Ramp's Sheets AI recently faced a vulnerability allowing unauthorized data exfiltration through malicious formulas. This risk was responsibly disclosed by PromptArmor, prompting Ramp's security team to quickly resolve the issue. The article explores the attack chain and compares it to a similar risk identified in Claude for Excel.

Chinese AI lab DeepSeek has launched its V4 series with two new models, Pro and Flash, which boast impressive token capacities and competitive pricing. Pro is notable for its large parameter count while Flash is the most affordable model among small AI offerings. Both focus on efficiency for longer contexts.

A recent supply chain attack compromised versions 2.6.2 and 2.6.3 of the popular PyPI package 'lightning', injecting malware that steals credentials and other sensitive data. The attack targets multiple cloud environments and sets up persistent hooks in developer tools, posing risks for many users relying on this framework.

A recent study reveals significant inconsistencies in AI models' carbohydrate estimates for food, with some discrepancies large enough to pose serious health risks for people with diabetes. Results show systematic and stochastic errors across popular AI systems, highlighting the need for caution when relying on AI for carb counting.

Large language models (LLMs) are now transforming unstructured data into structured formats, but current benchmarks often overlook crucial output quality aspects. This article introduces the Structured Output Benchmark (SOB), designed to accurately assess the extraction capabilities of LLMs across various data modalities.

This article explores the integration of the NVIDIA TensorRT plugin with Unreal Engine 5's Neural Network Engine. It highlights how utilizing TensorRT for RTX can enhance AI model inferencing on NVIDIA GPUs, improving performance in real-time graphics workflows while providing practical steps for developers to implement it in their projects.

Biohub has launched the Virtual Biology Initiative, committing $500 million over five years to develop technologies and datasets for predictive models of life. This global effort, in partnership with leading institutions, aims to enhance our understanding of cellular mechanisms, disease causes, and potential therapies through coordinated data generation.

This article explores the troubling disconnect between job responsibilities and compensation, particularly in critical roles within the public safety sector. It argues that wages should reflect not only the value of labor but also act as a safeguard for companies against worker dissatisfaction. As compensation declines, employers risk greater security challenges.

This article examines how Meta uses public relations strategies similar to the tobacco industry's marketing tactics to address concerns about the mental health impacts of social media. By highlighting safety measures, Meta shifts focus from the risks of its platforms, mirroring historical patterns observed in cigarette advertising.

took away valuable insights about collaboration with external partners and the importance of thorough troubleshooting strategies. By addressing underlying issues in their infrastructure, they improved their system's reliability and learned the significance of anticipating cascading failures in distributed environments.

Sam Altman confirms that OpenAI's new cybersecurity tool, GPT-5.5 Cyber, will be released to selected users, mirroring Anthropic's earlier strategy. The tool aims to assist in penetration testing and vulnerability identification, while OpenAI plans to gradually expand access to legitimate cyber defenders through a verification system.

The rapid evolution of AI is reshaping the tech landscape, leaving many professionals feeling outdated and overwhelmed. As workflows and hierarchies flatten, the value of traditional roles diminishes, while skills in clarity, judgment, and prioritization gain importance. This article explores the implications of this shift for career trajectories in technology.

The paper examines the growing challenges of designing dependable autonomous systems in the context of AI and machine learning. It discusses new methodologies and frameworks aimed at addressing the complexities of safety, security, and reliability, focusing on how to manage the inherent uncertainties of intelligent systems.

HealthFormer is a generative model that simulates human physiological changes over time, trained on extensive data from the Human Phenotype Project. It accurately predicts individual health outcomes and simulates the effects of clinical interventions, promising advancements in personalized medicine and clinical decision-making.

DEFault++ introduces a new approach to fault detection in transformer models by classifying and diagnosing issues at multiple abstraction levels. The method achieves high accuracy through a dedicated benchmark and enhances repair decision-making for developers, significantly improving their effectiveness in addressing faults in AI systems.