Jigsaw Jeeves: Building a Puzzle Assistant using Computer Vision
Conceptual overview and walkthrough of a solution approach in Python
The post Jigsaw Jeeves: Building a Puzzle Assistant using Computer Vision appeared first on Towards Data Science.
The latest round of restrictions and safeguards for frontier models are overly fussy and limiting. A Claude skill that I created demonstrates what happens when guardrails go astray. My skill helps me to find articles and blog posts that go into O’Reilly Radar’s monthly Trends to Watch. It reads roug...
Detecting and Discriminating Operator Misspecification in Hybrid PDE-Parameter Learning: a Reference-Free Instrument, with Discrimination Bounded In Sample
arXiv:2608.16925v1 Announce Type: new
Abstract: We build an instrument that reads, from a single fit and with no oracle, whether the operator a hybrid PDE-parameter estimator postulates is wrong-and separates that from a merely unidentifiable parameter. On one self-adjoint parabolic inverse problem...
Data-DPO: Direct Preference Optimization for Target Model Data Selection in LLM Post-Training
arXiv:2608.16926v1 Announce Type: new
Abstract: Data selection in supervised fine-tuning aims to select a small set of effective samples from large-scale candidate data, reducing training cost while preserving model performance. However, existing methods usually treat data value as a relatively sta...
Hierarchical Data Selection via Manifold Coverage and Sparse Feature Coverage in LLM Post-training
arXiv:2608.16927v1 Announce Type: new
Abstract: As supervised fine-tuning data continues to scale, selecting high-value subsets from large candidate pools is crucial for reducing training cost and improving model performance. Existing methods often measure diversity directly in the original embeddi...
Benchmarking Classical and Transformer-Based Models for Document Sensitivity Classification
arXiv:2608.16928v1 Announce Type: new
Abstract: Automatic sensitivity classification of organizational documents is a critical yet underserved problem, where the consequences of misclassification range from regulatory violations to security breaches. While AI-based approaches offer a scalable alter...
GxP-Agent: Process-DAG Topology for Reliable Clinical Trial Programming with LLM Agents
arXiv:2608.16890v1 Announce Type: new
Abstract: Clinical trial programming -- transforming study protocols into analysis-ready datasets under CDISC standards -- is a bottleneck in regulatory submissions, yet LLM-based code generation fails catastrophically on this task: across 11 single-shot attemp...
Runtime Governance for Agentic AI: Action-Boundary Control with Trusted Provenance and Fail-Closed Execution
arXiv:2608.16891v1 Announce Type: new
Abstract: Agentic AI systems request tool actions that can modify files, send messages, launch jobs, or change workflow state. This shifts the safety problem from harmful text generation to harmful operational side effects. Prompt-level governance can shape mod...
The Price of Thinking: Reasoning Effort as a Model-Specific API Contract
arXiv:2608.16956v1 Announce Type: new
Abstract: API buyers purchase a dated contract, not a model name alone: the contract includes the requested and served model, reasoning-effort term or its omission, output rail, service product, prompt, and price schedule. We study the reasoning-effort term thr...
The Problem Is the Problem: Towards Scalable Mathematical Discovery
arXiv:2608.16977v1 Announce Type: new
Abstract: AI systems are increasingly capable of contributing to mathematical research. In research practice, frontier-model reasoning is a limited resource, and expert mathematical review is even more sharply constrained. Allocating these scarce resources well...
Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts
Large language models (LLMs) exhibit a wide range of human-like behaviors, from expressing thoughts and emotions, to engaging in relationship-building with users, to refusing requests and maintaining boundaries. Despite their prevalence, researchers and practitioners lack methods and empirical insig...
The P-Completeness of Inverted Index Traversal: On the Complexity of Evaluating Boolean Query DAGs
Modern AI agents increasingly rely on search infrastructure to execute complex, neuro-symbolic reasoning workflows. These workflows often compile into deeply nested, non-monotonic Boolean queries over text fields. However, standard query evaluation strategies over inverted indices face severe theore...
Tiny robots powered by light can hunt down and collect bacteria
Researchers have built microscopic, light-driven robots that can rapidly navigate through liquid, collect bacteria, and deposit them in chosen locations. These tiny “cleaners” could open new possibilities for manipulating cells and microbes with remarkable precision.
Strengthening Democratic Oversight in National Security
OpenAI launches an initiative to strengthen democratic oversight of AI in national security, supporting government institutions with tools, training, and expertise.
OpenAI institutes new safeguards after Hugging Face breach
The new safeguards include more detailed monitoring of models during the development process, as well as greater emphasis on alignment and security during the post-training process.
From Prototype to Production: The Architecture Behind Secure & Governed AI Agents
Building the Responsible AI, security, and governance layers required for enterprise-ready agents
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Building Enterprise Agent Systems that People can Trust, Verify and Improve
5 principles that determine whether an agent system succeeds in production, explained through one I built for a $100M+ company.
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OpenAI launches a safer ChatGPT for teens — years after teens started using it
ChatGPT for Teens adds age-appropriate safety measures, parental controls, and learning tools designed to steer teens away from harmful content — and from using AI to cheat on their homework.