Photon Releases Spectrum: An Open-Source TypeScript Framework that Deploys AI Agents Directly to iMessage, WhatsApp, and Telegram
For all the progress made in AI agent development over the past few years, one fundamental problem has remained largely unsolved: most people never actually interact with agents. They live behind developer dashboards, inside specialized apps that users are asked to download, and within chat interfac...
OpenAI Open-Sources Euphony: A Browser-Based Visualization Tool for Harmony Chat Data and Codex Session Logs
Debugging an AI agent that runs for dozens of steps: reading files, calling APIs, writing code, and revising its own output, is not like debugging a regular function. There is no single stack trace to read. Instead, developers are left staring at hundreds of lines of raw JSON, trying to reconstruct ...
Compile to Compress: Boosting Formal Theorem Provers by Compiler Outputs
arXiv:2604.18587v1 Announce Type: new
Abstract: Large language models (LLMs) have demonstrated significant potential in formal theorem proving, yet state-of-the-art performance often necessitates prohibitive test-time compute via massive roll-outs or extended context windows. In this work, we addre...
Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning
arXiv:2604.18639v1 Announce Type: new
Abstract: Previous LLMs-based RL studies typically follow either supervised learning with high annotation costs, or unsupervised paradigms using voting or entropy-based rewards. However, their performance remains far from satisfactory due to the substantial ann...
FASE : A Fairness-Aware Spatiotemporal Event Graph Framework for Predictive Policing
arXiv:2604.18644v1 Announce Type: new
Abstract: Predictive policing systems that allocate patrol resources based solely on predicted crime risk can unintentionally amplify racial disparities through feedback driven data bias. We present FASE, a Fairness Aware Spatiotemporal Event Graph framework, w...
Curiosity-Critic: Cumulative Prediction Error Improvement as a Tractable Intrinsic Reward for World Model Training
arXiv:2604.18701v1 Announce Type: new
Abstract: Local prediction-error-based curiosity rewards focus on the current transition without considering the world model's cumulative prediction error across all visited transitions. We introduce Curiosity-Critic, which grounds its intrinsic reward in the i...
Beyond One Output: Visualizing and Comparing Distributions of Language Model Generations
arXiv:2604.18724v1 Announce Type: new
Abstract: Users typically interact with and evaluate language models via single outputs, but each output is just one sample from a broad distribution of possible completions. This interaction hides distributional structure such as modes, uncommon edge cases, an...
ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System
arXiv:2604.18789v1 Announce Type: new
Abstract: Reinforcement Learning from Human Feedback (RLHF) is central to aligning Large Language Models (LLMs), yet it introduces a critical vulnerability: an imperfect Reward Model (RM) can become a single point of failure when it fails to penalize unsafe beh...
AI scientists produce results without reasoning scientifically
arXiv:2604.18805v1 Announce Type: new
Abstract: Large language model (LLM)-based systems are increasingly deployed to conduct scientific research autonomously, yet whether their reasoning adheres to the epistemic norms that make scientific inquiry self-correcting is poorly understood. Here, we eval...
Quantum inspired qubit qutrit neural networks for real time financial forecasting
arXiv:2604.18838v1 Announce Type: new
Abstract: This research investigates the performance and efficacy of machine learning models in stock prediction, comparing Artificial Neural Networks (ANNs), Quantum Qubit-based Neural Networks (QQBNs), and Quantum Qutrit-based Neural Networks (QQTNs). By outl...
Hugging Face Releases ml-intern: An Open-Source AI Agent that Automates the LLM Post-Training Workflow
Hugging Face has released ml-intern, an open-source AI agent designed to automate end-to-end post-training workflows for large language models (LLMs). Built on the company’s smolagents framework, the tool can autonomously perform literature review, dataset discovery, training script execution, and i...
A Coding Implementation to Build a Conditional Bayesian Hyperparameter Optimization Pipeline with Hyperopt, TPE, and Early Stopping
In this tutorial, we implement an advanced Bayesian hyperparameter optimization workflow using Hyperopt and the Tree-structured Parzen Estimator (TPE) algorithm. We construct a conditional search space that dynamically switches between different model families, demonstrating how Hyperopt handles hie...
AI Weekly Issue #486: Apple is replacing Tim Cook because of AI
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We asked how you'd like deep dives delivered. 165 votes — nearly half (47.9%) want separate emails per topic, 38.8% want one weekly digest, 13.3% have no preference. The split means we'll do both: pick your setup in Preferences. That part's live.
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OpenAI Privacy Filter is an open-weight model for detecting and redacting personally identifiable information (PII) in text with state-of-the-art accuracy
OpenAI makes ChatGPT for Clinicians free for verified U.S. physicians, nurse practitioners, and pharmacists, supporting clinical care, documentation, and research.
When ChatGPT launched as an experimental prototype in late 2022, OpenAI’s chatbot became an everyday everything app for hundreds of millions of people. LLMs like ChatGPT were the new future: The entire tech industry was consumed by the inferno, with companies racing to spin up rival products. The as...
When ChatGPT was released to the public in late 2022, it opened people’s eyes to how easily generative AI could churn out vast amounts of human-seeming text from simple prompts. This quickly caught the attention of criminals, who soon began using large language models to produce malicious emails—bot...
AI systems have already gained impressive mastery over the digital world, but the physical world is still humanity’s domain. As it turns out, building an AI system that can compose a novel or code an app is far easier than developing one that can fold laundry or navigate a city street. To get there,...
DIY AI & ML: Solving The Multi-Armed Bandit Problem with Thompson Sampling
How you can build your own Thompson Sampling Algorithm object in Python and apply it to a hypothetical yet real-life example
The post DIY AI & ML: Solving The Multi-Armed Bandit Problem with Thompson Sampling appeared first on Towards Data Science.
As AI agents increasingly work alongside humans across organizations, companies could be inadvertently opening a new attack surface. Insecure agents can be manipulated to access sensitive systems and proprietary data, increasing enterprise risk. In some modern enterprises, non-human identities (NHI)...