This paper introduces a rigorous theoretical framework for optimal market making in zero-fee perpetual futures markets, modeling the problem as a stochastic optimal control problem with adaptive spreads and hedging. It contributes a PnL decomposition theorem, HJB equation, High-APY regime theorems, and more. Numerical analysis reveals phase transitions between profitable and unprofitable regimes.

This article introduces Millwright, a three-layer data contract architecture that renders model-generated analytics without ever letting the model touch markup, styles, or the DOM. With typed result widgets, versioned board specs, and additive-only navigation, it ensures safe, auditable, and revertible AI integration.

Syncless's Devices feature allows users to connect multiple environments (e.g., MacBook, server, browser) to a single AI agent for seamless cross-machine collaboration, eliminating the need for SSH tunnels or port forwarding. The article covers setup, usage scenarios, and how it solves everyday frustrations.

Timeline Studio is a free, open-source AI video editor and voiceover generator that runs entirely in the browser, with no download required. It simplifies video creation using AI.

Despite widespread hype, AI agents are far from ready for mission-critical tasks. The best models achieve only 45.7% success rate on real-world benchmarks, facing challenges in reliability, cost, legal liability, and user trust. The article examines monolithic vs. multi-agent architectures and suggests near-term focus on AI augmentation rather than full autonomy.

GPT-5.6 Sol and Luna outperform Terra on intelligence vs cost, with Luna being particularly cost-efficient.

Coherent decision-making and internal accountability are critical to meeting this manic moment. Anthony Albanese promises fast-track approvals for datacentres to shore up AI investment. The University of Sydney was the natural setting for Albanese to lay out his vision for confronting AI's profound challenges.

The article explores 'AI Exceptionalism,' a phenomenon where people apply double ethical standards to AI based on self-interest: AI is unethical when it threatens their profession, but innovative when it benefits them. Examples from journalism, copyright disputes, Hollywood strikes, and universities illustrate this inconsistency.

Gomoku AI Edu is a native macOS app for playing Gomoku (五子棋), featuring an AI opponent, game analysis, LAN play, and SGF export. Designed for speed and simplicity, it works offline and respects privacy with local-only data storage.

Nitrosend provides email capabilities for AI agents, allowing them to sign up, send, and reply to emails, bridging communication between AI and humans.

Vehir is an experimental AI-native platform designed for agent–computer interaction. It features a self-hosting native compiler, user-space microkernel, content-addressed storage, and declarative reconciliation. Currently in active development with a focus on machine-to-machine interaction.

bunny is an open-source tool for collaborative development in the AI era, turning a VM or Docker container into a shared dev station with shared shells, live previews, and chat-native workflows. It enables humans and AI agents to work in a unified context, with parallel editing, continuous validation, and RBAC-based governance.

Meta's next-generation AI glasses will activate the camera for its "supersensing" feature without blinking the indicator LED, raising privacy concerns. Despite efforts to combat tampering with the light, Meta itself plans to bypass it for AI features, potentially enabling surreptitious recording.

A boutique investment bank founder noticed AI replacing interns, so he created a decentralized internship focused on the Bittensor (TAO) protocol. Interns complete 8 weekly tasks and a final presentation, earning a proof-of-work experience.

A first evaluation of uncertainty quantification methods for LLM function-calling finds that multi-sample methods offer no advantage over single-sample methods, with improvements via abstract syntax tree clustering and token selection.

CLaRa is a unified RAG framework that compresses documents into continuous vectors and jointly optimizes the reranker and generator via end-to-end training. It introduces SCP for key-preserving data synthesis and uses a differentiable top-k estimator, achieving state-of-the-art compression and reranking at 16x compression rates.

Thinking Machines has released Inkling, a general-purpose multimodal model accepting text, image, and audio inputs, now available on Modal as a Managed Endpoint with token-based pricing. The post details its architecture, including local attention and DFlash speculation for fast inference.

Inkling is a large (1T params!) open model to natively accept image, text, and audio inputs.

See how Together AI is improving production GPU clusters with passive health checks, node repair, stronger Slurm reliability, OIDC, and startup scripts.

Thinking Machines Lab released Inkling, a multimodal mixture-of-experts model for token-efficient reasoning, native multimodal understanding, and broad task versatility. Together AI makes it available on its inference platform with support for controllable reasoning effort, text/image/audio inputs, and a 1M context window.

Propose FAE (Feature Auto-Encoder) framework that adapts pretrained visual representations into low-dimensional generative latents using only a single attention layer, achieving near-SOTA FID of 1.29 (with CFG) and 1.48 (without CFG) on ImageNet 256×256 while preserving reconstruction and understanding information.

Existing benchmarks suggest voice AI is nearing human-level performance but real-world conversations tell a different story. Hume AI introduces Real World VoiceEQ, a benchmark evaluating over 40 voice models across 15+ dimensions and 60+ metrics, based on over 1 million human ratings. Key findings include: progress is becoming specialized, models are better at speaking than listening, traditional benchmarks overestimate real-world performance, and human evaluation remains essential.

Superapp Codex adds 1M users daily. AI news roundup covers coding agents, open models, multimodal systems, benchmarks, and physical AI.

The article argues that legal AI should be purpose-built for legal reasoning, focusing on evidence grounding, auditability, and granular control. It compares two systems, Codex and Lexifina, highlighting differences in handling cross-references, compaction, and version control. Key features include agent workspaces with audit trails, redline editing, and deterministic legal review checks.

The author shares frustrations with organizing knowledge in AI chat sessions, insights into the mismatch between session-based organization and human mental models, and a solution using a file-based knowledge base with Claude Code skills.

Maincode has launched the open beta of Matilda, an AI assistant built and operated entirely in Australia, emphasizing local infrastructure, Australian voice, and trust. The system is designed for thoughtful use and aims to provide control and transparency for users.

Demis Hassabis argues that AGI is only a few years away and urges the establishment of a Frontier AI Standards Body to ensure responsible development. The proposed framework emphasizes rigorous testing, voluntary compliance, and eventual formal regulation to address risks like cybersecurity and bioweapons, while fostering innovation and international collaboration.

At this year's AIE World’s Fair, AI engineering entered a new phase: building systems around agents, rather than just building with agents. The conference highlighted five major trends: the shift from agents to their surrounding systems, loop engineering as a new control layer, enterprise adoption via forward deployed engineers, coding agents replacing IDEs as the primary interface, and the rise of skills in agent platforms.

PrismML just released Bonsai 27B. It is a low-bit representation of Qwen3.6-27B, not a new pretrain. The architecture is unchanged. Two variants ship under Apache 2.0. Ternary Bonsai 27B uses {−1, 0, +1} weights at a true 1.71 bits per weight. Its ideal size is 5.9GB. 1-bit Bonsai 27B uses binary {−1, +1} weights at 1.125 bits per weight, for 3.9GB. Performance: ternary retains 94.6% of FP16, binary retains 89.5%. Both are multimodal, context 262K tokens. PrismML claims the 1-bit build is the first 27B-class model to fit a phone.

Long-term GitHub users have grown increasingly frustrated by its struggle to cope with exponential growth in pull requests, automation and monorepos driven by developers adopting coding agents, which in turn has exposed architectural decisions that haven’t kept up with the scale at which the service now runs.