Artificial intelligence

Phishing messages target IndiaAI and Impact Summit 2026 participants

IndiaAI has issued an urgent advisory warning of a phishing campaign targeting attendees of the India AI Impact Summit 2026. Fraudulent SMS and WhatsApp messages claim refunds are pending and request sensitive financial details.

Organisers said the messages are not official and have not been authorised. Recipients are being urged to click links and provide full card numbers, WhatsApp numbers, and other contact information to ‘process’ refunds.

IndiaAI advised participants not to click suspicious links or share personal or banking information with unverified sources. Attendees in India are encouraged to delete such messages immediately and block the sender’s number.

Anyone who may have submitted details through a suspicious link should contact their bank without delay to secure their accounts. Organisers stressed that event-related communication will only be shared through official channels.

The advisory was issued under the AI Impact Summit 2026 banner, themed ‘Welfare for All | Happiness of All’, as authorities seek to prevent financial fraud linked to the high-profile gathering.

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Saudi Arabia steps into global AI leadership to shape AI future

The Global Partnership on Artificial Intelligence (GPAI), a multilateral initiative hosted by the OECD and launched by the G7, has officially welcomed Saudi Arabia as a new member. The move reflects the Kingdom’s commitment to shaping global AI governance and ethical technology use.

Accession is led by the Saudi Data and Artificial Intelligence Authority and supported by Crown Prince Mohammed bin Salman. Joining GPAI aligns with Vision 2030, which aims to localise advanced technologies and boost the digital economy’s contribution to GDP.

Through membership in GPAI, which unites over 40 countries, Saudi Arabia will help establish international AI standards, promote human-centric and responsible AI development, and strengthen global cooperation in the sector.

Officials also anticipate that the move will attract high-quality international investment, leveraging the Kingdom’s expanding regulatory framework and growing AI and data ecosystem.

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Secure quantum-safe optical transport strengthens Japan’s AI data center infrastructure

Nokia and KDDI Corporation demonstrated quantum-safe optical transport at Sakai Data Center, supporting advanced AI workloads. The network aims to deliver secure, uninterrupted data transfer while protecting sensitive AI operations.

The demonstration showcases KDDI’s scalable AI-ready infrastructure for real-time training, inference, and analytics. Quantum-safe encryption and resilient transport protect customer data and critical infrastructure across Japan’s distributed data centres.

Using Nokia’s 1830 Photonic Service Switch (PSS) and 1830 Security Management Server (SMS), the partners validated high-capacity, secure optical connectivity. The solution delivers privacy, reliability, and fast quantum-safe encryption for modern AI workloads.

Executives from both companies emphasised the importance of secure, scalable networks in enabling AI-driven services. Nokia and KDDI will continue advancing quantum-safe data centre connectivity, supporting Japan’s digital infrastructure and key enterprise applications.

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China sets new record in rare disease AI diagnosis

A Chinese research team has developed an AI-powered system, DeepRare, to diagnose rare diseases with unprecedented accuracy.

The project, led by Shenhua Hospital and the university’s School of Artificial Intelligence, has already attracted over 1,000 specialised users from more than 600 medical and research institutions worldwide.

Tests show DeepRare achieves 57.18 percent accuracy using only clinical data, marking a 24-point improvement over previous models. Including genetic data raises accuracy above 70 percent, showing potential to improve diagnosis in areas without advanced testing.

The system draws on an extensive knowledge base of medical literature and real-world cases. Its cycle of hypothesis, validation, and self-review boosts reliability and fills reasoning gaps, surpassing the limits of traditional AI models.

By enhancing transparency and precision, DeepRare offers a practical tool for clinicians facing the persistent challenge of identifying rare diseases, potentially setting a new global standard for AI-assisted diagnostics.

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Strict ban on crypto references introduced by OpenClaw

OpenClaw has introduced a firm community rule prohibiting any reference to Bitcoin or other cryptocurrencies on its Discord server, according to its creator, Peter Steinberger.

Enforcement drew attention after a user was removed for mentioning Bitcoin block height as a timing method in a benchmark, with the developer later offering to restore access.

The policy follows a rebrand scare when scammers hijacked old accounts to promote a fake Solana token. Market value spiked then plunged after Steinberger denied involvement, warning that no official token would be issued.

Rapid growth of the open-source project, which has attracted a large developer base within weeks of launch, contrasts with wider industry momentum linking AI agents and digital assets.

Leaders such as Jeremy Allaire of Circle argue stablecoins could become default payment rails for autonomous software, while Coinbase is already rolling out infrastructure enabling agents to transact on-chain.

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Generative AI presents the biggest data-risk challenge in history

Cybersecurity specialists warn that generative AI systems, such as large language models, are creating a data risk frontier far larger than that posed by previous digital innovations.

Because these models are trained on extensive datasets drawn from web pages, internal documents, email corpora and proprietary sources, they can unintentionally memorise or regenerate sensitive information, increasing the risk of exposure.

