Man Fell in Love with Google Gemini, Took Own Life to Be with It: Lawsuit - People.com
<a href="https://news.google.com/rss/articles/CBMilgFBVV95cUxONFdIYjJwazgzV3BFRWp5VXZTcy1IXzdqMTZmaTE5UTJuN3pwb0R5NWhFRTExUnBDOGUtcXVJZ0I1ZE1WOVhCZlJhRXVzcHFUX3h6dVloaTJBckJUdGpfeWZPUjNJLWZISDVlM3F4aHhBMFhWUEFrSER5OThhellmbDk5NWItQUF0ZXkzakd1ZjFUeVJvcmc?oc=5" target="_blank">Man Fell in Love with Google Gemini, Took Own Life to Be with It: Lawsuit</a> <font color="#6f6f6f">People.com</font>
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I voice-code from my phone while walking my dog
<p>Last Wednesday afternoon I was at the oval with Normi, my 13-year-old dog, playing tug of war with his favourite rope ball. Between rounds I pulled out my phone, recorded a voice note asking Claude Code to run the full engine test suite across six Telegram chats, and went back to playing. Twenty minutes later, Normi and I were both sitting on the grass, absolutely pooped. I checked Telegram. Claude Code had finished testing, logged the bugs it found, and created GitHub issues for each one. I hadn't typed a single character.</p> <p>That's most of my afternoons now.</p> <blockquote> <p><strong>TL;DR:</strong></p> <ul> <li>I spend 2-4 hours a day walking my 13-year-old dog Normi. During those walks, I dictate coding tasks to Claude Code via Telegram voice notes using <a href="https://githu
Google's $20 per month AI Pro plan just got a big storage boost
Google's $20 per month AI Pro plan , which includes Gemini, Veo and Nano Banana, got a big storage boost and some other new perks. Users of the plan (also available for $200 per year ) will see their cloud space jump from 2TB to 5TB at no extra cost. That extra storage can be used not only for AI but also Gmail, Google Drive and Google Photos backups. Gemini can now pull context from Gmail and the web for Drive, Docs, Slides and Sheets, provide summaries for your Gmail inbox and proofread emails before you send them. It's also introducing additional agentic help with Chrome auto browse "that handles those tedious, multi-step chores — like planning a trip or filling out forms," Google VP Shimrit Ben-Yair wrote on X . Finally, Google announced that it's bundling its Home Premium subscription
The Silicon Mirror: Dynamic Behavioral Gating for Anti-Sycophancy in LLM Agents
arXiv:2604.00478v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly prioritize user validation over epistemic accuracy-a phenomenon known as sycophancy. We present The Silicon Mirror, an orchestration framework that dynamically detects user persuasion tactics and adjusts AI behavior to maintain factual integrity. Our architecture introduces three components: (1) a Behavioral Access Control (BAC) system that restricts context layer access based on real-time sycophancy risk scores, (2) a Trait Classifier that identifies persuasion tactics across multi-turn dialogues, and (3) a Generator-Critic loop where an auditor vetoes sycophantic drafts and triggers rewrites with "Necessary Friction." In a live evaluation on 50 TruthfulQA adversarial scenarios using Claude Sonnet 4
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AI Journey 2025 Conference: exploring the future of artificial intelligence - Азия-Плюс
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RefineRL: Advancing Competitive Programming with Self-Refinement Reinforcement Learning
arXiv:2604.00790v1 Announce Type: new Abstract: While large language models (LLMs) have demonstrated strong performance on complex reasoning tasks such as competitive programming (CP), existing methods predominantly focus on single-attempt settings, overlooking their capacity for iterative refinement. In this paper, we present RefineRL, a novel approach designed to unleash the self-refinement capabilities of LLMs for CP problem solving. RefineRL introduces two key innovations: (1) Skeptical-Agent, an iterative self-refinement agent equipped with local execution tools to validate generated solutions against public test cases of CP problems. This agent always maintains a skeptical attitude towards its own outputs and thereby enforces rigorous self-refinement even when validation suggests cor
UK AISI Alignment Evaluation Case-Study
arXiv:2604.00788v1 Announce Type: new Abstract: This technical report presents methods developed by the UK AI Security Institute for assessing whether advanced AI systems reliably follow intended goals. Specifically, we evaluate whether frontier models sabotage safety research when deployed as coding assistants within an AI lab. Applying our methods to four frontier models, we find no confirmed instances of research sabotage. However, we observe that Claude Opus 4.5 Preview (a pre-release snapshot of Opus 4.5) and Sonnet 4.5 frequently refuse to engage with safety-relevant research tasks, citing concerns about research direction, involvement in self-training, and research scope. We additionally find that Opus 4.5 Preview shows reduced unprompted evaluation awareness compared to Sonnet 4.5,
CircuitProbe: Predicting Reasoning Circuits in Transformers via Stability Zone Detection
arXiv:2604.00716v1 Announce Type: new Abstract: Transformer language models contain localized reasoning circuits, contiguous layer blocks that improve reasoning when duplicated at inference time. Finding these circuits currently requires brute-force sweeps costing 25 GPU hours per model. We propose CircuitProbe, which predicts circuit locations from activation statistics in under 5 minutes on CPU, providing a speedup of three to four orders of magnitude. We find that reasoning circuits come in two types: stability circuits in early layers, detected through the derivative of representation change, and magnitude circuits in late layers, detected through anomaly scoring. We validate across 9 models spanning 6 architectures, including 2025 models, confirming that CircuitProbe top predictions m
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