A new open-source project called Reaper-MCP enables AI assistants to directly control Reaper DAW via the Model Context Protocol, covering the entire music production pipeline from composition to mixing.

Sarah Friar, CFO of OpenAI, introduces a practical AI scorecard to measure ROI through useful work, cost per successful task, dependability, and return on compute.

True diversification across all 11 economic sectors plus bonds, alternatives, and cash protects portfolios. Total market index funds and annual rebalancing are key strategies.

Learn how to connect MCP (Model Context Protocol) servers to Claude Desktop and Claude Code, enabling Claude to interact with external tools, files, databases, and more. This guide covers the MCP architecture, step-by-step setup for both platforms, including one-click Desktop Extensions and JSON config, as well as CLI commands for Claude Code.

Matt Pocock shares his 'grill-me' skill, a short but powerful prompt that makes AI interview users relentlessly about their plans, now with a recommended answer feature to speed up conversations.

The article explores how AI-assisted development leads to 'single-mode burnout' by collapsing the cognitive modes of planning, implementation, and integration, leaving developers exhausted despite increased productivity.

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This article summarizes five recent studies on AI in software engineering, revealing that AI compresses upstream work but creates downstream bottlenecks. Key findings: GitHub Copilot increases PR throughput by ~40% with a dose-response effect; AI coding gains (up to +180%) attenuate dramatically through the delivery process (only +30% more releases); productivity and developer experience decouple over time; developers want AI for verification tasks rather than code generation; and cognitive debt and intent debt are emerging as critical software health concerns alongside technical debt.

JetBrains Research explores how AI combined with Extended Reality (XR) can create new interaction paradigms for tech creators. Through expert interviews, they identified five themes: communicating intent to AI-XR systems, AI making XR environments adaptive, barriers to mainstream adoption, changes in creation workflows, and privacy/ethical risks. The study suggests that the convergence of XR hardware and AI may revolutionize technology creation, though technical, cognitive, and organizational constraints remain.

This dataset provides a single-file, pre-embedded SQLite corpus of the EU AI Act (Regulation (EU) 2024/1689), chunked by legal structure with BGE-M3 dense embeddings, metadata, risk tier labels, and more. It is designed for local query and RAG research, with verified completeness and transparent derivation rules.

NVIDIA released Nemotron 3 Embed on July 15 and 16, 2026. The collection has three open checkpoints: Nemotron-3-Embed-8B-BF16, Nemotron-3-Embed-1B-BF16, and Nemotron-3-Embed-1B-NVFP4. The 8B ranks #1 on RTEB at 78.46 average NDCG@10. The 1B came from ModelOpt NAS pruning plus COS+MSE distillation from the 8B teacher. NVFP4 retains 99%+ of BF16 retrieval accuracy at up to 2x Blackwell throughput. All three run 32,768-token inputs under OpenMDW-1.1.

The author used AI coding agents to port the Python e-book reader epy to Rust, creating repy. The project took months instead of hours and garnered little attention, prompting reflections on the devaluation of software in the age of AI and the meaning of creation.

Netflix revealed in its Q2 earnings report that approximately 300 titles on its platform used generative AI, mostly in post-production, to lower costs and improve efficiency.

Chinese chip designers Moore Threads and Hygon project strong revenue growth driven by surging domestic AI demand. Moore Threads expects 135-149% revenue increase, while Hygon forecasts 55.6-70.2% growth. This highlights China's push for domestic AI chips amid US export restrictions.

Einstein’s field equations, Newton’s universal law and artificial intelligence are among the subjects of Laidlow’s ambitious orchestral works on this NMC debut album.

BoomPop.Games is a browser-based arcade platform that hosts multiple online games, including the sci-fi tactical card game Warpforge, all playable without installation or account creation.

