I Built a Tool-Calling Agent in Python. Here’s How I Debugged It
A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework
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August is here, bringing 26 new games for GeForce NOW members. Command the seas in World of Warships: Legends and discover what’s next in the GeForce NOW library, starting with the eight newly added games this week. In addition, GeForce NOW is at the QuakeCon gaming conference this week in Grapevi...
Ex-Spotify employees raise $10M to bring the AI behind its recommendations to e-commerce
The startup's platform predicts what product a shopper wants next, learn their general taste, and fine-tune continuously based on what they do in real time.
Into the Omniverse: How Open World Models Push the Frontier of Physical AI
In July, NVIDIA joined more than 200 companies and organizations in signing “Open Weights and American AI Leadership,” an open letter arguing that AI leadership will be measured not by any single frontier model but by whether an open ecosystem reaches every sector.
Google Maps adds agentic features, including food ordering and hotel bookings
The launch of these new features reflects Google’s ambitions to transform Google Maps from a navigation tool into an assistant that's capable of helping users complete real-world tasks.
Your AI Agent Isn’t a Static Artifact. It’s Growing Up.
In July 2025, an AI coding agent on Replit deleted a production database belonging to SaaStr founder Jason Lemkin. It did this during an explicit code freeze. Lemkin had told the agent, in capital letters, not to change anything. The agent ran destructive commands anyway, wiped records on more than ...
Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel
Prime Intellect has open-sourced Prime Agent, a coding and research harness built on two abstractions: the Recursive Language Model, which turns sub-agent calls into functions inside a persistent IPython kernel, and the Continual Harness, which lets the agent edit its own prompts, skills, memory, an...
Working with the American Psychological Association on youth mental health and AI
OpenAI and the APA are launching a three-year partnership to develop guidance, resources, and safeguards for responsible AI use supporting youth mental health.
On Hamming-Lipschitz Type Stability of the Subdominant (Minmax) Ultrametric: Theory and Simple Proofs
arXiv:2608.04014v1 Announce Type: new
Abstract: The subdominant (minmax) ultrametric is a canonical tree-structured summary of a dissimilarity matrix, arising equivalently as the ultrametric induced by single-linkage clustering. While its classical stability theory is usually formulated in $\ell_\i...
arXiv:2608.04026v1 Announce Type: new
Abstract: In this paper, we develop a trust-region framework for understanding the behavior of adaptive moment estimation mechanisms, such as \textsc{Adam}, in stochastic gradient optimization. Specifically, in this framework, the magnitude of the update step f...
Learning to Resolve Neutron Resonances with Fully Convolutional Neural Networks
arXiv:2608.04027v1 Announce Type: new
Abstract: This work investigates the feasibility of augmenting traditional R-Matrix codes with a robust machine learning framework for automatically detecting neutron resonances in transmission spectra. Neutron transmission data are often complex and noisy, mak...
The LLM Proposes, the Executive Disposes: A Self-Verifying Agent Instrument that Dissociates Commitment Drift from Binding Drift in Long-Horizon Agents
arXiv:2608.04066v1 Announce Type: new
Abstract: How do you verify a long-horizon agent when its own state and self-reports are exactly what you cannot trust? We present an agent instrument built so that verification is structural rather than post-hoc. A deterministic Executive owns all belief; a la...
FinProBench: Evaluating Financial AI Agents with Role-Grounded Rubrics Derived from Professional Deliverables
arXiv:2608.04077v1 Announce Type: new
Abstract: Evaluating financial AI agents requires criteria aligned with real professional work. Existing rubric methods typically derive criteria from task prompts or model outputs, overlooking tacit standards visible only in practitioner deliverables. We intro...
FinPerMA: A Theory-Informed, Event-Grounded Personalized-Memory Benchmark for LLM Agents
arXiv:2608.04095v1 Announce Type: new
Abstract: Large language model (LLM) agents are increasingly used as personalized assistants in high-stakes domains such as financial advising, yet it remains unclear whether they can maintain and update an individualized user model over long horizons. Existing...
Microsoft’s SkillOpt Shows Optimized Agent Skill Artifacts Transfer Across Model Scales and Between Codex and Claude Code Harnesses
Most coverage of Microsoft's SkillOpt centers on its 52/52 result. The more consequential finding is in Section 4.3: the exported best_skill.md keeps working in environments it was never trained on. A Codex-trained SpreadsheetBench skill lifted Claude Code from 22.1 to 81.8, slightly above the 80.4 ...
Locking Pretrained Weights via Deep Low-Rank Residual Distillation
The quality of open-weight language models has dramatically improved in recent years. Sharing weights greatly facilitates model adoption by enabling their use across diverse hardware and software platforms. They also allow for more open research and testing, to the extent that users can use them as ...
DeepAmbigQA: Ambiguous Multi-hop Questions for Benchmarking LLM Answer Completeness
Large language models (LLMs) with integrated search tools show strong promise in open-domain question answering (QA), yet they often struggle to produce complete answer set to complex questions such as “Which actor from the film Heat won at least one Academy Award?”, which requires (1) distinguishin...