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By K Raveendran Cockroach Janta Party may have begun as satire, but its popularity has exposed something far more serious than a passing joke on the internet. The response it has drawn from government functionaries suggests that the ruling establishment is less disturbed by the humour itself than by the possibility that the satire has […]

The article Cockroach Party Exposes A Deeper Political Unease Among New Generation appeared first on Latest India news, analysis and reports on Newspack by India Press Agency).

Revenue Up 35.4% Year-on-Year API Token Call Volume Surges Nearly 6 Times

HONG KONG SAR – Media OutReach Newswire – 22 May 2026 – Phancy Group Co., Ltd. (“Phancy” or “The Company”, stock code: 6682.HK), a leading general artificial intelligence company, today announced its unaudited consolidated results for the first quarter ended 31 March 2026.

During the period, Phancy achieved revenue of approximately RMB1.458 billion, representing a 35.4% year-on-year increase. Gross profit margin remained at 35.1%. Phancy leveraged its deep expertise in full-stack AI cloud services, to capitalize on the accelerating adoption of localized computing power and strong enterprise demand for AI solutions. The Company achieved robust growth in its core businesses, accelerated product innovation, and secured several major partnerships, sustaining strong operational momentum.

2026 First Quarter Business Highlights:

Unified Enterprise AI Platform Drives Explosive Core Business Growth

Global computing resources remain constrained, while demand for both private enterprise AI deployments and API-based model calls continues to grow rapidly. Phancy’s enterprise-grade AI platform is built on a unified core architecture that seamlessly supports both API calling scenarios and dedicated private deployments. This significantly boosts AI application efficiency and resource utilization. Supported by a mature computing power supply chain developed over many years, Phancy’s deployable computing power resources have increased by over 200%. This enables the Company to effectively meet surging Token demand and consistently deliver stable, high-quality AI services to its customers.

In the first quarter of 2026, API Token call volume surged nearly 6 times compared to the same period in 2025, and already accounted for nearly 40% of the full-year 2025 total. Meanwhile, the Agentic AI business expanded rapidly, with deepening commercial adoption. Orders on hand grew nearly 100% compared to the end of 2025, emerging as a major growth driver for the Company.

AI Technology Iteration Accelerates, Commercialization Beats Expectations

Building on its continued push into digital employee applications and AI empowerment across business units, Phancy has significantly shortened the product development cycle from R&D to commercialization, enhancing overall operational efficiency and customer satisfaction.

As of mid-May 2026, ModelHub XC has completed adaptation and optimization for over 70,000 AI models on domestic chips, achieving more than 70% of its full-year target – well ahead of schedule.

In May, Phancy launched PhanthyMovie, a professional-grade AI video generation platform designed to enhance creativity, control, and stability in video production, enabling standardized and large-scale content creation for the industry.

Leveraging its advanced technology and proven execution capabilities, PhanthyMovie achieved rapid commercial traction. Just days after launch, the Company entered into a strategic cooperation agreement with Huanxi Media, covering approximately US$200 million in AI Token usage. The two parties will also collaborate on the development of a next-generation AI-powered film and television content production platform, further strengthening Phancy’s position in the AI-driven cultural and creative sector.

Core Products Align Closely with Policy Trends, Strengthening Compute-Model Integration

Since May 2026, China’s AI sector has seen a series of positive policy developments focused on computing infrastructure, data element circulation, and open-source compliance governance. Phancy’s core products, including HAMi vGPU and ModelHub XC, are well-aligned with national policy directions and mainstream industry trends.

In terms of computing resource allocation, policies emphasize cross-regional collaboration and broader access to computing power. Phancy’s HAMi vGPU offers unified scheduling and fine-grained resource partitioning, effectively improving utilization rates, optimizing data center energy efficiency, and supporting unified management across multiple chips to boost single-card efficiency.

In data and model governance, the government continues to promote high-quality dataset development and compliance management. ModelHub XC supports multi-model adaptation and optimization, incorporates data traceability and security certification features to help enterprises reduce compliance risks, and uses the EngineX engine for batch adaptation of domestic chips and models. This significantly improves compatibility while enhancing Token output efficiency through targeted model tuning.

