In an era where differentiation in banking is increasingly difficult, Ally Bank has emerged as a leader in creating exceptional digital banking experiences. Sathish Muthukrishnan, chief information and technology officer at Ally Financial said, “The intent behind launching our technology strategy was to ensure that technology will continue to be relevant in an all-digital bank, but more importantly, to create differentiation and drive significant business outcomes. We categorized our strategy into six different pillars. The first is security. Our second pillar was driving tremendous experiences. The third pillar is how I know my experience is working. That’s when data analytics came in. Measure what consumers do, but more importantly, measure what they don’t do. Our operational pillar involved migrating to cloud, driving automation and consistency in how we develop and deploy code. And then we needed to preserve our culture and take care of our talent. These pillars laid the foundation for our transformation. We now have about 75% of our applications running on the cloud and about 95% of the enterprise data in the cloud. This allows us to learn from consumer behaviors, understand what they’re expecting and create experiences in real time so consumers think they are our only customer. We had our cloud strategy and data in the cloud warehouse. At the beginning of 2022, we redefined our network. As we were thinking about AI, we launched our chat assistant, Ally Assist. We created Ally AI because we knew technology was fast-evolving, but there were concerns about sending data to external LLMs. To address this, we built an AI platform that could connect to external LLMs but with added security — it removes PII, tracks all transactions and rehydrates PII for context. Our platform can connect to multiple LLMs — from GPT to FLAN to Bedrock. We can pick the right LLM depending on the use case or combine answers from several LLMs. Our content creation LLM is different from what we use for code generation or risk assessment. We have different models for different use cases. My advantage is that the product team, UI/UX team and technology team are all part of the same technology organization. We rolled out savings buckets — your deposit account with multiple savings buckets that you can name yourself. If you start questioning why roadblocks exist and how to solve them, your brand becomes more relevant to consumers. You become their next best experience, deepening relationships.”
Sakana’s Continuous Thought Machines (CTM) AI model architecture uses short-term memory of previous states and allows neural synchronization to mirror brain-like intelligence
AI startup Sakana has unveiled a new type of AI model architecture called Continuous Thought Machines (CTM). Rather than relying on fixed, parallel layers that process inputs all at once — as Transformer models do —CTMs unfold computation over steps within each input/output unit, known as an artificial “neuron.” Each neuron in the model retains a short history of its previous activity and uses that memory to decide when to activate again. This added internal state allows CTMs to adjust the depth and duration of their reasoning dynamically, depending on the complexity of the task. As such, each neuron is far more informationally dense and complex than in a typical Transformer model. CTMs allow each artificial neuron to operate on its own internal timeline, making activation decisions based on a short-term memory of its previous states. These decisions unfold over internal steps known as “ticks,” enabling the model to adjust its reasoning duration dynamically. This time-based architecture allows CTMs to reason progressively, adjusting how long and how deeply they compute — taking a different number of ticks based on the complexity of the input. The number of ticks changes according to the information inputted, and may be more or less even if the input information is identical, because each neuron is deciding how many ticks to undergo before providing an output (or not providing one at all). This represents both a technical and philosophical departure from conventional deep learning, moving toward a more biologically grounded model. Sakana has framed CTMs as a step toward more brain-like intelligence—systems that adapt over time, process information flexibly, and engage in deeper internal computation when needed. Sakana’s goal is to “to eventually achieve levels of competency that rival or surpass human brains.” The CTM is built around two key mechanisms. First, each neuron in the model maintains a short “history” or working memory of when it activated and why, and uses this history to make a decision of when to fire next. Second, neural synchronization — how and when groups of a model’s artificial neurons “fire,” or process information together — is allowed to happen organically. Groups of neurons decide when to fire together based on internal alignment, not external instructions or reward shaping. These synchronization events are used to modulate attention and produce outputs — that is, attention is directed toward those areas where more neurons are firing. The model isn’t just processing data, it’s timing its thinking to match the complexity of the task. Together, these mechanisms let CTMs reduce computational load on simpler tasks while applying deeper, prolonged reasoning where needed.
