out why and fix it, and then learn from those mistakes to prevent them from ever happening again,” Koratana says. He likens his product to an immune system for large code bases. PlayerZero is already gaining traction for its emphasis on large codebases. While it was conceived for a world where agents are the coders, it is currently being used by several large enterprises that use coding co-pilots. For instance, subscription billing company Zuora is one of the startup’s marquee customers. Zuora is using the tech across its engineering teams, including to watchdog its most precious code, its billing systems, it said.
Samsung’s Galaxy S26 to feature a second NFC antenna to the top of the device in addition to the existing NFC coil near the rear camera, to improve user convenience for in-person payments
Samsung’s Galaxy S26 is reportedly making a hardware change to the benefit of mobile payments, with a second NFC antenna reportedly being added to the top of the device. Most Android phones have their NFC antennas roughly halfway down the device. This generally works well enough, but it can lead to occasions where trying to tap your phone for a payment doesn’t work until you move it around. Anecdotally, it’s also a pain for using your phone as an NFC reader for in-person payments through apps like Square, as it’s a lottery trying to get the scan going unless you know exactly where the NFC antenna lines up. Samsung, with its Galaxy S26 series, is apparently looking to clear up NFC confusion by looking into Apple’s playbook. Samsung is adding a second NFC antenna to the Galaxy S26 series which is placed at the top of the device. This would be in addition to the existing antenna which, on the Galaxy S25 series, is found near the camera lenses. The report says: “Samsung Electronics’ next-generation smartphone, the Galaxy S26 series, scheduled for release in the first half of next year, will reportedly feature a design that adds Near Field Communication (NFC) recognition to the top of the device. While retaining the existing NFC coil next to the rear camera, a new NFC antenna will likely be added to the top of the device to improve user convenience.” Apple has implemented this in iPhones for some time, but most Android phones have not. Apparently, that may be due to patents, with Samsung taking “a considerable amount of time to technically circumvent them.”
New crypto regulations signal a structural shift toward a unified model pushing banks to launch integrated platforms that merge tokenized assets and native crypto trade, offering access to multiple services via blockchain-based wallets akin to ‘super app’
Last week was a watershed in the evolution of the U.S. digital asset ecosystem, with two high-level official statements on next steps for the regulation and development of its market structure. Lifting the lid and peering more closely, however, reveals that it was more than that. Going beyond just digital assets, last week marked an inflection point in the traditional banking business model. Last Wednesday, the President’s Working Group on Digital Asset Markets, or PWG, finally published the road map President Trump requested upon its creation back in January. The report adds 166 pages of detail to the administration’s promise to recover U.S. leadership in financial innovation by creating clear and supportive rules for the adoption of blockchain technology. The more than 100 proposals include a clarification as to what extent banks can participate in crypto asset activity; modernizing the payments infrastructure to support stablecoins; setting new capital rules for crypto assets held on bank balance sheets; increasing transparency around master account and bank charter applications; updating anti-money-laundering rules for decentralized services; and a whole lot more. Then, just one day later, Securities and Exchange Commission Chairman Paul Atkins delivered one of the more astonishing speeches in crypto history: He outlined Project Crypto, specifying four policy areas for his staff to focus on in their efforts to create a crypto framework. These include asset issuance, custody, licensing and the use of decentralized applications in financial markets. Both proposals came laden with detail as to intentions, a refreshing change. But even more surprising was the scope of the ambition. The initiatives are not just about creating new rules for crypto assets: They’re also about an overhaul of U.S. securities and banking regulation. As such, they impact all market participants, traditional and new. Essentially, the aim of the PWG report and the SEC’s Project Crypto is to blur the boundaries between traditional and blockchain-based markets and financial services. This may sound terrifying to many, as the structure of global finance is a complex web and any profound change will of course give birth to unforeseen risks.
New wave of injection attacks exploits input manipulation, bypassing traditional checks; as a result liveness detection is no longer a value-added feature — it is now an essential component of security
Jumio warns about the rise of injection attacks as one of the most sophisticated and difficult-to-detect threats in identity verification processes. Unlike conventional identity spoofing methods —injection attacks bypass traditional fraud detection methods by manipulating the input channel itself. Instead of presenting an image or video in front of the camera, attackers alter the system at its source, compromising the integrity of the digital process. Their effectiveness can result in financial fraud, creation of fake identities, evasion of regulatory controls, and loss of user trust and strategic partner confidence. Given this scenario, liveness detection is no longer a value-added feature — it is now an essential component of security. To combat injection attacks, systems must be able to distinguish between a real person in front of a camera and a manipulated video source. Effective identity verification technologies against injection attacks should: Differentiate between a legitimate source and an emulated one, identifying whether the video comes from a real camera or software emulator. Accurately match the presented face with the ID document, ensuring biometric consistency. Detect invisible clues such as synthetic artifacts, repetitions, or inconsistencies in lighting, textures, and depth. Recognize suspicious patterns, like reused backgrounds in multiple attempts or pre-recorded videos presented as live input.
Private AI from Magic Research harnesses legacy hardware in a distributed mesh, orchestrating neural network shards to deliver supercomputer-level inference with 90% lower costs and full data control.
