The Supreme Court of India set aside NCLT and NCLAT orders in an insolvency dispute after finding the tribunals relied on fabricated, AI-hallucinated case citations that could not be traced in legal databases. The Court ordered a rehearing and directed the Bar Council of India to form an expert committee on AI use in courts.
The Supreme Court set aside an NCLT insolvency verdict after finding it relied on non-existent, fake, and hallucinated AI-generated precedents. The Court directed the Bar Council of India to form a committee to set guiding principles and disciplinary actions.
The Supreme Court set aside NCLT and NCLAT orders that relied on non-existent, AI-generated 'hallucinated' judicial precedents in an insolvency dispute. It directed the Bar Council of India to form an expert committee to examine AI challenges in adjudication.
An Illinois man, Aidan Brewis, was sentenced in Waukesha County Circuit Court for possession of virtual child pornography under Wisconsin’s law that covers AI-generated explicit images. The court imposed three years of initial confinement and five years of extended supervision, plus sex-offender registration.
The House Science, Space, and Technology Committee advanced a package of 10 bipartisan AI bills, including measures to establish/expand AI security, data guidelines, workforce programs, and model documentation/reporting requirements. Bills now move to the full House for consideration.
Large Language Model (LLM) inference workloads are a rapidly growing contributor to data center energy consumption. Optimizing these deployments requires matching specific LLMs to the most efficient GPUs, but operators currently lack the tools to do so without exhaustively profiling each combination. While some predictive models exist, they still require profiling data and struggle to generalize t
Parameter-efficient continual learning aims to adapt pre-trained models to sequential tasks without forgetting previously acquired knowledge. Most existing approaches treat continual learning as avoiding interference with past updates, rather than considering what properties make the current task-specific update naturally preserve previously acquired knowledge. From a knowledge-decomposition persp
Deploying trustworthy AI systems requires principled uncertainty quantification. Conformal prediction (CP) is a widely used framework for constructing prediction sets with distribution-free coverage guarantees. In many practical settings, including healthcare, finance, and mobile sensing, the calibration data required for CP are distributed across multiple clients, each with its own local data dis
Short-horizon prediction is essential for electro-optical UAV tracking, especially when the target is small, maneuvering, or intermittently observed. Image center, line-of-sight, and range measurements provide direct constraints on target position, but their constraints on acceleration are weak. As a result, prediction can lag during aggressive maneuvers. This paper proposes an image-domain tilt c
AI agents that pay for resources via the x402 protocol embed payment metadata - resource URLs, descriptions, and reason strings - in every HTTP payment request. This metadata is transmitted to the payment server and to the centralised facilitator API before any on-chain settlement occurs; neither party is typically bound by a data processing agreement. We present presidio-hardened-x402, the first
Capital remains concentrated in large, late-stage checks and public-market exits, with infrastructure and compute-adjacent names absorbing the biggest allocations. The pattern signals continued investor preference for scale and strategic backing over broad seed dispersion.
Capital remains concentrated in large, late-stage checks and public-market exits, with infrastructure and compute-adjacent names absorbing the biggest allocations. The pattern signals continued investor preference for scale and strategic backing over broad seed dispersion.
Capital remains concentrated in large, late-stage checks and public-market exits, with infrastructure and compute-adjacent names absorbing the biggest allocations. The pattern signals continued investor preference for scale and strategic backing over broad seed dispersion.
Named moves are concentrated in senior operating and AI leadership, where departures and hires can reshape execution at large institutions and platform teams. The desk points to ongoing churn around data, AI, and field operations roles.
Named moves are concentrated in senior operating and AI leadership, where departures and hires can reshape execution at large institutions and platform teams. The desk points to ongoing churn around data, AI, and field operations roles.
Named moves are concentrated in senior operating and AI leadership, where departures and hires can reshape execution at large institutions and platform teams. The desk points to ongoing churn around data, AI, and field operations roles.
Benchmark movement is limited to one model family across math and general knowledge surfaces, which makes the signal more about coverage than leaderboard disruption. The desk still matters because even small score updates can reset internal baselines for downstream comparisons.
Benchmark movement is limited to one model family across math and general knowledge surfaces, which makes the signal more about coverage than leaderboard disruption. The desk still matters because even small score updates can reset internal baselines for downstream comparisons.
Benchmark movement is limited to one model family across math and general knowledge surfaces, which makes the signal more about coverage than leaderboard disruption. The desk still matters because even small score updates can reset internal baselines for downstream comparisons.