Microsoft finds API- based agents are generally more stable, less error-prone vis-à-vis GUI-based agents that require multiple actions to accomplish the same goal
Microsoft researchers have compared API-based and GUI-based AI agents, finding that each approach has distinct strengths and can work well together. API agents interact with software through programmable interfaces, while GUI agents mimic human use of software, navigating menus and clicking buttons. API agents are generally more stable and less error-prone, while GUI agents require multiple actions to accomplish the same goal. However, GUI agents can control almost any software with a visible interface, whether or not it offers an API. Microsoft outlines three strategies for combining both types of agents into hybrid systems: using API wrappers to hide GUI actions behind a programmable interface, using orchestration tools to coordinate both API and GUI steps in a workflow, and using low-code and no-code platforms for non-technical users to build automations using drag-and-drop interfaces. Recent advances in multimodal AI and new tools simplifying API development could lead to more flexible forms of automation that blur the line between front-end and back-end integration. Choosing the right agent for the job is crucial for long-term automation success. API agents are best for performance-critical tasks and security-sensitive environments, while GUI agents are better suited for legacy systems that lack APIs and mobile apps. Organizations can start with GUI agents and gradually switch to APIs as they become available.
Morgan Stanley forecasts the market for humanoids will grow to become materially larger than the global auto industry and reach approximately $4.7 trillion by the year 2050
Humanoid will arrive sooner than expected, says Morgan StanleyHumanoid will arrive sooner than expected, says Morgan Stanley. The investment banking firm projects that “the team set forth their proprietary humanoid TAM model that projects the global market for humanoid robots will grow to become materially larger than the global auto industry.” This accelerated timeline suggests a potentially disruptive force with broad economic and sector-wide implications. With the arrival of humanoids, the MS research estimates this potential impact by estimating that the market for humanoids could reach approximately $4.7 trillion by the year 2050. This provides the long-term investment opportunities and the transformative nature of humanoid technology for the investors. Within this AI-driven landscape, the development of humanoids, considered a subset of “Embodied AI,” is identified as a key area of focus. However, 2025 will be the year of Agentic AI, where companies can use Agentic AI tools to improve their businesses. Morgan Stanley says, “we believe the magnitude of benefits from AI adoption is vastly underestimated.” “AI spend is set to rise dramatically, but we see a $1.1 trillion revenue opportunity as early as 2028, with contribution margins of 34% in 2025, rising to 67% by 2028,” Morgan Stanley said. On the nuclear power front, Morgan Stanley believes that “nuclear renaissance will be worth $1.5 trillion through 2050 in the form of capital investment in new global nuclear capacity, which is based on the assumption that there will be 383.5GW of new nuclear capacity to be added globally, which is roughly equal to the current global nuclear capacity of 390GW.” Both AI and humanoids are seen as pivotal forces shaping investment strategies and offering significant opportunities for alpha generation within the evolving technological landscape.
TSB Bank offers access to safeguarding app for users who are fleeing or experiencing abuse- alerts can be sent to chosen emergency contact with a simple tap or shake of the smartphone
TSB will offer customers who are fleeing or experiencing abuse, free access to Hollie Guard Extra for a year1 – simply by downloading the app and using a unique activation code. Those wishing to claim can discuss their situation in branch, over the phone or via video banking. Once installed, Hollie Guard Extra transforms an everyday smart phone into a personal safety device. TSB has added this level of protection to its existing domestic abuse support – which includes its Emergency Flee Fund2 and Safe Spaces3. With a simple tap or shake of the device, the user can send alerts to chosen emergency contacts, including the police, and a 24/7 monitoring centre. The app allows for a user’s location to be shared every five seconds, alongside audio and video recordings, helping to keep people safe in a vulnerable or potentially dangerous situation. The app has already been downloaded by almost 500,000 people in the UK and Hollie Guard Extra is being used by police forces across England and Wales. In addition, it has led to numerous arrests and helped in more than 1,500 threatening and dangerous situations. TSB hopes that Hollie Guard Extra can provide further support to TSB’s Flee Fund – helping connect and protect victim-survivors having fled an abuser.