Through deep integration of its computing and model layers, Phancy has built a comprehensive “Compute–Model” integrated solution. This addresses key industry needs such as efficient computing utilization, secure data supply, enterprise compliance, and domestic substitution, while strengthening its technological moat. The Company is well positioned to capture policy dividends and industry opportunities, supporting enterprises in their digital and intelligent transformation.

Hashtag: #PhancyGroup

The issuer is solely responsible for the content of this announcement.

About Phancy Group

Phancy Group (6682.HK) is a leading full-stack AI cloud services platform, providing comprehensive solutions for the AI 2.0 era. Our offerings include SageAIOS, HAMi vGPU and ModelHub XC, delivering efficient and scalable AI infrastructure with end-to-end capabilities. We provide a complete solution from heterogeneous compute resource management and optimization to the deployment of intelligent agent models. These solutions empower digital transformation across a wide range of industries, supporting our vision of building a large-scale and efficient “Token Factory.”

Guided by the mission of “AI for Everyone” and positioned as the “Navigator of AI,” Phancy Group is committed to becoming a global leader in Artificial General Intelligence.

Dr. Chana Poomee, Honourary Chairman of TCMA and President of ASEAN Federation of Cement Manufacturers (AFCM), stated that today’s “National Milestone” reflects the power of collaboration at both national and international levels. The initiative is led by the United Nations Industrial Development Organization (UNIDO), in partnership with TCMA and key Thai government agencies, including the Department of Climate Change and Environment and the Department of Industrial Works, with financial support of CAD 8 million from the Government of Canada through Environment and Climate Change Canada (ECCC), to accelerate tangible greenhouse gas reductions in the cement and concrete sector.

TCMA, as the industry representative, serves as a central platform connecting stakeholders across the entire value chain, driving the implementation of the “Thailand 2050 Net Zero Cement and Concrete Roadmap.” This aligns with Thailand’s NDC 3.0 targets, strengthening industrial competitiveness, attracting green investment, and fostering sustainable economic growth.

“Decarbonization is not only a pressing challenge but also a strategic opportunity to enhance national competitiveness. The progress achieved under this project spans policy development, innovation, technology deployment, standards, and capacity building-key enablers that will accelerate the industry’s transition toward Net Zero”, Dr. Chana said.

A key technological advancement under the project is the introduction of the Mobile Carbon Capture Unit (MCCU) from CETRI, Canada. This advanced and flexible technology is designed for real-world industrial operations and will be piloted starting in June, rotating across cement plants of TCMA members in the SARABURI SANDBOX. The pilot aims to validate performance under diverse operational conditions and pave the way for large-scale industrial application.

“The deployment of MCCU in Thailand highlights the strength of international collaboration in bringing advanced technologies into real-world application. It accelerates learning-by-doing, validates technological performance, strengthens local technical capabilities, and reduces investment risks-laying a strong foundation for future scale-up”,
Dr. Chana added.

From an investment perspective, the development of technology-ready and standards-aligned projects enhances investor confidence, increases the attractiveness of green investment, and improves access to sustainable finance-key drivers in accelerating the industry’s transition to Net Zero.

TCMA continues to advance the industry under a “Collaborative Mindset-Action-Value,” promoting the systematic adoption of low carbon technologies, including low carbon cement innovations such as Limestone Calcined Clay Cement (LC³), Carbon Capture, Utilization and Storage (CCUS). These solutions not only reduce emissions but also improve efficiency, lower long-term costs, and strengthen global competitiveness.

At the regional level, TCMA is expanding its role through AFCM by fostering collaboration and advancing the AFCM Decarbonization Roadmap, which serves as a shared framework to reduce carbon emissions across ASEAN’s cement industry while enhancing regional technology, standards, and competitiveness.

