The following article originally appeared on Q McCallum’s blog and is being republished here with the author’s permission. Generative AI agents and rogue traders pose similar insider threats to their employers. Specifically, we can expect companies to deploy agentic AI with broad reach and insuffici...
Health CIOs Call for Interoperable EHRs, Cite Cost Barriers
Nearly 90% of health IT leaders surveyed say vendor consolidation is crucial to their interoperability strategy, while less than one-fifth currently have the technology required to provide it CliniComp, the pioneer in high-performing, reliable, electronic health record (EHR) solutions, today announc...
Wristband enables wearers to control a robotic hand with their own movements
By moving their hands and fingers, users can direct a robot to play piano or shoot a basketball, or they can manipulate objects in a virtual environment.
Learn how OpenAI’s Model Spec serves as a public framework for model behavior, balancing safety, user freedom, and accountability as AI systems advance.
RethinkBH Launches AI Dashboard for Real-Time ABA Insights
New command center surfaces risks, guides action, and ensures smoother workflows to support better care and on-time revenue Rethink Behavioral Health (RethinkBH), the leading provider of EHR solutions designed for ABA therapy, today announced the launch of AI Dashboard. This centralized, intelligent...
My Models Failed. That’s How I Became a Better Data Scientist.
Data Leakage, Real-World Models, and the Path to Production AI in Healthcare
The post My Models Failed. That’s How I Became a Better Data Scientist. appeared first on Towards Data Science.
Avahi Wins 2026 Artificial Intelligence Excellence Award in Agentic AI
Recognition honors organizations, products, teams, and individuals delivering measurable results through artificial intelligence Avahi, an AWS Premier Partner, today announced it has been named a winner in the 2026 Artificial Intelligence Excellence Awards, in the category of Agentic AI. Presented b...
AI is at war. Anthropic and the Pentagon feuded over how to weaponize Anthropic’s AI model Claude; then OpenAI swept the Pentagon off its feet with an “opportunistic and sloppy” deal. Users quit ChatGPT in droves. People marched through London in the biggest protest against AI to date. If you’re kee...
NVIDIA AI Introduces PivotRL: A New AI Framework Achieving High Agentic Accuracy With 4x Fewer Rollout Turns Efficiently
Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent trade-off between computational efficiency and model generalization. While Supervised Fine-Tuning (SFT) is computationally inexpensive, it ...
Vectra AI Advances Observability with Proactive Exposure Mgmt
As AI-driven environments constantly evolve, Vectra AI brings real-time visibility, measurement, and action to changing exposure Vectra AI, the leader in modern network observability, signal, and control, today announced a major advancement to the Vectra AI Platform, delivering exposure management b...
Ping Identity Defines the Runtime Identity Standard for Autonomous AI
General Availability of Identity for AI establishes continuous, contextual enforcement and real-time control over AI agents Ping Identity, a leader in securing digital identities for the world’s largest enterprises, announced the General Availability of Identity for AI, introducing a model designed ...
Google Introduces TurboQuant: A New Compression Algorithm that Reduces LLM Key-Value Cache Memory by 6x and Delivers Up to 8x Speedup, All with Zero Accuracy Loss
The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size scales with both model dimensions and context length, creating a significant bottleneck for long-context ...
Now that we know AI is inevitably a part of our workflow, the more relevant question today is not “should I use AI?”, but “how to use AI?”. With the AI tools market more crowded than ever, each passing week sees a new assistant, generator, or automation. The struggle then is of choice from a […]
The...
Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning
arXiv:2603.22292v1 Announce Type: new
Abstract: Sequential decision making using Markov Decision Process underpins many realworld applications. Both model-based and model free methods have achieved strong results in these settings. However, real-world tasks must balance reward maximization with saf...
Efficient Embedding-based Synthetic Data Generation for Complex Reasoning Tasks
arXiv:2603.22294v1 Announce Type: new
Abstract: Synthetic Data Generation (SDG), leveraging Large Language Models (LLMs), has recently been recognized and broadly adopted as an effective approach to improve the performance of smaller but more resource and compute efficient LLMs through fine-tuning....
Between the Layers Lies the Truth: Uncertainty Estimation in LLMs Using Intra-Layer Local Information Scores
arXiv:2603.22299v1 Announce Type: new
Abstract: Large language models (LLMs) are often confidently wrong, making reliable uncertainty estimation (UE) essential. Output-based heuristics are cheap but brittle, while probing internal representations is effective yet high-dimensional and hard to transf...
arXiv:2603.22300v1 Announce Type: new
Abstract: Scaling Transformers to ultra-long contexts is bottlenecked by the $O(n^2 d)$ cost of self-attention. Existing methods reduce this cost along the sequence axis through local windows, kernel approximations, or token-level sparsity, but these approaches...
Latent Semantic Manifolds in Large Language Models
arXiv:2603.22301v1 Announce Type: new
Abstract: Large Language Models (LLMs) perform internal computations in continuous vector spaces yet produce discrete tokens -- a fundamental mismatch whose geometric consequences remain poorly understood. We develop a mathematical framework that interprets LLM...
The Efficiency Attenuation Phenomenon: A Computational Challenge to the Language of Thought Hypothesis
arXiv:2603.22312v1 Announce Type: new
Abstract: This paper computationally investigates whether thought requires a language-like format, as posited by the Language of Thought (LoT) hypothesis. We introduce the ``AI Private Language'' thought experiment: if two artificial agents develop an efficient...
Intelligence Inertia: Physical Principles and Applications
arXiv:2603.22347v1 Announce Type: new
Abstract: While Landauer's principle establishes the fundamental thermodynamic floor for information erasure and Fisher Information provides a metric for local curvature in parameter space, these classical frameworks function effectively only as approximations ...
arXiv:2603.22350v1 Announce Type: new
Abstract: Deterministic pre-execution safety gates evaluate whether individual agent actions are compatible with their assigned roles. While effective at per-action authorization, these systems are structurally blind to distributed attacks that decompose harmfu...
OpenAI launches a Safety Bug Bounty program to identify AI abuse and safety risks, including agentic vulnerabilities, prompt injection, and data exfiltration.