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.
Zilliz Cloud is supporting powering database infrastructure of AI applications through sub-10ms latency, zero downtime and outages, 70% savings in infrastructure costs, 10% improvement in search accuracy and 8% faster responsesdelivers sub-10ms latency and cost savings for AI-first companies
Organizations implementing Zilliz Cloud are experiencing transformative performance improvements that directly impact their AI applications: 1) CX Genie doubled query performance after migrating to Zilliz Cloud, reducing latency to just 5–10ms across over 1 million embeddings. The team eliminated recurring downtime and improved global service reliability — critical for its always-on AI-powered customer support. Latency: 2× faster, now 5–10ms; Uptime: Zero daily downtime; Costs: 70% infrastructure savings. 2) Beatoven.ai, an AI-powered music creation platform, shortened generation time by 2–3 seconds per track after adopting Zilliz Cloud — improving creative workflows for its 1.5 million+ users. Tracks: Over 6 million AI-generated; Speed: 2–3s faster music creation; Costs: 6× reduction in operational spend. 3) Ivy.ai powers AI chatbots for higher education and government institutions. As data volumes surged by 200%, Zilliz Cloud enabled them to maintain consistent response times without a single outage. Data growth: +200%; Reliability: Zero outages; Consistency: Stable response times at scale 4) Dopple Labs uses Zilliz Cloud to store and retrieve long-term memory embeddings for Dopple.ai, its virtual AI companion. By improving context awareness across conversations, Dopple now offers more natural, personalized interactions. Context: Improved memory across sessions; Interactions: More personalized, human-like dialogue 5) EviMed, a medical AI platform, integrated Zilliz Cloud to manage 350M+ medical knowledge entries. They achieved better search accuracy and faster responses while cutting system costs. Accuracy: +10% in clinical search precision; Speed: +8% faster responses; Efficiency: 30% lower operational cost. The results reported by Zilliz Cloud customers show that database infrastructure is no longer just backend plumbing — it’s a core driver of AI performance, reliability, and cost-efficiency. The ability to deliver sub-10ms latency, reduce outages, and cut operational costs gives AI teams a powerful edge in a competitive market.
Anaconda supports enterprise open source, combining trusted distribution, simplified workflows, real-time insights, and governance controls in one place to deliver secure and production-ready enterprise Python
Anaconda announced the release of the Anaconda AI Platform, the only unified AI platform for open source that provides proven security and governance when leveraging open source for AI development, empowering enterprises to build reliable, innovative AI systems without sacrificing speed, value, or flexibility. As the only AI platform for open source, the Anaconda AI Platform combines trusted distribution, simplified workflows, real-time insights, and governance controls in one place to deliver secure and production-ready enterprise Python. The Anaconda AI Platform empowers organizations to leverage open source as a strategic business asset, providing the essential guardrails that enable responsible innovation while delivering documented ROI and enterprise-grade governance capabilities. The Anaconda AI Platform enables enterprises to build once and deploy anywhere safely and at scale. Anaconda saw a 119% ROI and $1.18M in benefits within three years, with improved operational efficiency (80% improvement worth $840,000, according to the Forrester study) and enterprise-powered security (Anaconda provided an 80% reduction in time spent on package security management and a 60% reduction in security breach risk, according to the Forrester study). The Anaconda AI Platform eliminates environment-specific barriers, enabling teams to create, innovate, and run AI applications across on-premise, sovereign cloud, private cloud, and public cloud on any device without reworking code for each target. The platform is now available on AWS Marketplace for seamless procurement and deployment. Additional features include: Trusted Distribution; Secure Governance; Actionable Insights
Parasoft’s agentic assistant automates generating API test scenarios using service definition files while also parameterizing for data looping
Parasoft has added Agentic AI capabilities to SOAtest, featuring API test planning and creation. Parasoft also has enhanced its Continuous Testing Platform (CTP), extending Test Impact Analysis (TIA) and code coverage collection to manual testers, further reducing technical barriers, accelerating feedback, and improving collaboration between development and quality. Parasoft SOAtest’s AI Assistant now utilizes agentic AI in API test-scenario generation, making it easier for testing teams with diverse skill sets to adopt API test automation. This release now enables a tester to, in natural language, request the AI to generate API test scenarios using service definition files. Going beyond simple test creation, the AI Assistant leverages AI agents to generate test data and parameterize the test scenario for data looping. Complex, multi-step workflows with dynamic data are handled in collaboration with the user, allowing less technical testers to build complicated tests without requiring scripts, advanced code-level skills, or in-depth domain knowledge. In addition to reducing technical burdens, Parasoft’s AI Assistant will help customers scale API testing and automate other in-product actions. As additional agents are introduced over time, it will produce even smarter test scenarios and workflow guidance. QA teams can leverage Parasoft CTP to collect and analyze code coverage from manual test runs, then publish that coverage into Parasoft DTP for deeper analysis. In CTP, the tester can easily create a manual test case, and with a few clicks can ensure code coverage is captured during their test runs. With this visibility, teams can fine-tune their manual testing efforts—eliminating redundancies, filling coverage gaps, and focusing on the highest-risk areas. Teams can now create, import, and manage manual tests directly in CTP, capture code coverage as those tests run, and utilize that data in test impact analysis to pinpoint exactly which manual regression tests need to be rerun to validate application changes. This trims retesting time and effort, reducing testing fatigue while strengthening collaboration between development and QA teams. This new capability also makes it easier to adapt manual regression testing for agile sprints, as it allows teams to only focus on impacted areas. With faster test cycles, QA teams can quickly validate changes and shorten feedback loops.
