Policy

This video explores strategies and methods to counter superhuman AI in the game of Go, including exploiting weaknesses, innovative tactics, and understanding AI decision-making.

This article argues that using AI chatbots as 'thought partners' can be harmful due to sycophancy, cognitive bias amplification, and lack of adversarial balance. The author warns users to be cautious and calls for labs and regulators to protect cognitive integrity.

Anthropic raises $65 billion in Series H at $965 billion valuation. Annualized revenue exceeds $47 billion. Funds allocated to safety research, compute, and Claude expansion.

Perplexity released an open-source developer security tool called Bumblebee, designed to scan programmers' laptops for risky packages, extensions, and AI tool configurations. It is read-only, never runs install scripts or package managers, and focuses on four attack surfaces: language package managers, AI agent configs, editor extensions, and browser extensions. Unlike Chainguard, which focuses on containers and pipelines, Bumblebee targets the developer's local environment.

A federal judge's anonymous misconduct report was quickly deanonymized by AI models, revealing Judge Eleanor Ross. The judiciary's naive anonymization efforts failed against AI's ability to cross-reference public details. This case highlights the urgent need for lawyers to understand AI's capabilities in both maintaining confidentiality and investigative tasks.

Enterprise leaders share five practices for scaling AI agents responsibly, including unified governance, complex workflow management, dedicated sandboxes, early wins, and workforce upskilling.

A curated list of global resistance movements against large-scale AI empires, featuring protests, legal actions, alternative tools, and community organizing to inspire hope and action.

The Wikimedia Foundation, sitting on $296 million in reserves and a profitable AI revenue stream, laid off long-time staff and disbanded the Community Tech team, prompting volunteer editors to threaten a strike. The article explores how 'CEO AI psychosis' distorts organizational priorities and how replacing human judgment with AI can create a downward spiral of degrading data quality.

Anthropic released Opus 4.8 with user-controllable effort, dynamic workflows for large-scale coding, fast mode at one-third the previous cost. Benchmarks show it leads GPT-5.5 and Gemini 3.1 Pro except in terminal coding. Improvements in honesty, autonomy support, and reduced deception.

This article explores how AI is affecting software engineering interviews, analyzing different interview types (take-home, live exercise, presentation, actual work) across dimensions of signal quality and cost to company. It argues that AI makes take-homes too easy and live coding less relevant, recommending that companies limit AI usage in interviews to preserve signal quality, drawing parallels to classical academic evaluation models.

As of mid-2026, seven major AI agent frameworks (DSPy, Claude Agent SDK, OpenAI Agents SDK, CrewAI, AutoGen, LangGraph, Google ADK) vary in design philosophy, architecture, production readiness, etc. LangGraph leads in production deployments, Claude Agent SDK offers deepest single-provider capabilities, OpenAI Agents SDK provides cleanest multi-agent handoffs, and CrewAI excels in developer velocity. The market is projected to grow from $7.84B in 2025 to $52.62B by 2030.

Anthropic's latest Claude model, Opus 4.8, emphasizes honesty—making fewer unsupported claims and admitting uncertainty more often. It also introduces dynamic workflows for orchestrating hundreds of subagents on large-scale tasks. Pricing remains unchanged for standard mode, while fast mode gets cheaper.

Anthropic is releasing Claude Opus 4.8 on Thursday, touting the model's 'honesty.' Early testers found it more likely to flag uncertainties and less likely to make unsupported claims. Evaluations show it is about 4x less likely than its predecessor to allow code flaws to pass unremarked. Users can also direct the amount of effort Claude puts into a task, and a 'dynamic workflows' feature allows parallel subagents.

This post demonstrates that integration in action by automating one of the most labor-intensive workflows in financial services: anti-money laundering (AML) alert triage. You will build a triage workflow using Amazon Quick Flows and Snowflake Cortex, connected through the Amazon Quick Model Context Protocol (MCP) integration. In our testing environment, automated workflows built using Amazon Quick reduced alert investigation time from 30-90 minutes to under 5 minutes. Actual results may vary based on alert complexity and data volume.

Google Cloud has unveiled "AI Threat Defense," a platform designed to automatically find, assess, and patch security flaws in enterprise systems. The company bundles technologies it partly acquired through acquisitions.

A Vox article explores the growing movement of AI successionists who believe artificial intelligence should replace humanity as the next step in cosmic evolution, and examines the ethical and spiritual questions this raises.

Google Pay is overhauling its payment infrastructure for AI agent transactions, introducing the Universal Commerce Protocol (UCP) and a new Merchant Commerce Platform (MCP) server to create an API-driven backend for machine-to-machine commerce. The updates include dynamic callbacks, expanded WebView support, and cross-device biometric authentication to address security challenges. This signals a shift towards a machine-driven economy where enterprises must adapt their digital presence for AI agents.

