10 results on this page
CISA warns that hackers are actively targeting Siemens equipment used in critical U.S. water infrastructure. Attackers are reportedly using artificial intelligence to identify vulnerabilities as water systems face increasing cyberattacks.
Kuaishou’s Kling AI raised nearly $3 billion at a post-money valuation of $18 billion, with Kuaishou’s stake falling to 68.33% and a potential Hong Kong IPO targeted by 2031. Despite strong revenue growth, Kling faces slowing momentum, talent departures, and intense competition from ByteDance’s Seedance and open-source video models.
OpenAI’s Q2 2026 revenue reportedly rose to $6.7 billion, but quarterly growth slowed to 18% while operating losses expanded to $12.3 billion. Ahead of a potential trillion-dollar IPO, the company faces pressure from consumer ARPU limits, enterprise competition, falling API prices, and massive compute commitments.
The US Trade Representative’s reference to “digital trade alignment” in talks with Prime Minister Mark Carney’s government is raising concerns in Canada. Critics worry the agreement could limit Canada’s ability to independently regulate technology companies and AI.
Meta has introduced a new Meta AI app for Mac that lets users interact with their applications through conversation. The app’s dictation feature is powered by Meta’s Muse Spark model.
Lightelligence is shifting from computing with light to connecting with light, signaling a more pragmatic focus on photonic interconnects. Despite strong investor enthusiasm following a 383.62% first-day stock surge in Hong Kong, the company faces concentrated customers, slow receivables, declining margins, and supply-chain risks.
A position paper analyzing 500 Hugging Face model cards argues that model cards alone do not provide enough information for governing open-weight foundation models. It proposes combining model cards with acceptable use policies and licenses to address safety, provenance, behavior, and enforcement gaps.
The paper proposes Transition Complexity Profile (TCP), a reproducible framework for measuring how difficult game-world transition prediction is at a specified interface. It evaluates branching, interaction-driven uncertainty, opponent influence, and temporal or spatial dependencies to improve comparisons across game-modeling and reinforcement-learning benchmarks.
Anthropic announced that Claude would add invisible watermarks to AI-generated content to comply with new EU rules. Within hours, coders online began sharing purported methods to override or bypass them.
Anthropic’s effort to label AI-written text has prompted developers to build tools that remove those labels. Business Insider reports that one remover has gone viral on GitHub, raising concerns about the durability of AI-text provenance signals.