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.
Vectara offers to reduce hallucination rates in enterprise AI systems to about 0.9%; provides detailed explanation for factual inconsistency along with a corrected version
AI agent and assistant platform provider Vectara launched a new Hallucination Corrector directly integrated into its service, designed to detect and mitigate costly, unreliable responses from enterprise AI models. In its initial testing, Vectara said the Hallucination Corrector reduced hallucination rates in enterprise AI systems to about 0.9%. The HHEM scores the answer against the source with a probability score between 1 and 0, where 0 means completely inaccurate – a total hallucination – and 1 for perfect accuracy. HHEM is available on Hugging Face and received over 250,000 downloads last month, making it one of the most popular hallucination detectors on the platform. In the case of a factually inconsistent response, the Corrector provides a detailed output including an explanation of why the statement is a hallucination and a corrected version incorporating minimal changes for accuracy. The company automatically uses the corrected output in summaries for end-users, but experts can use the full explanation and suggested fixes for testing applications to refine or fine-tune their models and guardrails to combat hallucinations. It can also show the original summary but use corrections info to flag potential uses while offering the corrected summary as an optional fix. In the case of LLM answers that fall into the category of misleading but not quite outright false, the Hallucination Corrector can work to refine the response to reduce its uncertainty core according to the customer’s settings.
Web browsers, by including agentic AI capabilities (capable of understanding context, automating and executing multi-step tasks), can access information without any tabs, clicking or scrolling
From Netscape to Chrome, browsers are digital windows to the world. But that era is potentially poised to quickly circle the drain as AI comes to control a greater share of the flow of information. ChatGPT.com is now the fifth-most visited website in the world, with Google.com on top, followed by YouTube, Facebook and Instagram. The news that Perplexity is developing its own web browser, Comet, that is expected to include agentic AI capabilities and the ability to automate certain tasks, is already showing that how users find things, how they buy things and even how they know things, could increasingly be up for grabs. Instead of opening a browser window and typing a URL, users may soon speak or text a request into an agent that goes out, searches the internet and delivers what they need. No tabs, no clicking and no endless scrolling. That, at least, is the envisioned future. The whole concept of a web browser may be absorbed into an ecosystem of intelligent, personalized, persistent AI agents. The advent of the agentic AI web experience could mark a transformative period in how users access and interact with information online. At the heart of the potential evolution are large language models (LLMs) like OpenAI’s GPT-4, Google’s Gemini and Anthropic’s Claude. These systems are increasingly capable of understanding context, maintaining memory and executing multi-step tasks. But true agency requires more than linguistic prowess. Integration is key. APIs now serve as conduits through which AI agents interact with apps, services and devices. If AI agents are making purchasing decisions, traditional advertising strategies could falter. SEO, influencer marketing and even visual design may lose relevance if AI agents bypass websites in favor of direct API transactions. Brands will need to pivot, optimizing not for human attention but for AI interoperability. The AI browser wars have begun, and the outcome will shape the future of the digital landscape.
SavvyMoney acquires integration solution CreditSnap to bring credit scores, personalization and fin literacy to more LoS platforms
SavvyMoney announced its acquisition of CreditSnap, a fintech solution provider that powers intelligent integrations to digital loan, deposit and account onboarding solutions for banks and credit unions. With CreditSnap’s technology, we aim to strengthen our ability to work alongside existing LOS and account opening systems, delivering even greater value to our partners and their consumers. JB Orecchia, president and CEO of SavvyMoney said, By combining SavvyMoney’s ability to drive high-intent demand with CreditSnap’s flexible integration solution, we’re delivering a comprehensive digital experience for both lending and deposit growth—one that works with, not against, their existing systems. Financial institutions can now offer a seamless, end-to-end experience by leveraging SavvyMoney’s demand-generation capabilities in conjunction with CreditSnap’s flexible integration process. From personalized credit insights to frictionless application and booking, allowing every integration to work with one unified platform. CreditSnap Key Benefits: The platform integrates with more than 73 loan origination, core and digital banking systems; Loan application time can be reduced from 12 minutes to as little as 2 minutes; Financial institutions have reported a 20–40% increase in loan volume and deposit funding rates as high as 78%
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” for leads from data aggregators, such as 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.
Cleo partners with Paystand to automate B2B payments- integrating the creation of sales orders, invoices, order-to-cash and accounts receivable (AR) processes directly with ERP, CRM, eCommerce, and accounting systems
Cleo announced a strategic partnership with Paystand, a B2B payments solution provider that works largely with retailers, manufacturers, distributors, and software vendors. Paystand can help retailers, manufacturers, distributors and software vendors automate their order-to-cash and accounts receivable (AR) processes, letting them collect revenue faster. Todd Kibisu, Channel Account Manager at Paystand. “Cleo’s platform automates the creation of sales orders and invoices in our customers’ ERP systems, and Paystand seamlessly takes over at this point by automating AR processes through the reconciliation of funds. Together, we’re enabling businesses to save time, reduce costs, and unlock new growth opportunities.” Through this collaboration, Paystand also delivers ecosystem integration to customers, offering: Streamlined Operations: Eliminate manual data entry for AR tasks and integrate directly with ERP, eCommerce, and accounting systems. Enhanced Visibility: Comprehensive views of payment transactions, improving tracking, reducing fees, and mitigating risks. Improved Customer Experience: Integration with CRM systems enables better customer support, communication, and overall management.