Plaid’s ID verification tech can now counter deepfakes, synthetic media and facial duplicates; and includes age estimation to flag impersonation risks
Plaid has updated its identity verification (IDV) product to counter the threat posed by fraudsters who use Gen AI. New features added to the product include deepfake and synthetic media detection, facial duplicate detection to catch repeat fraud attempts, age estimation to flag impersonation risks, and risk-based flows that adapt in real time to streamline trusted users and escalate high-risk ones. The upgrades are now available to all Plaid IDV customers, with no extra integration required. Powered by our Trust Index, these enhancements help you streamline verification for trusted users while tightening controls for higher-risk cases: Risk-Based Escalations; Selfie Re-Authentication; Trust Index Risk Check. By combining rich data sources and high-fidelity signals with the scale of our network, Plaid gives companies a faster, more secure way to verify identity and stop fraud at the front door. These enhancements are available to all Plaid Identity Verification (IDV) customers out of the box, with no additional integration required.
Pagaya’s platform for second-look personal loans offers potential for a mid-sized bank of over $1.5 billion of personal-loan origination in less than nine months; can help lenders “bid better” on Credit Karma or Experian
Alternative lending fintech Pagaya Technologies has its sights set on expanding its personal loan offering to regional and super-regional banks while it also builds out its marketing acquisition engine. Pagaya currently partners with banks such as U.S. Bank and neobanks such as SoFi to offer artificial intelligence-powered second-look personal loans to consumers who might not otherwise qualify. Pagaya integrates with lenders’ loan origination systems and buys the loans it originates from the lenders and sells those loans on the secondary market. It is also active in auto lending and point-of-sale buy now/pay later lending. All in, Pagaya counts 31 lenders as partners. Pagaya is in talks with four or five regional banks to help build out or expand their personal-loan offerings, co-founder and CEO Gal Krubiner told. “There is a new era where people are starting to look at growth, and for the regional banks, personal loan is a good way to grow the franchise and to give solutions and products to their customers,” he said. Many regional banks look to personal loans to help secure deposit inflows, a trend that Pagaya is hoping to capitalize on when bringing new partner banks into the fold, Krubiner said. “From our perspective … working with Pagaya could generate for a mid-sized bank over $1.5 billion of personal-loan origination in less than nine months,” Krubiner said, citing U.S. Bank’s performance on the platform. Pagaya is also using its integration into lenders’ underwriting platforms to offer pre-screened loans to potential customers in another avenue that it hopes will lead to growth, said Sanjiv Das, president of Pagaya. “Think about our total market opportunity. We have 31 lending partners. Those 31 lending partners have about 60 million consumers as existing customers. We’ve only scratched the surface right now with the 3% [penetration],” Das, told. Pagaya is also working to help lenders “bid better” for leads from data aggregators, such as Credit Karma or Experian, Das said. The push toward regional banks comes on the heels of solid first-quarter earnings results that beat analysts’ estimates across nearly every metric. Revenue jumped 18% year over year to $290 million, ahead of analysts’ expected $285 million. Net income landed at $8 million, or 10 cents per share, compared with a $21 million loss in the same reporting period last year and eclipsing analysts’ estimate of a $10 million, or 15 cent per diluted share, loss. Shares of Pagaya have risen about 26% since the company reported earnings on May 7, according to a research note from David Scharf at Citizens. Scharf attributes the gains to Pagaya hitting positive GAAP net income ahead of schedule. KBW analyst Sanjay Sakhrani bumped his price target for Pagaya’s stock following the earnings report, pointing to pre-screen and affiliate channels as “growth drivers.” “We believe PGY is well-positioned to shift toward revenue growth across its three loan markets — personal, auto, and POS and deliver profitability. While macroeconomic volatility may introduce risks to funding costs and underwriting capabilities, management’s disciplined risk approach and measured appetite provide confidence,” Sakhrani said.
