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Hitachi confirms practicality of Cryptocurrency AML Demonstration, new service launching in October. By: rootdata | 2026/07/30 02:30:37 Confirmation of Practicality in Cryptocurrency AML Demonstration Hitachi Ltd. announced on the 30th that it has conducted a demonstration experiment in collaboration with 17 companies, including financial institutions and cryptocurrency-related businesses, to verify the practicality of anti-money laundering (AML) measures in digital asset transactions involving cryptocurrencies, stablecoins, and NFTs. Based on these results, Hitachi will begin providing an AML monitoring service for digital asset transactions starting in October 2026. This demonstration tested a system for sharing information on suspicious transactions and high-risk wallets among businesses to facilitate initial responses, as well as a mechanism to monitor the circulation of tokens such as stablecoins to assess risks based on the flow of funds. This project was supported by the Financial Services Agency's "FinTech Demonstration Experiment Hub" and was conducted from March to May 2026. Contents of the AML monitoring service. Money laundering refers to the act of concealing the origins of funds obtained through criminal activities. While cryptocurrencies and stablecoins facilitate cross-border remittances, they are difficult to trace, raising concerns about their potential misuse for money laundering, as highlighted by regulatory authorities in various countries. The new service consists of three functions: "Post-Transaction Monitoring" for ongoing surveillance after transactions, "Online Instant Assessment" for evaluating the risk of counterpart wallets before transactions, and "Token Monitoring" for tracking the circulation status of issued tokens. In addition to known sanctions and crime-related lists and blockchain analysis, the service aims to complement risks that are difficult for individual businesses to grasp by combining AI and machine learning for similarity analysis of transaction behaviors. Hitachi has already conducted the first round of demonstration experiments with 12 companies from February to April 2025, and this is the second phase of that initiative. Moving forward, Hitachi plans to work with relevant parties to develop the concept of an "AML Joint Center" that integrates risk information across the industry, involving financial institutions and cryptocurrency businesses. This content is provided for general informational purposes only and doesn't constitute financial, investment, legal, or tax advice. Any events, rewards, online promotions, or related information mentioned herein should not be considered a recommendation, solicitation, or invitation to purchase, sell, trade, or otherwise deal in any crypto assets. Crypto assets are highly volatile and may result in loss. The availability of WEEX services, products, and related events may vary by region. You are responsible for ensuring that your participation is in accordance with applicable local laws and regulations.

Hitachi's 240x AI claim and its own 30% target. Hitachi says AI agents hit 240x productivity in requirements definition - then set a 30% companywide goal. Here's how to read AI productivity claims. Hitachi announced an AI platform yesterday with two numbers in it, and the gap between them is the whole story. On July 24 the company unveiled its Agentic AI Integration Platform, claiming up to 240x productivity in requirements definition and roughly 200x from design through testing. In the same announcement, Hitachi set its actual corporate goal: 30% productivity improvement across system integration by fiscal 2027. Both figures are true. Only one is a forecast anybody is accountable for. What actually happened. The platform applies task-specific AI agents across the full system integration lifecycle - external environment analysis, planning, requirements definition, design, coding, testing, and operations. It combines Hitachi's own integration expertise with frontier models from Anthropic, Google Cloud, and OpenAI, and its distinguishing feature is a knowledge base Hitachi calls "enterprise context": customer-specific operating know-how and decision criteria, accumulated and updated as projects move through development and into operations. Target sectors are finance, public administration, energy, and railways - places with a lot of legacy code and a shrinking supply of engineers who understand it. Hitachi is unusually straight about the caveat, and the Japanese coverage carries it: the 200x and 240x results were measured under specific internal conditions, and effect varies with project scale and characteristics. That's a vendor telling you its own headline number is a ceiling from a controlled setting. So the honest read is that a company with world-class integration talent, three frontier model vendors, and a purpose-built agent platform expects a 30% productivity gain company-wide - and it needs 18 months to get there. Why it matters for your business. Every AI productivity number you will read this year comes in one of these two flavors, and telling them apart is a skill worth developing. The 240x kind measures one narrow step under favorable conditions - often a step that was slow because it was waiting on a human's calendar, not because it was hard. Agents are genuinely spectacular at collapsing wait states. The 30% kind measures the whole pipeline, which still contains review, approval, rework, integration testing, and the meeting where someone says the requirement was wrong. You are buying the 30%. Price accordingly. Practically: before you adopt an AI coding or workflow tool, measure your own baseline on your own work - cycle time from ticket opened to merged and deployed, plus rework rate. Then run the tool for a month and compare the same two numbers. Not tokens, not lines generated, not developer vibes. If a vendor's pilot doesn't produce a before-and-after on a metric you already track, it produced a demo. And note what Hitachi built alongside the agents: the enterprise context layer. The reason their platform is worth anything is the accumulated institutional knowledge feeding it - decision criteria, operating know-how, why the system works the way it does. That's the part you can't buy. It's also the part most small businesses have never written down anywhere except in one person's head. Start there and the agents get better on their own. Key takeaways * Hitachi's Agentic AI Integration Platform, announced July 24, claims up to 240x productivity in requirements definition and ~200x from design through testing * Those figures were measured under specific internal conditions and vary by project - Hitachi says so directly * The company's actual accountable target is 30% across all system integration processes by fiscal 2027 * Narrow-step multipliers mostly collapse wait states; whole-pipeline gains land in the double digits, not the hundreds * Measure cycle time and rework rate before and after any AI dev tool - a pilot without a before-and-after is a demo Trying to figure out what an AI tool is actually worth to you? Rush Commerce benchmark your current process first, then build against that number - so the gain is provable, not promotional. Model it with its ROI calculator or bring Rush Commerce your numbers. * #ai-productivity * #ai-coding * #ai-agents * #benchmarks * #software-development Tommy Rush - Founder, Rush Commerce Operator turned builder. 15+ years running operations - now shipping the systems businesses run on. More Get The Rush Report weekly - one email, zero fluff.