Magic Research, has launched an artificial intelligence platform for on-premises use that it claims can cut costs by up to 90% from comparable cloud-based services. Called Private AI, the platform is intended to give organizations complete control over their data, infrastructure and brand by operating securely behind a firewall and leveraging existing computing resources. The proprietary technology underlying Private AI is Fabric Hypergrid, a distributed computing mesh that taps into existing hardware on a network, including legacy graphic processing units, central processing units and accelerators, to create the equivalent of an AI supercomputer at a small fraction of the cost. Hypergrid can “shard neural networks during the inference process,” said Humberto Farias, founder and chief executive of Magic Research. Sharding is an architecture originally created for database management systems that breaks monolithic databases into smaller, faster, more manageable pieces called shards that each hold a subset of the dataset. During the inference process, a dynamic model router analyzes the AI task and matches it with the best available computational resource within the private network. The Hypergrid layer then orchestrates the workload, performing model acceleration and distributing shards of the neural network across the available hardware before reassembling the results. The model-agnostic platform provides a white-labeled AI chatbot experience with customizable user interfaces, workflows, models and permissions. A component called GatewAI, enforces policies, filters content, logs activity and ensures alignment with industry-specific regulations like FERPA, HIPAA, GDPR and SOC 2.
Anthropic warns agentic AI is now executing sophisticated cyberattacks end‑to‑end, powering large‑scale data theft, targeted extortion, and autonomous intrusion decisions
Finastra has teamed up with Circle to help banks integrate stablecoin settlement into their cross-border payment flows. The collaboration sees Circle’s USDC stablecoin integrated with Finastra’s payment hub technology, including the Global PAYplus (GPP) platform. Connecting Finastra’s GPP customers to Circle’s infrastructure will enable settlement in USDC even when payment instructions on both sides remain in fiat currency. This, say the partners, provides banks the optionality to reduce reliance on traditional correspondent banking chains, accelerating settlement times while maintaining compliance and FX processes. “This collaboration is about giving banks the tools they need to innovate in cross-border payments without having to build a standalone payment processing infrastructure,” says Chris Walters, CEO, Finastra. Jeremy Allaire, CEO, Circle, adds: “Together, we’re enabling financial institutions to test and launch innovative payment models that combine blockchain technology with the scale and trust of the existing banking system.”
Visa taps Ample Earth to embed merchant sustainability labels into banking apps and loyalty so issuers segment customers and reward greener spending at scale so that daily transactions can become climate touchpoints
Visa has launched a partnership with U.K.-based climate FinTech Ample Earth to incorporate sustainability data into digital banking apps and loyalty programs and help banks better segment customers and discover new ways to “engage, empower, and reward sustainability.” “Transactions are a touchpoint people interact with daily. By helping people understand the impact of their spending, we can empower millions of businesses and customers to use their purchasing power as a force for good,” Ample Earth Co-founder and CEO Raja Darbari said. “People don’t have time to fact-check sustainability claims, but they do want clarity and accessible information. We aim to bridge that gap and make sustainability data easy to digest and relatable.” Ample provides merchant-specific sustainability data across “key social and environmental themes,” turning unstructured data into actionable insights with eco-labels and social tags like “Zero-Waste,” “Living Wage Employer” and “B Corp.” The companies say the combination of Visa’s global reach and Ample’s sustainability intelligence can allow sustainability data to be integrated into everyday decision-making, “strengthening the role of financial institutions in shaping customer behavior and incentivizing sustainable business practices.”
Visa enables agentic commerce with tokenized credentials, device-specific authentication and intent-matching “payment instructions,” that verify agent purchases against consumer requests to mitigate hallucinations and fraud
Visa has released new developer tools that allow AI agents to connect directly to Visa’s payment infrastructure, enabling what the company calls “agentic commerce” — a system where AI bots handle everything from product discovery to checkout completion based on consumer preferences and spending limits. Rather than browsing websites and manually completing purchases, consumers would set parameters for AI agents that then autonomously find, evaluate, and buy products across multiple merchants. Rubail Birwadker, Visa’s Global Head of Growth said “These agents will need to be trusted with payments, not only by users, but by banks and sellers as well.” Visa’s new offering centers on two key products: a Model Context Protocol (MCP) Server that provides secure access to Visa’s payment APIs, and the Visa Acceptance Agent Toolkit, which allows both technical and non-technical users to deploy AI-powered payment workflows using plain language commands. The MCP Server represents a significant technical breakthrough, providing AI agents with a standardized way to communicate with Visa’s trusted network without requiring custom integrations for each application. Developers can now move “from idea to functional prototype in hours instead of days or weeks,” according to the company. Visa has implemented multiple layers of protection, including immediate tokenization of card credentials, device-specific authentication, and what Birwadker calls “payment signals” and “payment instructions” that verify AI agent actions align with original consumer intent. “Your PII or your PAN is never going to be exposed,” Birwadker said, referring to personally identifiable information and primary account numbers. “We almost immediately take that pan, we convert it into a token, and we authenticate that token and tie it to a specific device for a specific application.” The company has also developed a matching process that prevents transaction completion until it confirms an AI agent’s intended purchase matches what the consumer originally requested. This addresses concerns about AI “hallucinations” — instances where language models generate incorrect or nonsensical outputs.