Professor Martin Hayes of UL discusses his research in systems theory, highlighting the future of engineering with 'pi-shaped' graduates and emphasizing the need for patience in developing reliable AI solutions for safety-critical environments.
The European Commission aims to mobilize a combined €30 billion from both public and private sources to support the development of seven state-of-the-art AI gigafactories. This ambitious effort is designed to enhance Europe's position in the global AI sector and stimulate technological growth across the continent.
Experts from IAS and Rent the Runway discuss how artificial intelligence is reshaping research and development within organizations. Their insights highlight the significant role AI plays in accelerating innovation and improving R&D processes.
Whether you operate a medical practice or a law firm, getting recognized by AI search engines hinges on three key strategies. Surprisingly, most businesses fail to implement any of these crucial steps.
Samsung Electronics, the South Korean tech giant, reported an unprecedented operating profit of 89.5 trillion won ($62 billion) for Q2, fueled mainly by soaring demand for semiconductors powering AI infrastructure. Despite this historic surge, their shares fell sharply amid investor worries over aggressive capacity expansion plans and rising competition from China. Samsung’s chip division led the growth thanks to higher prices and shipments of advanced memory chips for AI servers, outweighing losses in mobile and home appliance sectors. The company anticipates continued strong demand for AI-related memory products through the second half of 2024, supported by long-term supply deals with global data center giants. Meanwhile, Samsung and peer SK Hynix together dominate about two-thirds of the global memory chip market and recently outlined a massive $554 billion investment to strengthen South Korea’s position as an AI semiconductor hub. However, concerns remain over whether this hefty spending will generate sufficient returns amidst ongoing market volatility and competitor pressures from China’s emerging chip technologies.
OpenAI has drastically cut the prices of its GPT-5.6 Luna and Terra models, with Luna's cost dropping by 80% and Terra's by 20%. Luna now costs $1.40 per million tokens, making it one of the lowest-cost commercial AI models and directly competing with Google's lower-priced Gemini models. Terra's pricing aligns with Google's Gemini 3.1 Pro Preview, while OpenAI introduces a premium Fast mode for its Sol model, priced at double the standard rate. These price cuts come shortly after Google's launch of cost-efficient Gemini 3.6 Flash and 3.5 Flash-Lite models and Anthropic's release of Claude Opus 5, highlighting a shift in the AI market focus towards cost-efficiency alongside performance. OpenAI's Luna targets high-throughput, low-latency applications, while Terra balances capability and cost for general use. The move signals that AI competition is no longer just about access to powerful models but also about making them economically viable for high-volume production workloads.
Every Mastercard transaction undergoes a split-second fraud assessment, with 175 billion transactions analyzed last year. Chief AI and Data Officer Greg Ulrich revealed at VB Transform 2026 that Mastercard’s risk system, once designed to block bots, is now evolving to accommodate them. This shift requires a new framework that balances security with enabling bot transactions. Mastercard’s Safety Net has already prevented over 70 billion fraudulent transactions, leveraging AI to identify 300-400% more fraud without disrupting genuine purchases. Beyond consumer fraud, AI powers a third of Mastercard’s services, driving faster growth in marketing, security, and business intelligence. Ulrich detailed five security layers—identity verification, verifiable intent, controls, execution via Mastercard Agent Pay, and intelligence monitoring—that ensure trust in agent-driven commerce. As AI agents gain autonomy in complex transactions, especially in B2B procurement, Mastercard is building scalable trust infrastructures that link multiple agents across organizations. Learning from initial models, Mastercard prioritizes embedded security and continuous monitoring to prevent vulnerabilities. Identity verification, including emerging standards for agentic identity, remains pivotal. The company is already re-engineering its AI systems to handle the new reality where bots do the buying, not just the stealing.
Less than a year after revealing itself to tackle the challenge of non-human identity security, Israeli cybersecurity startup Hush Security asserts the AI security landscape has shifted significantly. The company recently secured a $30 million Series A funding round, led by Battery Ventures and YL Ventures, with Akamai Technologies joining as a strategic investor. Hush points out that enterprises are moving beyond simple generative AI tools, deploying autonomous software agents that demand new security models focused on identity management rather than model protection. CEO Micha Rave explains that as AI agents increasingly act across multiple systems with broad permissions often tied to human credentials, the core issue is securing these non-human identities. Hush has developed an "Identity Gateway" platform that assigns unique identities to AI agents, enforces least-privilege access, and offers centralized control and audit capabilities. The platform enables organizations to govern AI agents’ access in real-time, mitigating risks associated with broad or inherited permissions. With autonomous agents projected to balloon in enterprise environments, Hush emphasizes that securing identity is becoming the essential control point, marking a notable shift in AI security strategies from focusing on model vulnerabilities to managing identity governance for autonomous software.
Security teams evaluating open-source AI models often rely on unverified metadata tags to determine model lineage, leaving verification gaps. A recent report from Interconnects AI tracked 1,500 open models and found that 69% of derivatives stem from Alibaba’s Qwen family, with Chinese labs contributing 70%. Cisco's newly launched AI Supply Chain Provenance Explorer addresses these gaps by fingerprinting nearly 900 open models using sophisticated similarity scores and weight-level analysis. This public tool allows users to verify model parentage, license restrictions, scan coverage, and provider details without needing a Cisco product or extensive local computation. The Explorer improves risk management by replacing self-reported tags with data-driven lineage, enabling security teams to assess vulnerabilities, malware scanning completeness, jurisdiction, and licensing obligations more accurately. It also supports compliance with the upcoming EU AI Act by providing transparent provenance data. Although the tool currently covers a subset of models on Hugging Face, it marks a significant advancement in securing open AI model supply chains and assisting organizations to adopt safer AI practices.
Minnesota's pioneering legislation aims to curb AI-generated fake nude images by banning 'nudification' technology on digital platforms. Elon Musk's xAI has filed a federal lawsuit against this law just days before it becomes effective, raising a critical legal debate on state authority to regulate AI usage. Passed in May, the law positions Minnesota as the first state to confront this fast-evolving AI issue at a legal level.