The article highlights several core concerns. Data leakage and memorisation, where AI models can repeat or infer private data if training processes are not tightly controlled.

Amplification of poor hygiene, when generative tools can magnify the reach of bad actors by automating phishing, social engineering, and malware generation at scale.

Compounding breach impact, if an AI model is trained on stolen or leaked data, it could internalise and regurgitate that information without detection, entrenching harm. Cloud and access governance gaps that allow organisations to adopt AI without robust access controls and encryption may widen their attack surface.

The author calls for revised data governance frameworks, including strict training data provenance, auditability, encryption, minimisation and purpose limitation, to mitigate what is described as ‘the biggest data risk in history.’

Recommendations also include accountability measures for models, continuous monitoring, and legislative action to align AI development with privacy and security principles.

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Altman urges urgent AI regulation

OpenAI chief Sam Altman has called for urgent global regulation of AI, speaking at the AI Impact Summit in New Delhi. Addressing leaders and executives in New Delhi, he said the rapid pace of development demands coordinated international oversight.

In New Delhi, Altman suggested creating a body similar to the International Atomic Energy Agency to oversee advanced AI systems. He warned that highly capable open source biomodels could pose serious biosecurity risks if misused.

Altman argued in New Delhi that democratising AI is essential to prevent power from being concentrated in a single company or country. He added that safeguards are urgently required, even as technology continues to disrupt labour markets.

During the summit in New Delhi, Altman said ChatGPT has 100 million weekly users in India, with more than a third being students. OpenAI also announced plans with Tata Consultancy Services to build data centre infrastructure in India.

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EVMbench from OpenAI, Paradigm and OtterSec measures AI smart contract risks

OpenAI, with Paradigm and OtterSec, introduced EVMbench to test how AI agents detect, patch, and exploit smart contract flaws. The benchmark draws on 120 real vulnerabilities from 40 blockchain projects to better reflect live conditions.

Researchers report that leading agents can now discover and exploit end-to-end vulnerabilities in live blockchain instances. Over six months, exploit success rates rose sharply, prompting both praise for improved auditing capabilities and concern over the rapid scaling of offensive skills.

EVMbench evaluates agents across three modes: detect, patch, and exploit. Each stage reflects increasing technical complexity and mirrors the responsibilities faced in production blockchain environments, where contracts are often immutable, and errors can lead to irreversible losses.

Recent incidents underline the stakes. A vulnerability in AI-generated Solidity code reportedly mispriced an asset, triggering liquidations and losses. Such cases highlight the risks of deploying AI-written financial logic without rigorous human review and governance safeguards.

While EVMbench advances measurement of AI capabilities, it remains limited to curated vulnerabilities and sandboxed conditions. As blockchain adoption expands and criminal misuse evolves, researchers stress the need for responsible AI development alongside stronger innovative contract security practices.

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South Korea accelerates AI education reform in universities

South Korea’s Ministry of Education has launched a nationwide initiative to introduce mandatory AI courses at universities. The measure aims to ensure that all students acquire basic AI skills, regardless of their major, and to extend AI education reforms to higher education.

Under the plan, 6 billion won will be allocated to 20 universities, each receiving 300 million won to develop compulsory introductory AI courses. An additional 30 billion won will support national universities outside Seoul, alongside 5 billion won for short-term interdisciplinary AI programmes.

AI education will be integrated across disciplines rather than confined to computer science departments. Universities are expected to introduce AI courses for nonengineering majors, promote cross-faculty collaboration, and establish campus-wide support systems.

Participating institutions will share curricula, enable credit recognition across universities, and expand course delivery through online platforms. A consultative group will coordinate implementation and disseminate best practices nationwide.

Significant structural challenges remain. Shortages of AI-specialised faculty, limited recruitment flexibility, and the absence of generative AI guidelines in many institutions raise concerns about implementation capacity.

Education officials state that support will also be provided to professors outside AI-related fields to strengthen teaching capacity and address instructor shortages.

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AI-generated harmful imagery sparks alarming warning from 60 regulators

Nearly 60 privacy and data protection authorities issued a joint statement warning about the risks of AI-generated harmful and non-consensual imagery. The initiative was coordinated through the Global Privacy Assembly (GPA) and its International Enforcement Cooperation Working Group (IEWG), reflecting growing cross-border cooperation.

Regulators expressed concern about AI systems that create realistic but fabricated images and videos of identifiable individuals without their knowledge or consent. They warned that such tools can lead to serious privacy violations and reputational harm.

The Office of the Privacy Commissioner for Personal Data (PCPD), which co-chairs the IEWG, highlighted the global dimension of the issue. Privacy Commissioner stressed that children are particularly vulnerable to abusive AI-generated content.

Authorities called on organisations developing and using AI systems to introduce strong safeguards against the misuse of personal data. They also urged transparency, effective mechanisms for content removal, and enhanced, age-appropriate protections for children and other vulnerable groups.

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