Show HN: Caddy plugin that charges AI crawlers real USDC to access your site
Caddy middleware implementing HTTP 402 protocol to charge AI crawlers USDC on Base blockchain for content access.
Caddy middleware implementing HTTP 402 protocol to charge AI crawlers USDC on Base blockchain for content access.
Framework for improving text reconstruction in 3D Gaussian Splatting scenes. Addresses preservation of fine-grained textual elements in 3D representations.
Pixels is a sandbox running on TrueNAS homelab using Incus containers for testing AI agent CLIs without paid services.
Opinion piece on AI agents and workforce reduction, citing Jack Dorsey and Dario Amodei on automation of software engineering.
Essay on five architectural decisions for AI products based on real-world experience, covering cost and reliability pitfalls.
Httap is an HTTP proxy tool for terminal and AI agents to intercept, inspect, and mock HTTP traffic with automatic browser profile management.
Desktop application orchestrating Claude Code agent teams with specialized roles. Enables dependency graphs, parallel/sequential workflows, and multi-model coordination.
APort is a public CTF stress-testing framework for AI agent guardrails and safety mechanisms in autonomous financial systems.
Speculation on smartphone era ending due to new AI device project from designer Jony Ive.
Incomplete title-only entry about PewDiePie training an AI coding model.
Tchop.io is described as a fully AI-powered community framework with user control and ownership.
FAR uses persistent .meta sidecar files to augment file readability for AI coding agents, addressing 30-40% context blindness.
System to generate job descriptions from real engineering tasks and evaluate candidates against code evidence from GitHub/Jira, PRs and diffs.
Backend development framework using Model Context Protocol (MCP) for building systems with AI assistance.
Free business directory API with 11M+ businesses, full-text search and geo-location for AI agents to query real-world business data reliably.
Framework for governing autonomous AI agents in production environments, addressing safety and control.
Video about enshittification.
Research on LLM-generated passwords being predictable, exposing security vulnerabilities in password generation tasks.
Discussion about how LLM prevalence affects open source contributor motivation and reputation, questioning whether AI-generated code diminishes accomplishment recognition.
Commentary on concentration of AI infrastructure ownership among large conglomerates.
Collection of 380+ agent skills from Anthropic, Google, Vercel, Stripe and other teams for use with Claude, Codex, Gemini CLI and similar platforms. Real-world skills, not auto-generated.
MIT study reports agentic AI moving mainstream with capabilities outpacing governance; notes OpenAI hired OpenClaw framework creator.
Analysis of legal and regulatory risks from AI agents equipped with crypto wallets for autonomous transactions and hiring.
Anthropic offers 6 months free Claude Max 20x to open-source maintainers and contributors through rolling application review.
Kill switch governance tool for autonomous AI agents using LangChain, preventing agent sprawl and cost overruns from runaway recursion.
Discusses designing LLM applications as systems built around models, planning for quarterly model swaps rather than model-centric architecture.
Discussion about journaling's long-term effects on self-understanding, unrelated to AI/tech interests.
Claim that AI agent supply chain has problems with proposed solutions, no substantive details provided.
Case study of AI voice agents deployed in hotels analyzing 15,910 real guest interactions and lessons learned from deployment.
Personal experience using AI-assisted coding with GLM 4.7/5 models and Claude CLI for debugging and development tasks, particularly Vulkan code.
Open source static documentation generator from single Markdown file with AI agent support via llms.txt format. Includes CLI tool, dark mode, search indexing.
OpenAI and Amazon announce multi-year strategic partnership with $50B investment. Joint development of Stateful Runtime Environment for enterprise AI.
Amazon Bedrock launches Stateful Runtime Environment for AI agents, powered by OpenAI models. Enables multi-step reliable agent execution with tool integration and operational controls.
Joint statement from OpenAI and Microsoft reaffirming their partnership and collaboration since 2019.
Funding announcement for AI company with $110B investment from SoftBank, NVIDIA, and Amazon. Strategic partnership with Amazon and NVIDIA for compute infrastructure.
Analysis of backdoor vulnerabilities in multimodal diffusion language models with self-purification defense mechanism.
Benchmark evaluating LLMs on financial knowledge through exam questions and practical business reasoning scenarios.
Deep learning approach for computing accurate geodesic distances on continuous surfaces via polygonal mesh discretization.
Training-free framework for multimodal information retrieval using MLLMs without large datasets or pre-training fine-tuning.
Framework for multi-level causal embeddings that generalize abstraction and preserve causal relations across coarse and detailed models.
Large-scale hypothesis screening of biological foundation models to understand what geometric and topological structures they learn from gene expression data.
Multimodal LLM framework analyzing video ad effectiveness by examining the first three seconds using visual, audio, and text analysis.
Algorithm for testable learning of Massart halfspaces under Gaussian distribution with tester-learner framework.
Analysis of function vectors in LLMs showing they lack invariance across input formats despite targeting same concepts.
Testing framework to diagnose whether MLLMs genuinely read text in images or rely on parametric shortcuts in prompts.
Topology optimization post-editing tool using structured latent embeddings for fast localized design revisions.
GAN-based speech reconstruction from mmWave radar signals captured through glass with low SNR using dual-conditioned architecture.
Conformal prediction method for gradient-boosted trees that improves uncertainty quantification under heteroscedasticity without auxiliary models.
GetBatch: Object store API elevating batch retrieval to first-class operation for efficient ML data loading across storage clusters.
veScale-FSDP: Enhanced FSDP distributed training framework supporting block-wise quantization and non-element-wise optimizers.