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Myrtle.ai Halves Latency in Financial Machine Learning Inference Benchmark Record with VOLLO

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CAMBRIDGE, England, April 29, 2026 /PRNewswire/ — myrtle.ai, a recognized leader in accelerating machine learning inference, today announced that a stack featuring its VOLLO® product has recently been audited by STAC®, a leading benchmark authority for the finance industry.[1] The results, unveiled at the STAC Summit in London today, clearly demonstrate the latency benefits of an FPGA-based solution for ML inference in financial trading and related applications.

STAC-ML (Markets) Inference is the technology benchmark standard for solutions that may be used to run inference on real-time market data. Designed by quants and technologists from some of the world’s leading financial firms, STAC-ML Markets (Inference) reports the performance, resource efficiency, and quality of any technology stack capable of performing inference using the provided models.

VOLLO achieved latencies as low as 2 microseconds (99th percentile) while also exhibiting excellent results in throughput and efficiency. Across all three benchmark models, VOLLO inferred in lower latency (99th percentile) than all previously audited systems, halving its previous record. Such low, deterministic latency enables users to make more intelligent decisions using more complex models faster than in the past, giving them a competitive advantage in trading, risk analysis, quotes and many other trading-related activities.

With hundreds of thousands of hours of production trading under its belt, VOLLO is generating alpha for many of the world’s leading trading firms today. Those firms have developed and trained a wide range of models in standard ML tool flows before compiling them into VOLLO and then running them on their choice of FPGA-based hardware platform.

In the system under test, VOLLO ran on the standard form factor FBAP4@VP18-2L0S PCIe accelerator card from Silicom, containing an AMD Versal™ Premium series VP1802 Adaptive SoC and installed in a Supermicro AS -2015CS-TNR server. The AMD Versal Premium Series Adaptive SoC provides PCIe Gen5x8 and more than 3.3M programmable LUTs, making it well suited to low latency inference applications.

“Since VOLLO first exploited the full potential of FPGAs in this STAC benchmark in 2023, we have worked with our customers to further reduce latencies, expand the variety and size of models that VOLLO can run, and grow the range of platforms it can run on,” said Peter Baldwin, CEO of myrtle.ai.  “We’re excited to work with AMD, Silicom and Supermicro on this benchmark, to demonstrate how our combined technologies can enable ultra-low latency AI inference in quant trading.”

“The future of financial markets will be shaped by AI systems that can interpret data and act on it in near real time,” said Girish Malipeddi, director for Data Center FPGA business, AMD. “With AMD Versal™ Premium series adaptive SoCs at the foundation, myrtle.ai’s VOLLO demonstrates how advanced, low-latency inference can help unlock a new generation of intelligent trading infrastructure.”

“Supermicro continues to address a wide range of markets with our AMD systems, which were used for this STAC-ML benchmark,” said Michael McNerney, Senior Vice President Marketing and Network Security, Supermicro. “Our servers address the most challenging workloads in the financial services industry, and together with partners, we are able to deliver top-end performance with very low latencies for machine learning workloads.”

Anders Poulsen, VP Solutions at Silicom Denmark, said: “We’re pleased that myrtle.ai selected Silicom’s Artena accelerator card, based on AMD Versal Premium, for these tests. Built around one of the largest FPGAs in a PCIe form factor, Artena is an ideal platform for VOLLO. Together, VOLLO and our low-latency hardware deliver deterministic, microsecond-level inference for demanding trading workloads.”

ML developers can evaluate today how their models could perform on VOLLO, without the need for any FPGA tools or expertise. For more details go to vollo.myrtle.ai or contact myrtle.ai today at fintech@myrtle.ai.

The full benchmark results are available in the STAC Report (SUT ID MRTL260323) at http://www.STACresearch.com/MRTL260323.

About myrtle.ai

Myrtle.ai is an AI/ML software company that delivers world-class inference accelerators on FPGA-based platforms from all the leading FPGA suppliers. With broad neural network expertise, myrtle.ai has delivered accelerators for applications including fintech, wireless telecoms, LLMs, speech processing, and recommendation.

VOLLO, VOLLO Accelerator and the VOLLO logo are registered trademarks of myrtle.ai.

“STAC” and all STAC names are trademarks or registered trademarks of the Strategic Technology Analysis Center, LLC. AMD, the AMD logo, Versal, and combinations thereof are trademarks of Advanced Micro Devices, Inc. 

[1] www.STACresearch.com/MRTL260323

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SOURCE Myrtle.ai

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Zifo Transforms Ontology Engineering with AI-Powered Intelligent Automation

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Advanced AI solution speeds up ontology creation by 80%, generating structured, interoperable knowledge models for science-driven organizations.