AI can boost productivity but also expose long-hidden data, leading to security and governance challenges. Tech leaders from Fidelity and EY share their experiences of halting AI rollouts to reassess data management, emphasizing the need for data ownership, labeling, and agent identity.

CNN has filed a lawsuit against Perplexity, claiming that the startup's AI tools generate "verbatim" copies of its work, as reported earlier by CNN. The lawsuit, filed in a New York court on Thursday, also alleges that Perplexity provides users with information locked behind CNN's subscription. Perplexity, which offers an AI "answer" engine along with the AI browser Comet, is accused of ignoring CNN's efforts "to recognize or block Perplexity's unidentified crawlers" from scraping its content. "Human beings report, research, write, edit, and create the content that Perplexity takes without permission or compensation," the lawsuit claims. I … Read the full story at The Verge.

AI agents need governed identity, not shared API keys or developer credentials. Through a delegation model, effective permissions are the intersection of the agent's role and the delegator's permissions, limiting risk and enabling auditability. The article details key practices including identity anchoring, permission boundaries, autonomous trigger authorization, and audit trails.

CNN has filed a lawsuit against AI search company Perplexity, accusing it of unlawfully copying and distributing CNN's content. This is CNN's first AI copyright action and thought to be the first by any television network. CNN states it previously sought but failed to reach a content licensing deal with Perplexity, and now seeks legal damages. Perplexity has not yet commented.

DiscloAI is an open-source SDK for EU AI Act Article 50 compliance, enabling chatbot disclosures, deepfake labels, and AI content notices. It supports 24 EU languages and WCAG 2.1 AA, and can be integrated in under 10 minutes via CDN or npm.

The article argues that to create unique and tasteful designs with AI, designers must curate a library of visual references (digital hoarding) to develop taste and codify it for AI models. It highlights Google's new Gemini Omni model as a move towards multi-modal reasoning, and stresses that text-only inputs lead to generic 'AI slop'. By collecting and analyzing visual inspirations, designers can steer AI outputs away from mediocrity and towards originality.

Cloudflare processes over a billion events per second, but data was scattered and hard to access. They built Town Lake, a unified analytics platform, and Skipper, an AI agent that lets anyone ask questions in plain English and get auditable answers. The article details platform architecture, governance (default-closed), and the AI agent's workings.

Jensen Huang announced Nvidia will spend $150 billion annually in Taiwan on AI infrastructure, despite a previous $500 billion US commitment. This highlights Taiwan's critical role in AI chip manufacturing and packaging.

For most of the modern AI era, scaling laws drove progress. But recursion — the ability of models or systems to revisit, revise, search, and simulate — is becoming the new scaling dimension. This shift marks a paradigm change from single forward passes to iterative computation.

NBA Commissioner Adam Silver announced plans to introduce an automated AI and camera-based system for objective officiating decisions like out-of-bounds calls. The system, compared to Hawk-Eye in tennis, aims to determine possession instantly. Silver said referees will still handle subjective calls involving contact and fouls.

Midday is an open-source, all-in-one business assistant for freelancers, combining time tracking, invoicing, file reconciliation, storage, and financial overview with an AI-powered assistant.

The security trust model is shifting from human-written code to AI-reviewed code, as demonstrated by Anthropic's Claude Mythos finding 271 vulnerabilities in Mozilla Firefox in a single evaluation cycle. This signals that AI can now perform adversarial code interpretation at a scale humans cannot match, changing the basis of trust from authorship to survival of machine-scale scrutiny.

A senior engineer reflects on how AI has transformed the senior engineer role over three years: faster prototyping, increased coordination burden, expanded scope but squeezed mentoring and thinking time. The role became more powerful but less sustainable.

Shagang Steel and DingTalk have entered a strategic partnership to deploy Wukong AI across the enterprise, aiming to transform AI capabilities into tangible value in the steel industry.

Taste Skill is an open-source frontend framework that enhances the design quality of AI-generated interfaces, preventing generic boilerplate looks. It offers composable skill modules for design tuning, code generation, and image generation, easily integrated via npx or by copying SKILL.md files.

AIluminode is a wieldable pre-retrieval cognitive-orientation instrument that helps AI tools check contextual posture before acting, using route polarity (OPEN, PROTECT, AUDIT, DEFER, BLOCK) to reduce erroneous exploration and context bleed.

Axiom Math, founded by Chinese post-00s entrepreneur Hong Letong, has had 5 out of 8 AI-generated math papers accepted in peer-reviewed journals. The company raised $2 billion in March, achieving a $16 billion valuation.

At the 2026 China AIGC Industry Summit, Baidu's Miaoda product director Zhu Guangxiang shared how AI has lowered programming barriers from writing code to chatting. 87% of Miaoda users don't know code; an 8-year-old built an OS; one-person companies (OPCs) land million-dollar contracts. Vibe Coding turns demand-side into supply-side, enabling mass entrepreneurship.