Android 16 UI to sport a bolder visual appeal and feature “springy” animations, new motion physics, newer shapes, brighter splashes of color and more impactful fonts
Google is introducing one of the biggest revamps it has ever seen with the launch of a new design language called Material 3 Expressive. Set to arrive in Android 16, Material 3 Expressive is a sweeping new user interface update that aims to make the platform more visually appealing, emotional and interactive. It incorporates new motion physics, fresh color schemes, component updates and more impactful fonts to bring a fresh new look to Android, and potentially reshape how devices feel and function. Material 3 Expressive was announced , alongside new security features for “at risk” users. The company also revealed it’s expanding the availability of its Gemini generative AI models to Android-powered devices such as cars, TVs and wearables. According to Google, the Material 3 Expressive language will launch on Android handsets first, and we’ll likely see it on the next generation of Pixel smartphones, before expanding to Google’s broader app ecosystem. Material 3 Expressive shares some of the basic design elements that debuted in the Material You system launched by Google four years ago, but it’s altogether much bolder, featuring “springy” animations, newer shapes and brighter splashes of color. “With the release of Android 16, users who choose to activate Advanced Protection will gain immediate access to a core suite of enhanced security features,” said Il-Sung Lee, Google’s product manager for Android Security. “Additional Advanced Protection features like Intrusion Logging, USB protection, the option to disable auto-reconnect to insecure networks, and integration with Scam Detection for Phone by Google will become available later this year.”
Wyoming’s Stable Token Commission taps Inca Digital’s analytics platform for real-time monitoring and mitigation of risks related to fraud for its fiat-backed, state-issued stablecoin
The Wyoming Stable Token Commission has partnered with analytics provider Inca Digital on its forthcoming state-backed Wyoming Stable Token (WYST). WYST is said to be “the first fully-reserved, fiat-backed stable token issued by a U.S. public entity.” The asset will be fully backed by U.S. Treasurys, cash, and repurchase agreements. “The Commission’s goal is to enhance financial transparency and drive economic growth for the state, fortifying Wyoming’s position as a national leader in digital assets,” it wrote. Inca will provide real-time risk management solutions and other analytics services. “This collaboration will bolster the Commission’s ability to monitor and mitigate risks related to fraud, money laundering, and market anomalies, ensuring the safety and integrity of WYST for its users,” the commission wrote. Executive Director of the Wyoming Stable Token Commission Anthony Apollo said. “By leveraging Inca’s industry-leading intelligence tools, we are reinforcing our promise to deliver a trustworthy digital asset for Wyoming and beyond.” State authorities hope the token will enable “near-instant, dollar-denominated transactions worldwide” while offering “significantly lower fees compared to traditional financial systems.” At launch, WYST will be the first stablecoin directly issued by a government.
Pega launches agents for workflow and decisioning design that can instantly create out-of-the-box conversational agents from any workflow
Pegasystems unveiled Pega Predictable AI™ Agents that give enterprises extraordinary control and visibility as they design and deploy AI-optimized processes. Businesses can deploy Pega Predictable AI Agents with confidence, accelerating value while minimizing risk. Pega Predictable AI Agents allow enterprises to avoid the sinkhole of “AI black boxes” by thoughtfully integrating AI agents into the world’s leading enterprise platform for workflow automation. Instead of providing nothing more than prompt-based authoring tools, basic dashboards, and vague advice to use it wisely, Pega maximizes the value of AI while minimizing risk with the following Pega Predictable AI Agents: Design Agents: At the core of Pega Predictable AI Agents strategy is Pega Blueprint™, the industry’s first agents for workflow and decisioning design. Pega Blueprint leverages a collection of unique AI models and agents to generate workflows, next-best-action strategies, data structures, interfaces, user screens, security configuration, and more. It can also be invoked at runtime if a user needs to automate a process on the fly that isn’t already defined in the application. Conversation Agents: Leveraging the Pega Agent Experience™ API, Pega Blueprint can instantly create out-of-the-box conversational agents from any workflow. Automation Agents: Clients can incorporate these agents into their workflows as specific workflow steps, orchestrating agents both inside and outside of Pega to accelerate productivity in a transparent and reliable way. Knowledge Agents: Pega Blueprint leverages Pega Knowledge Buddy™ agents to create workflows that leverage industry best practices and to embed guidance inside other workflows. Coach Agents, such as Pega Coach, collaborate with humans involved in a workflow step to provide real-time, contextual guidance about the work.