CAMBRIDGE, Mass. and CAMBRIDGE, England, April 30, 2026 /PRNewswire/ — Zifo, the leading global enabler of AI and data-driven enterprise informatics for science-driven organizations, has developed an Intelligent Automation solution for Ontology Engineering, which is designed to seamlessly generate structured, interoperable knowledge models while accelerating ontology creation by 80%.

Overcoming the Bottlenecks of Manual Ontology Creation

Manual ontology creation in the biopharma industry has traditionally been a time-consuming process that requires specialized expertise. Organizations frequently struggle with semantic ambiguity, complex integration challenges, and limited scalability, resulting in workflows that can take weeks to complete. Zifo’s AI-powered automation tackles these challenges head-on by eliminating 80% of the manual work through automated class generation, description creation, and precise IRI mapping.

Addressing the Complexities of Semantic Knowledge

Developing comprehensive knowledge models often demands deep domain expertise to define relationships and align terminology. Zifo’s intelligent solution overcomes this by providing an AI-guided workflow featuring an intuitive interface, meaning specialized ontology engineering knowledge is no longer required. By leveraging LLM-powered generation, the solution creates precise definitions with a deep understanding of domain-specific context, while generating standardized synonyms and establishing controlled vocabulary alignment to eliminate inconsistent terminology.

A Solution Designed for Scalable Scientific Data Modeling

The AI-powered solution addresses critical format compatibility and integration points in ontology management:

Seamless Integration: Automated mapping connects directly to established ontologies, including NCIT, CHEBI, OBI, and EFO, via BioPortal and OLS APIs.Massive Scalability: Parallel processing and batch operations empower teams to execute large-scale ontology projects without performance limitations.Automated Hierarchies: The AI autonomously generates semantic relationships and parent-child hierarchies based on domain context and predefined relation vocabularies.Format Compatibility: The solution produces direct OWL/RDF exports with proper URIs, ensuring seamless downstream integration.

Unique Features include:

Multi-Source Integration: The solution combines BioPortal, OLS, and EMBL-EBI APIs to guarantee comprehensive ontology coverage.Intelligent Ranking System: The system uses AI-powered relevance scoring and justification for precise ontology mappings.Precise IRI Mapping: It ensures that each generated class is linked to the correct IRI, directly promoting semantic web compatibility.Human-in-the-Loop Design: The solution automates repetitive tasks while maintaining vital expert oversight.End-to-End Workflow: Users are guided through a complete pipeline, from initial domain knowledge input straight to exportable OWL files.Visual Knowledge Graph: An interactive graph visualization allows for intuitive relationship exploration and validation.Multi-Format Exports: Provides seamless export options in CSV, OWL, or HTML Ontograph formats for downstream use, collaboration, and visualization.

Strategic Value Across the Scientific Chain

This solution breaks down the traditional barriers of data structuring. Built on a robust backend of Python, LangChain, and leading LLM models, alongside a frontend framework using Next.js 15 and Cytoscape.js for graph visualization, the solution is highly adaptable. Furthermore, future optimization enhancements will include provisions for uploading user-defined classes or semi-ready ontologies.

About Zifo

Zifo is the leading global enabler of AI and data-driven enterprise informatics for science-driven organizations. With expertise spanning research, development, manufacturing, and clinical domains, Zifo serves a diverse range of industries including Pharma, Biotech, Chemicals, Food and Beverage, and more. Trusted by over 190 organizations worldwide, Zifo is the partner of choice for advancing digital scientific innovation.

For more information, visit www.zifornd.comhttps://zifornd.com/practical-ai-blueprints/

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SOURCE Zifo Technologies

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UNC-Chapel Hill establishes ‘Carolina in the Capital’ with new Washington, D.C. office

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CHAPEL HILL, N.C., April 30, 2026 /PRNewswire/ — The University of North Carolina at Chapel Hill has opened a new office in Washington, D.C., establishing an expanded presence for the University in the nation’s capital and creating exciting opportunities for students, faculty, staff and alumni.

Located at 101 Constitution Avenue NW, the 10,861-square-foot space – coined “Carolina in the Capital” – will support a variety of functions, including educational programming for undergraduate and graduate students, alumni relations and engagement with government partners.

As a leading R1 university, UNC-Chapel Hill annually attracts more than $1.6 billion to the state’s economy to fund research that creates a better quality of life for all its citizens. More than 60% of UNC-Chapel Hill’s total research funding comes from federal sponsors with the majority of that federal funding coming from the National Institutes of Health (NIH), which is based in the Washington area.

“Carolina in the Capital is a state-of-the-art facility that reflects our commitment to creating experiential learning opportunities for our students and faculty,” said Chancellor Lee H. Roberts. “The space is designed as an immersive learning environment where students can translate classroom knowledge into hands-on experience, which has never been more important. The facility also strengthens our ability to support engagement between our staff, alumni, policymakers and partners.”