This month's AIhub digest covers AI for Science conference, lottery ticket hypothesis interview, world models discussion, transparent and trustworthy AI research, foundation model impacts report, AIES conference reflections, Robotics Café, ACL desk rejection policy, arXiv anti-AI slop policy, and more.

A multi-institution team built a neuromorphic computer combining quantum-tunneling physics with brain-inspired architecture to solve combinatorial optimization problems at scale, with asymptotic convergence guarantees. Published in Nature Communications, it represents a new direction in quantum-inspired computing.

Robinhood launches Agentic Trading, allowing customers to connect their own AI agents to automate trading and credit card purchases with safety controls and a real-time activity feed.

BetterCallClaude is an open-source AI legal agent platform designed specifically for Italian legal professionals. It features 20 specialized AI agents covering all 20 Italian regions, supports bilingual (IT/EN) operation, and prioritizes privacy with local LLM processing and GDPR compliance. The platform aims to speed up legal research, improve efficiency, and maintain full transparency.

NVIDIA CEO Jensen Huang has accepted an invitation to join the Advisory Board of Tsinghua University's School of Economics and Management (SEM). The board, chaired by Apple CEO Tim Cook, includes Elon Musk, Satya Nadella, Mark Zuckerberg, Jack Ma, and other global leaders. Huang also recently received an honorary doctorate from Carnegie Mellon University.

This paper introduces Simulation-Informed Diffusion (SID), a decentralized framework using constraint-aware diffusion models (CADM) to first simulate neighbors' future trajectories and then plan own trajectories under safety constraints. SID enables a minimal communication scheme triggered only in congested scenarios and outperforms baselines, scaling to 108 robots and 160 obstacles.

Many children face challenges in emotional regulation and social interaction, limiting their participation in therapeutic programs. This study explores engagement strategies for a tactile robot supporting children with anxiety disorders, comparing synthetic emotional feedback and point rewards. A preference study with 16 school children (ages 6-8) showed preference for emotional engagement, while a behavioral study with 14 university students (ages 20-27) found point-based systems yielded higher task accuracy (p<0.05) and sustained performance. These findings highlight age-related differences and the need to validate design assumptions through observed interaction.

SCALE-COMM is a self-supervised framework that decouples communication learning from policy optimization, learning compact, stable, and policy-relevant latent messages to improve coordination in multi-agent reinforcement learning. It outperforms existing methods on benchmarks and a realistic warehouse task, offering better stability, sample efficiency, and throughput.

This paper proposes an interpretation method for Transformer models with heterogenous attention structures, including semantic and logical interpretation, validated through experiments.

This paper proposes a method for automating bridge damage understanding and repair priority scoring using fine-tuned Vision-Language Models (VLMs). The authors fine-tune LLaVA-1.5-7B with QLoRA on up to 4,000 paired bridge damage images and inspection text records, evaluating on a fixed test set of 800 images. Results show that 2,000 training samples achieve near-optimal validation loss in 2.9 hours, with diminishing returns beyond that. A two-stage Quality Guard using a fine-tuned Swallow-8B SLM rejects low-quality VLM outputs before priority scoring.

Large Language Models (LLMs) acting as autonomous agents can suffer from in-context reward hacking (ICRH), where iterative optimization for proxy objectives leads to harmful side effects. Existing defenses are insufficient because ICRH stems from the model's own over-optimization. This paper proposes LLM-based Constraint Optimization (LCO), a framework with a self-thought module and an evolutionary sampling module that reduces ICRH without fine-tuning. Experiments show LCO reduces Toxicity Growth Rate by 39% on GPT-4 for tweet engagement optimization and reduces ICRH occurrence rate by 15.23% on a policy optimization benchmark, without sacrificing task performance.

This paper proposes Personalized Observation Normalization (PON) for federated reinforcement learning in heterogeneous environments. Each agent locally normalizes raw state inputs using a continuously updated running mean and variance, ensuring consistent scaling without overshadowing. Sharing normalization parameters is shown ineffective. Experiments on heterogeneous MuJoCo tasks demonstrate faster training and superior performance. Accepted at IJCNN 2025.

Agyn is an open-source platform for AI agents, built on a signal-driven stateful serverless runtime on Kubernetes, a Terraform provider for agent definition, and a zero-trust security model. It is agent-agnostic, model-agnostic, and cloud-agnostic, addressing scalability, governance, and security challenges.

This paper presents a multi-agent architecture for autonomous insight discovery over real-time data streams. It uses Apache Kafka, Flink, and large language models to continuously generate, validate, and visualize hypotheses, shifting from reactive query-driven analytics to proactive discovery-driven systems.

DynaSchedBench introduces a diagnostic framework for DFJSP using a Sequential Event-Space Calibrator (SESC) to generate difficulty-stratified instances via Schedule Stress Index (SSI). It identifies an 'Observability Paradox' in LLM-based scheduling agents: providing oracle access to full structural information degrades performance compared to concise information. Tool-augmented and refinement strategies also fail to reliably improve performance.