“As President of the AFCM, TCMA is committed to driving ASEAN toward becoming a low carbon region by leveraging collaboration as a key mechanism to accelerate technology transfer, strengthen the industry capabilities, and unlock new regional economic opportunities”,
Dr. Chana said.

TCMA reaffirmed its commitment to strengthening collaboration and welcoming international support in both technology and finance to accelerate the transition toward a low carbon industry, while enhancing Thailand’s competitiveness on the global stage.

Hashtag: #TCMA #CementActionToNetZero #NetZero2050 #Decarbonization

The issuer is solely responsible for the content of this announcement.

A 2026 software supply chain security assessment shows that about 65 per cent of organisations in India cannot detect malicious packages, while 71 per cent do not use container security tools. The findings underline a widening gap between the speed of AI-led software development and the controls needed to secure code, dependencies, models and deployment pipelines before they reach production systems.

Security teams are facing a more complex threat environment as AI coding assistants, model registries, agent frameworks and machine-learning libraries become embedded in day-to-day software engineering. AI is no longer confined to application features or analytics layers. It is becoming part of the software supply chain itself, influencing how code is written, tested, packaged and deployed.

Enterprises in India have been quick to adopt AI tools to improve developer productivity, reduce repetitive work and accelerate product releases. Yet the same shift has increased reliance on open-source packages, pre-trained models, plug-ins and automated build systems. Each of these components can introduce hidden risks if provenance, integrity and behaviour are not continuously verified.

Global software repositories are now attracting sustained attacks because they provide a direct route into enterprise development environments. Malicious npm packages rose by 451 per cent during 2025, while more than 48,000 new Common Vulnerabilities and Exposures were disclosed worldwide, a rise of about 20 per cent from the previous year.

The pressure on security teams is being amplified by the volume of AI-generated code. Developers in India are spending about 51 per cent of their time reviewing, validating and hardening code produced by AI tools. About 53 per cent treat such output only as a starting point and review every line before use, while 11 per cent rewrite AI-generated fixes from scratch.

This shift has altered the economics of software engineering. AI may reduce the time needed to draft code, but it can also transfer effort to verification, testing and security review. Weaknesses such as cross-site scripting, SQL injection and missing authorisation checks can still be reproduced by automated tools, particularly when developers rely on generated code without adequate scrutiny.

Governance is emerging as another area of concern. Nearly 97 per cent of organisations surveyed said they had certified AI model governance programmes, but only 59 per cent claimed full provenance visibility across production environments. About 48 per cent still needed a week or longer to produce audit-ready compliance evidence.

That gap points to a difference between policy and enforceable control. Many enterprises have AI governance frameworks on paper, but fewer can prove where every model, library, container image and software artefact came from, how it changed, who approved it and whether it complies with internal policy.

CERT-In has also warned that software supply chain compromises are increasingly targeting developer tools and trusted repositories. Its April 2026 activity note referred to attacks affecting npm, PyPI, GitHub Actions and container registries, including incidents involving Checkmarx, Trivy, LiteLLM, Axios, Telnyx and npm packages linked to the CanisterWorm campaign. The payloads observed in these attacks included credential harvesting, data exfiltration, remote execution and persistence within developer systems.

Model registries have added another layer to the risk. Around 1.4 million new AI artefacts were published on Hugging Face during 2025, representing 58 per cent of all new software packages tracked in one assessment. Researchers identified 495 malicious AI models in public repositories with active payloads capable of credential theft, command execution and reverse-shell activity, along with 969 malicious AI-agent skills designed to exploit developer environments and automation workflows.

For enterprises in India, the challenge is sharpened by the country’s role as a major software engineering and global capability centre hub. Bengaluru, Hyderabad, Pune, Chennai and Gurugram host large engineering teams serving banking, retail, telecoms, manufacturing and cloud services. These centres are increasingly responsible not only for maintenance work but also for product development, AI integration and security-sensitive digital platforms.

