Trader Follows 2024 Record With 252% Gain; Plans Broader Investor Education Push
NEW YORK, Feb. 26, 2026 /PRNewswire/ -- Law Wai-Sum, a Hong Kong trader known as J Law, is expanding his investment education business, JLawStock, to the International market after posting a record 1,499% cumulative return over two years in the top division of the United States Investing Championship.
Law followed a 353.9% gain in 2024 with a 252.3% return in 2025, securing first place in the division for a second consecutive year. Over the same two-year period, the S&P 500 advanced about 47%, based on data published by the competition.
Founded in 1983, the annual championship tracks verified real-money accounts across multiple categories and publishes audited performance rankings. Organizers said 579 participants entered the 2025 event. Law competed in the Money Manager Verified Ratings division, which requires a minimum starting balance of $1 million.
In an interview, Law attributed the results to disciplined execution.
"Most people focus on finding a magic strategy," he said. "What makes performance repeatable is a process that reduces costly mistakes and puts risk control first."
Law said individual investors can improve results by adhering to three principles: reducing trade frequency to reduce execution mistakes and transaction costs; adapting established frameworks to personal constraints such as time availability and risk tolerance; and adjusting tactics as market conditions evolve.
"A strategy that performs in one environment may underperform in another," he said.
Law, who trades U.S. markets from Asia, also said time differences are not the primary challenge.
"Time zones aren't the real issue — emotional trading is," he said. "Success depends on preparation and identifying favorable risk-reward setups before the opening bell."
Following the competition, Law said he plans to expand his investor education business, JLawStock, from Singapore, including the development of English-language materials and structured analytical frameworks aimed at investors in North America, Europe, the Middle East and Southeast Asia.
JLawStock offers structured trading frameworks for retail investors. Its curriculum emphasizes professional trading techniques, discipline and the mindset required for long-term market participation. The programs have attracted full-time traders, financial influencers, and fund managers.
"I want to raise the standard of investment education," Law said. "Empowering investors with a professional-grade process is my next mission."
About the United States Investing Championship
Founded in 1983, the United States Investing Championship is a real-money investing competition that tracks participants' performance across multiple divisions and publishes annual standings.
About J Law
J Law (Law Wai-Sum) is a two-time winner of the United States Investing Championship $1,000,000+ Stock Division. He runs an investment education channel and develops training content focused on systematic decision-making, trend and momentum frameworks, and risk management.
Disclaimer:
This release is for informational and educational purposes only and does not constitute investment advice, an offer or a solicitation. Trading and investing involve risk, and past performance does not guarantee future results. J Law does not provide personalized investment recommendations or manage client funds.
Sources:
https://financial-competitions.com/
https://x.com/USICOfficial/status/2010490410171502877
** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **
J Law Sets Two-Year Record With 1,499% Return in U.S. Investing Championship
Unisound Unveils U1-OCR: The First Industrial-Grade Document Intelligence Model, Ushering in OCR 3.0 Era
BEIJING, Feb. 26, 2026 /PRNewswire/ -- Unisound has officially launched its Unisound U1-OCR, the world's first industrial-grade foundation model for document intelligence, a groundbreaking release that ushers in the OCR 3.0 era and sets a new industry standard with five core strengths: SOTA performance, verifiable results, out-of-the-box functionality, efficient deployment, and robust adaptability.
Document intelligence leverages AI to automatically read, understand, classify digitized documents and extract key information. OCR 1.0 only enabled basic text recognition, while OCR 2.0 added preliminary layout understanding capabilities. U1-OCR takes a quantum leap to OCR 3.0, moving far beyond layout recognition to deliver deep semantic insight, automatic document classification and business-level information extraction—marking a transformative shift from "character perception" to "document cognition".
As a SOTA-level document intelligence model, U1-OCR resolves the longstanding bottleneck of traditional models that "recognize text but fail to grasp layout", enabling it to interpret complex documents like human experts. It pioneers a "semantic-driven + dynamic focus" strategy, first mapping a document's hierarchical structure of headings and structural metadata before extracting content on demand, and builds a semantic map to identify the relationship between titles, charts and text—even in disorganized layouts. Its enhanced spatial alignment module leverages positional data to accurately restore document structure for dense tables and mixed text-image content, effectively mitigating spatial recognition errors. Equipped with Multi-Token Prediction technology and full-task reinforcement learning, it boosts reasoning efficiency by over 80%, ensuring logical coherence for long documents.
Trained with multi-task collaborative reinforcement learning and optimized for both semantics and coordinates, U1-OCR suppresses spatial hallucinations for reliable outputs, and achieves SOTA results across major authoritative benchmarks: scoring 95.1 in OmniDocBench V1.5, outperforming leading models like GLM-OCR and Gemini-3-Pro; hitting an F1 score of 90.8 in D4LA and 95.9 in DocLayNet, excelling in table recognition and cross-page association; and outperforming models such as Gemini-2.5-Flash and Qwen-2.5-VL in internal business tests, with standout performance in medical document processing such as admission and discharge records.
Built for real-world industrial applications, U1-OCR features four key capabilities that bridge the gap between document understanding and business action. Its proprietary "coordinate-text-semantics" architecture enables pixel-level positioning and full evidence traceability, making audit processes transparent and efficient. Integrated with Unisound's industry expertise in healthcare and finance, it achieves over 99% classification accuracy for more than 50 common business documents, supporting cross-field logical verification with zero-shot capabilities. It supports private on-premise and offline deployment while delivering highly efficient document processing, meeting strict data privacy requirements for government, healthcare, and finance sectors while lowering hardware costs. Most notably, it delivers stable, high-precision performance in extreme scenarios—including non-standard photos, blurred documents, complex formatting and multilingual text—freeing businesses from reliance on standardized document formats.
Validated in real-world use cases, U1-OCR enables visual traceability of extracted information, automatic classification of mixed documents, performing intelligent image purification for cluttered layouts, and accurate recognition of complex nested tables with full structural retention.
The launch of U1-OCR marks AI's evolution from simple text recognition to business logic comprehension, a key step for Unisound toward AGI. By taking multimodal documents as a knowledge entry point, Unisound is empowering machines with autonomous reasoning and evidence traceability capabilities, driving AI from perceptual intelligence to cognitive intelligence—with the vision to build a general intelligent agent that reads, thinks and solves complex problems like humans, turning every document into a stepping stone to AGI.
** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **
Unisound U1-OCR: The First Industrial-Grade Document Intelligence Foundation Model Ushering in the OCR 3.0 Era