Supporting students participating in Carolina’s Washington-based academic programs is a priority. For years, students and faculty have relied on temporary or borrowed spaces across the city. The new office provides a permanent home where students can gather, learn and build community while living and studying in Washington. A robust schedule of classes and events will fill the space throughout the year.

The Washington, D.C. region is home to the largest concentration of out-of-state Carolina alumni anywhere in the country. The new office creates a dedicated space to strengthen those connections and support networking, mentorship, professional development and community-building among D.C.-based Tar Heels.

The space will also serve as a platform to bring Carolina’s research and academic expertise into closer conversation with policymakers, industry leaders and member organizations. Carolina is the nation’s 11th largest university in the country based on research volume with primary federal funding coming from NIH and the National Science Foundation (NSF), both based in the D.C. area. Carolina is a proud member of the Association of American Universities (AAU) and the Association of Public & Land Grant Universities (APLU), which are both based in Washington.

The office is funded entirely through the UNC-Chapel Hill Foundation and does not use any state appropriations.

You can view additional photos of the space here.

Media Contact: UNC Media Relations, 919-445-8555, mediarelations@unc.edu

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SOURCE University of North Carolina at Chapel Hill Office of Communications

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Investing.com Acquires Stonki to Accelerate Its Entry into the Agentic AI Era

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The acquisition strengthens Investing.com’s AI capabilities, advancing a next-generation research assistant that can analyze markets, generate insights, and guide investors in real time

NEW YORK, April 30, 2026 /PRNewswire/ — Investing.com, one of the world’s largest financial platforms used by more than 60 million investors each month, today announced the acquisition of Stonki, an AI-powered investing assistant designed to help traders turn ideas into structured, actionable trading plans.

The move marks a major step in the company’s evolution toward agentic AI, strengthening its ability to deliver faster, deeper, and more actionable market insights to a growing base of more than 300,000 paying subscribers across its InvestingPro suite, the company’s premium subscription offering for advanced market data, tools, and AI-driven insights.

Over the past 12 months, nearly 3 million users have used WarrenAI, Investing.com’s AI-powered financial research assistant launched last year, to perform market analysis, making AI a central entry point into the platform’s ecosystem. With the addition of Stonki, the company is moving beyond traditional AI tools toward agentic systems that can proactively guide users through the investment process.

“We’re entering the age of agentic AI, where the technology moves beyond just answering questions to actively helping investors think, analyze, and act,” said Omer Shvili, CEO of Investing.com. “Bringing Stonki.ai into the fold accelerates our goal of building an agentic platform that will serve as a 24/7 analyst for our users. We are developing this to be more than just a tool; it will be a partner that identifies opportunities, tracks unfolding situations, and surfaces trade ideas even when the user isn’t active—giving our users the kind of edge that was previously only available to professional investors.”

Founded in 2025, Stonki is developing a new category of ‘agentic’ AI for investing, enabling users to turn investment ideas into fully defined strategies with entry and exit conditions, risk management rules, and continuous monitoring.

“We started Stonki because, as investors and traders ourselves, we knew how much time and focus it takes to stay on top of the market and properly manage a day trade, a swing trade, an investment idea, or a portfolio,” said Ulas Bilgenoglu and Itay Verkh, co-founders of Stonki. “We set out to build AI that could carry part of that load by continuously monitoring the market, turning ideas into structured strategies, and helping users make better decisions with clear entry and exit conditions, disciplined risk management, and ongoing tracking. Joining Investing.com gives us the scale, data, reach, and strong AI foundation to accelerate that vision. Together, we can create an experience where AI helps users stay ahead of the market, manage risk, and act with greater confidence.”

The acquisition expands Investing.com’s AI capabilities across both technical and fundamental investing workflows. Stonki’s technology is built around persistent, real-time intelligence, continuously monitoring markets, tracking user-defined strategies, and alerting investors when conditions align, rather than relying on one-off prompts or static analysis.

For active traders, the platform is evolving into a real-time analysis engine designed to support high-frequency decision-making with precision and speed. For long-term investors, it is becoming a central hub for research, enabling users to evaluate opportunities, set personalized alerts, and monitor portfolios based on their individual investment strategies.

Users will be able to define specific conditions, such as a stock crossing a long-term moving average, and have the AI continuously monitor the market, analyze relevant signals, and surface actionable insights in real time. The system will also review portfolios on an ongoing basis, helping investors avoid potential losses and uncover new opportunities aligned with their strategy.

This latest step builds on Investing.com’s broader strategy of expanding its AI-powered suite, including WarrenAI, ProPicks AI, and its recently launched AI Chart Analysis, all aimed at delivering faster, more accurate and more actionable insights to investors.

View original content:https://www.prnewswire.com/news-releases/investingcom-acquires-stonki-to-accelerate-its-entry-into-the-agentic-ai-era-302756588.html

SOURCE Investing.com

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