Regulatory and customer expectations are also tightening. Buyers are asking for software bills of materials, vulnerability disclosure processes, provenance records and proof that build pipelines are protected. CERT-In’s technical guidance on SBOM, QBOM, CBOM, AIBOM and HBOM has emphasised regular updates, vulnerability exploitability exchange documents and staff training around software supply chain visibility.

Security leaders are therefore moving towards stronger controls across development pipelines. These include automated malicious package detection, container image scanning, secrets detection, signed artefacts, dependency pinning, model provenance checks, policy enforcement in CI/CD systems and continuous monitoring of developer environments.

The investment case is becoming harder to ignore. Software supply chain attacks can bypass perimeter defences because they enter through trusted development channels. Once inside, malicious packages can steal credentials, alter builds, move into cloud environments or compromise downstream customers. AI raises the stakes because it can accelerate both legitimate development and attacker experimentation.

The investment is designed to strengthen the chipmaker’s partnerships with foundries, packaging houses, substrate suppliers and server manufacturers that are central to its next generation of AI systems. The programme places Taiwan at the centre of AMD’s effort to scale production of high-performance processors, accelerators and rack-level systems built for increasingly complex AI workloads.

A major focus will be Elevated Fanout Bridge, or EFB, a 2.5D packaging technology intended to improve the speed and efficiency of connections between chip components. AMD plans to use the technology in its sixth-generation EPYC central processing units, codenamed “Venice”, which are being positioned for AI, cloud and high-performance computing deployments.

The move comes as AI infrastructure spending shifts from individual chips towards complete systems that combine CPUs, graphics processors, high-bandwidth memory, networking and software. Advanced packaging has become a critical bottleneck because AI workloads require large volumes of data to move quickly between processors while keeping power consumption and heat within manageable limits.

AMD Chair and Chief Executive Lisa Su said customers were rapidly expanding AI infrastructure to meet rising compute demand. The company is seeking to combine its high-performance computing portfolio with Taiwan’s manufacturing and packaging capabilities to support integrated, rack-scale AI systems.

AMD is working with partners including ASE, SPIL, Powertech Technology, Wiwynn, Wistron, Inventec, Unimicron, AIC, Nan Ya PCB and Kinsus. These companies cover key parts of the supply chain, from advanced packaging and substrates to server assembly and mechanical architecture. Sanmina is also involved in manufacturing support for the company’s Helios platform.

The investment will support both wafer-based and panel-based EFB interconnect development. AMD and Powertech Technology have qualified what they describe as the industry’s first 2.5D panel-based EFB interconnect, a step aimed at improving scalability and production economics for high-volume AI processors.

The technology is expected to help the “Venice” EPYC processors deliver higher interconnect bandwidth and better power efficiency. That matters because data centre operators are increasingly constrained by electricity availability, cooling capacity and rack density, not only by chip performance.

AMD has also begun ramping production of “Venice” CPUs using Taiwan Semiconductor Manufacturing Company’s 2-nanometre process technology in Taiwan. Future production is planned at TSMC’s Arizona facility, extending the supply chain beyond Taiwan while preserving the company’s close reliance on TSMC’s leading-edge manufacturing.

The “Venice” chips will be a central element of AMD’s Helios rack-scale platform, which also includes AMD Instinct MI450X graphics processors, advanced networking and the ROCm open software stack. The platform is scheduled for deployments beginning in the second half of 2026, with AMD describing the opportunity in terms of multi-gigawatt AI infrastructure rollouts.

The strategy puts AMD in a more direct contest with Nvidia, which dominates AI accelerator sales and has built a strong lead through its GPUs, networking, software ecosystem and full-rack systems. AMD’s challenge is not only to deliver competitive silicon but also to prove that it can scale complete AI infrastructure with dependable supply, efficient packaging and broad software support.

AMD’s data centre business has become the company’s main growth engine. First-quarter 2026 data centre revenue reached $5.8 billion, up 57 per cent from a year earlier, driven by demand for EPYC processors and the ramp-up of Instinct GPU shipments. That performance has strengthened investor expectations that AMD can capture a larger share of AI and cloud infrastructure spending.