Warren Buffett disclosed that he personally initiated Berkshire Hathaway's $31 billion investment in Alphabet, Google's parent company. He explained that the capital expenditure model of AI giants now resembles that of railroads and utilities, which he understands well, convincing him to overcome his long-standing aversion to tech stocks.

An orchestrator agent that unifies your entire commerce stack, automating workflows for e-commerce businesses.

Lightport is a lightweight AI gateway focused on making LLM providers OpenAI-compatible. It is a fork of Portkey AI Gateway, stripped down to the request/response transformation layer, without retries, caching, etc. Supports 77 providers including OpenAI, Anthropic, Azure OpenAI, and more. Quick start with pnpx lightport.

The European Union has issued two new rules requiring Google to share search data and open its Android operating system to rival AI companies, aiming to foster competition and innovation. Google warns the move could undermine user privacy and security.

This article introduces voidguard, a new tool that detects hollow tests, type gates, and CI conditions that exist but verify nothing. Inspired by a sweep that found seven such void guards in one repository, the tool identifies four types of voids and explicitly acknowledges three it cannot catch. It emphasizes the importance of verifying our verification systems rather than trusting green CI statuses blindly.

OpenAI has encrypted multi-agent v2 messages in its Codex CLI, hiding agent instructions from local history and raising developer concerns about debugging and auditability.

Since 2017, Iason Gabriel has worked at Google DeepMind, trying to anticipate and think through the impact of AI. As commercial and geopolitical pressures escalate, can ethicists make any difference?

This paper proposes ConFlow, a framework that incorporates constraint information directly into the flow matching training objective via differentiable barrier or cost functions and a conditional Gaussian Process, improving constraint satisfaction and trajectory quality in robot motion generation. Experiments on a two-robot navigation task demonstrate lower collision rates and higher trajectory quality compared to standard flow matching baselines.

This paper explores the feasibility of using brain signals via functional near-infrared spectroscopy (fNIRS) to modulate robot reinforcement learning. It compares agents trained on passive (observational) versus active (demonstrative) interaction tasks, and tests multiple methods for enhancing the RL algorithm with the neural signal, focusing on parameter augmentation rather than replacement. The results show that this framework is effective: the neural signal improves learning when augmenting trajectory priorities and state-action q-values. Additionally, the framework learns successfully from offline data, offering a practical alternative for settings where real-time BCI setups are impractical or only limited data is available.

Existing grasp benchmarks focus on visual pose detection, ignoring multi-step reasoning and semantic constraints. GCA-Bench introduces complex action scenarios to evaluate large models. Current methods achieve below 70% success rate, highlighting critical limitations.

DiMaS is a distribution-matching steering strategy for flow-matching vision-language-action (VLA) models, enabling fine-grained behavioral control in robotic manipulation. It transports between representation distributions rather than shifting along a fixed direction, proving effective on two state-of-the-art VLAs. The study also examines transferability and explains why linear steering fails in visuomotor settings: behavioral features are linearly decodable but not linearly steerable.

A new study from arXiv proposes a stochastic filtering protocol (ANTk) for quorum sensing in robot swarms that use anonymous communication. The protocol mitigates double-counting bias common in anonymous protocols, improving estimate stability, though it increases error recovery time. The research compares ANTk with baseline and randomized variants, revealing trade-offs in accuracy, speed, and stability.

MEMORA introduces Embodied Action Memory (EAM) to enable robots to use persistent memory from egocentric video for long-horizon planning. It features four typed memory stores, online editing, and offline consolidation. Evaluated on 45 hours of EPIC-KITCHENS-100 video, MEMORA improves memory accuracy by up to 20.5 points and planning scores by 16.6%.

This paper proposes LIFT, a force-aware post-training framework that adds contact reactivity to pretrained vision-language-action (VLA) policies. By grafting a reactive action expert, injecting 6D end-effector force via causal force memory and cross attention, and coupling with an online DAgger loop, LIFT outperforms vision-only post-training in towel folding, book insertion, and Hanoi ring placement.