Models, papers, tools. 16,915 articles with AI-powered sentiment analysis and key takeaways.
Intel stock surged 4.4% following news of potential collaboration with Nvidia, along with AI partnerships with Ericsson and Infosys. The rally was also driven by progress reports on Intel's advanced 18A manufacturing process.
Nvidia's flagship GTC 2026 conference will feature CEO Jensen Huang's keynote address focusing on the company's vision for the future of computing and AI. The annual event typically serves as a platform for announcing new products, partnerships, and strategic directions for the chipmaker.
Tower Semiconductor and Scintil Photonics have developed the world's first single-chip DWDM light engine for AI infrastructure, integrating multiple laser wavelengths onto silicon wafers. This breakthrough enables dense wavelength division multiplexing in AI data centers, allowing multiple optical signals over single fibers to reduce power consumption and latency while connecting dozens of GPUs.
Iran's top diplomat announces that the Strait of Hormuz will only be blocked for vessels belonging to the United States, Israel, and their allies. This selective blockade of the critical oil shipping route could impact global energy markets and supply chains.
Bank of America significantly raised its 2026 Brent crude oil forecast to $77.50 from $61 following supply disruptions at the Strait of Hormuz that drained 200 million barrels. The bank also boosted price targets for energy exploration and production stocks including FANG, DVN, and OVV.
Goldman Sachs international executives Anthony Gutman and Kunal Shah draw parallels between Iran's military actions and Russia's Ukraine invasion, while noting fundamental differences in starting conditions. The comparison highlights potential similar geopolitical and economic implications but acknowledges distinct contextual factors.
Fundstrat's Tom Lee predicts the S&P 500 will rally to new all-time highs in the coming weeks before experiencing a 20% market crash later this year. This forecast suggests a significant bear market correction following the anticipated near-term stock market gains.
A debate is emerging over whether AI data centers, which can pay more for electricity than Bitcoin miners, pose a threat to Bitcoin's long-term security. Market and energy specialists are pushing back against claims that this dynamic threatens Bitcoin mining viability.
Nebius (NBIS) stock surged following the announcement of a massive five-year AI infrastructure partnership with Meta valued at up to $27 billion. The deal includes $12 billion in guaranteed contracts and an additional $15 billion in optional agreements, positioning Nebius as a major AI infrastructure provider.
Taiwan Semiconductor (TSM) stock has surged 83% with Bernstein upgrading the stock to a NT$2,200 target price. The company expects AI revenue to exceed 20% by 2026 as part of a $45 billion expansion plan.
Meta is reportedly considering a potential 20% workforce reduction that could generate up to $8 billion in annual savings. This strategic move appears aligned with the company's pivot toward AI-focused operations and cost optimization efforts.
OpenAI's Frontier platform, launched in February, positions AI agents as a semantic layer connecting enterprise systems, potentially disrupting traditional SaaS revenue models. The platform aims to integrate data warehouses, CRM platforms, and internal tools, challenging the existing software industry architecture.
Micron (MU) is set to report Q2 FY26 earnings on March 18, with analysts expecting massive growth driven by AI demand for high-bandwidth memory (HBM). Revenue is projected at $19.1B, representing a 137% year-over-year increase, as AI applications create demand that exceeds current supply capacity.
WIRED investigation reveals dozens of Telegram channels advertising jobs for 'AI face models,' with mostly women being recruited to serve as the face of AI-powered financial scams. These models are likely being used to conduct video calls with victims to build trust before defrauding them of money.
Trump has initiated new Section 301 trade probes targeting Asian countries, potentially leading to additional tariffs. China condemned the probes as protectionist measures, while Malaysia declared its U.S. trade deal 'null and void' in response.
Crypto trader Ran Neuner warns that Bitcoin mining could be threatened as AI data centers compete for the same computational resources and energy infrastructure. The debate centers on whether AI's rapid expansion will pull miners away from Bitcoin's network, potentially impacting its security and decentralization.
Anthropic has filed a lawsuit against the Trump administration over an AI-related Pentagon dispute. Meanwhile, Elon Musk's xAI is reportedly restarting its development process again, and Iran-related AI-generated fake content about potential warfare is spreading chaos online.
DriveMind introduces a new AI framework combining vision-language models with reinforcement learning for autonomous driving, achieving significant performance improvements in safety and route completion. The system demonstrates strong cross-domain generalization from simulation to real-world dash-cam data, suggesting practical deployment potential.
Researchers propose the Superficial Safety Alignment Hypothesis (SSAH), suggesting that AI safety alignment in large language models can be understood as a binary classification task of fulfilling or refusing user requests. The study identifies four types of critical components at the neuron level that establish safety guardrails, enabling models to retain safety attributes while adapting to new tasks.
A comprehensive survey examines the integration of TinyML (for resource-constrained IoT devices) and LargeML (for large-scale services) in 6G wireless networks. The research identifies key challenges and opportunities for unified machine learning frameworks to enable intelligent, scalable, and energy-efficient next-generation networks.
Researchers introduce the AI Search Paradigm, a comprehensive framework for next-generation search systems using four LLM-powered agents (Master, Planner, Executor, Writer) that collaborate to handle everything from simple queries to complex reasoning tasks. The system employs modular architecture with dynamic workflows for task planning, tool integration, and content synthesis to create more adaptive and scalable AI search capabilities.
Researchers developed a supervised fine-tuning approach to align large language model agents with specific economic preferences, addressing systematic deviations from rational behavior in strategic environments. The study demonstrates how LLM agents can be trained to follow either self-interested or morally-guided strategies, producing distinct outcomes in economic games and pricing scenarios.
Research published on arXiv demonstrates that training diverse AI model ecosystems can prevent knowledge collapse, where AI systems degrade when trained on their own outputs. The study shows that optimal diversity levels increase with training iterations, and larger, more homogeneous systems are more susceptible to collapse.
Researchers have identified why current deepfake voice detection systems fail in real-world applications, finding that existing datasets don't account for how audio changes when transmitted through communication channels. A new framework improved detection accuracy by 39-57% and emphasizes that better datasets matter more than larger AI models for effective deepfake detection.
Researchers have developed a new methodology that leverages Large Language Models to automate the creation of Ontological Knowledge Bases, addressing traditional challenges of manual development. The approach demonstrates significant improvements in scalability, consistency, and efficiency through automated knowledge acquisition and continuous refinement cycles.