Taiwan remains critical to that effort because of its concentration of semiconductor expertise. TSMC anchors the foundry side, while packaging, substrate and system-assembly partners provide the manufacturing depth needed to turn chip designs into deployable infrastructure. The concentration also creates geopolitical and supply-chain risks, particularly as governments and companies seek greater resilience across strategic technologies.

The New York-founded company, led by Shayne Coplan, is seeking to open discussions around whether event-based contracts can be permitted under Japan’s financial and digital-asset framework rather than treated purely as gambling. The move comes as prediction markets draw heavier institutional interest, stronger trading volumes and sharper scrutiny from regulators over consumer protection, market integrity and the legal boundary between betting and derivatives.

People familiar with the matter said the company’s Japan strategy is at an early stage and would require engagement with officials, lawmakers and industry participants before any formal market entry. Japan does not have a dedicated framework for cash-based prediction markets, leaving platforms that allow users to trade on political, economic, sports or cultural outcomes exposed to uncertainty under gambling and financial laws.

Polymarket allows users to buy and sell contracts tied to the outcome of real-world events, with prices reflecting market-implied probabilities. Its markets have covered elections, central bank decisions, geopolitical events, sports, entertainment and cryptocurrency milestones. The platform gained global visibility during the 2024 US presidential election cycle, when trading volumes surged and its odds were widely cited as an alternative gauge of political sentiment.

Japan would offer Polymarket a large, sophisticated retail market with deep participation in equities, foreign exchange and digital assets. The country has also built one of the world’s more structured crypto regulatory regimes, requiring registration for crypto-asset exchange service providers and imposing rules on custody, anti-money laundering controls and customer protection. That framework may give the company a potential route for engagement, although prediction markets remain a separate and more politically sensitive category.

The company’s global push has accelerated after a period of regulatory pressure in the United States. Polymarket settled a case with the Commodity Futures Trading Commission in 2022 after being accused of offering off-exchange event-based binary options without proper registration. It blocked US users for several years before moving to rebuild a domestic regulatory path through acquisitions and licensing efforts. Its purchase of a derivatives exchange and clearinghouse gave it a route to pursue compliant US operations.

Institutional backing has also strengthened its position. Intercontinental Exchange, the parent of the New York Stock Exchange, agreed to invest up to $2 billion in Polymarket in a deal that valued the business at about $8 billion before the transaction. The partnership gave Polymarket a powerful market infrastructure ally and signalled that event-driven data may have value beyond retail speculation, particularly for investors seeking real-time sentiment around political, economic and corporate developments.

Competition is intensifying. Kalshi, a regulated US prediction market operator, has expanded rapidly by framing event contracts as financial instruments under commodities law. Its growth has triggered legal disputes with state regulators, some of whom argue that sports and election-linked contracts resemble gambling products. That debate is likely to influence Japan’s assessment of whether prediction markets can be supervised as finance, gaming, information markets or a hybrid category.

Polymarket’s Japan plan faces several obstacles. Gambling is tightly restricted, with permitted activity largely confined to state-authorised sectors such as horse racing, bicycle racing, motorboat racing, lotteries and pachinko-linked structures. Online betting carries heightened enforcement risks, and any product involving wagers on uncertain outcomes would need careful legal classification. A crypto-funded model could add further complexity because regulators would need to examine custody, settlement, identity checks, sanctions screening and investor suitability.

Supporters of prediction markets argue that they create useful public signals by aggregating dispersed information into tradable prices. Traders who believe a market is mispriced can buy or sell contracts, pushing prices closer to collective expectations. That model has appealed to political analysts, hedge funds, economists and technology investors seeking faster indicators than polls, surveys or conventional research.

Critics counter that thin liquidity, anonymous participation, insider access and coordinated trading can distort outcomes. Questions have intensified around markets linked to sensitive events, where participants may possess non-public information or where the existence of a market could create troubling incentives. Japan’s regulators are likely to examine whether surveillance systems, position limits, disclosure rules and dispute-resolution mechanisms are strong enough to reduce those risks.