Hitachi, Intel, and AIST launch government-backed silicon quantum computing project to advance Japan's quantum future. Last updated: July 24, 2026 11:23 am Japan has moved closer to becoming a global frontrunner in quantum computing as Hitachi, Intel K.K., and National Institute of Advanced Industrial Science and Technology (AIST) are set to conduct a government-funded research to develop next-generation quantum computing using silicon technology. The project is funded by Japan's New Energy and Industrial Technology Development Organization (NEDO) with the objective of developing silicon-based technologies for future quantum computers and bridging the gap between laboratory research and commercial applications of quantum computing. This is one of the several steps that Japan has been taking in order to become more self-sufficient in advanced computing, semiconductor chips, and artificial intelligence. This particular project, which will be ongoing until March 2029, is aimed at developing the core technologies for constructing scalable, fault-tolerant silicon-based quantum computers. Accelerating the industrialization of quantum computing. Unlike other quantum research efforts that concentrate only on experimental devices, Hitachi's research effort concentrates on technology needs for commercialization. The collaborating firms will work together to develop the design of silicon-based quantum chips comprising 100 qubits, semiconductor process technologies, package technologies, and cloud software development platforms, all of which would allow experimental quantum computers to be accessible by scientists and companies. Silicon-based quantum computing is increasingly gaining interest because it can take advantage of existing semiconductor process technologies, thus being more scalable than some other types of quantum computers. Four strategic development areas. The research initiative is organized around four major technology pillars designed to support future large-scale quantum systems. The first objective focuses on developing industrial-grade silicon quantum processors with approximately 100 qubits, incorporating improved chip architectures and cryogenic packaging technologies. Second, the project will create a Process Design Kit (PDK) that provides standardized design rules and manufacturing information, enabling engineers to design silicon quantum chips compatible with commercial semiconductor fabrication processes. Third, researchers will develop advanced 3D integration technologies capable of supporting future quantum systems with around 1,000 qubits, addressing the increasingly complex wiring and packaging challenges associated with larger processors. Finally, Hitachi and AIST will establish a cloud platform through AIST's Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), allowing researchers to remotely access experimental silicon quantum computing hardware and accelerate collaborative innovation. Roadmap toward practical quantum systems. The collaboration outlines an ambitious long-term roadmap extending beyond the initial research period. Hitachi will first roll out an initial cloud-based silicon quantum computing offering in the fiscal year 2027, followed by the development of a 100-qubit fault-tolerant quantum computing prototype through quantum error correction technology in the fiscal year 2028. Ultimately, Hitachi and Tohoku University hope to build a 1,000-qubit prototype in the fiscal year 2030, establishing a stepping stone towards future fault-tolerant quantum computing machines capable of handling practical industry issues. This serves as part of Japan's overall plan to establish their place in quantum technologies. Strengthening Japan's technology industry. This is a huge step for Japan in terms of developing its state-of-the-art technological ecosystem. Quantum computing will be the underlying technology for many industries such as pharmaceuticals, advanced materials, energy optimization, logistics, finance, and semiconductors. Through this technology investment in Japan, the country is capitalizing on its long-standing experience in the field of semiconductor production while generating new possibilities for the deep-tech industries. This effort will also boost the demand for semiconductor production, cryogenics engineering, cloud computing, HPC, AI integration, and quantum software development. Furthermore, this cooperation aligns with the plans of Japan to develop sovereign computing capabilities that will help Japan rely less on foreign quantum technologies. Business opportunities across industries. The commercialization of scalable quantum computing has the potential to transform numerous industries operating in Japan. Pharmaceutical companies could accelerate drug discovery through advanced molecular simulations, while manufacturers may optimize materials development and product design. Logistics providers could solve highly complex routing and supply chain optimization problems, and energy companies could improve power grid management through advanced optimization algorithms. Financial institutions are also expected to benefit from quantum-powered risk modeling, portfolio optimization, and fraud detection capabilities that exceed the performance of conventional computing systems. Technology vendors, cloud service providers, semiconductor manufacturers, and systems integrators will find growing opportunities as enterprises begin preparing quantum-ready infrastructure and software environments. Advancing Japan's leadership in deep technology. The partnership is based on the more extensive partnership agreement signed in early 2021 between Hitachi and Intel on quantum computing, semiconductor manufacturing, physical AI, and future digital infrastructure. Through combining the technological strengths of Hitachi and its knowledge of industrial and operational technology with the semiconductor manufacturing expertise of Intel, the two companies seek to make progress in implementing new computing technologies. As regards Japan's technology sector, this project that the government of Japan plans to undertake will serve as yet another landmark step in the overall innovative approach of the country. The development of quantum computing will provide Japan with an opportunity to be among the major centers for quantum technology in the world, while providing businesses engaged in AI, semiconductors, cloud computing, and advanced manufacturing with numerous business opportunities.