A new study reveals that optimizing the orchestration layer (Harness) can significantly reduce costs and improve efficiency in enterprise agentic AI, more than model choice alone. Experiments show the Writer Agent Harness cuts cost per task by 41%, time by 44%, and tokens per task by 38%, while maintaining quality.

Recent advances in AI for Mathematics have focused largely on autoformalization and theorem proving. This paper proposes a ReAct-style agentic setup combining LLM reasoning with verifiable feedback from SageMath and Context7 documentation. Evaluated on research-level problems from RealMath, the setup shows substantial performance gains averaging 9.7 pp, with GPT-5.5 achieving 75.2% solve rate. Accepted to ICML 2026 3rd AI for Math Workshop.

Researchers propose two cost-effective agent architectures—Explorer-Definer Pipeline and Reflective Orchestrator—achieving 57.50% and 67.25% pass@2 on ARC-AGI-1 at $0.25 and $0.62 per task respectively, without benchmark-specific training or heavy test-time compute.

QANTIS treats a quantum processor as a calibrated belief-update service for autonomous systems under partial observability. Using IBM Heron hardware on the Tiger POMDP, the study shows that all-step fixed-point amplification preserves the posterior across sequential steps, with hardware posteriors matching exact Bayes posteriors in all decision checks. Boundary-aware BIQAE stabilizes amplitude estimation, and a rare-event sweep maps sample complexity for one-in-a-million evidence.

Researchers introduced a scalable Hybrid Agent-based and Language-driven Epidemic (HALE) modeling framework that leverages large language models (LLMs) to predict human decision-making in agent-based modeling (ABM), with a proof-of-concept simulation of COVID-19 in Salt Lake County, UT.

This paper provides a theoretical analysis of in-context search in LLMs, modeling it as approximate inference over reasoning traces. It shows that when reflections reliably localize early mistakes, in-context search yields exponential improvements with only polynomial sequential attempts; otherwise, no asymptotic benefit over parallel sampling. Gains are robust, learnable, and connect to optimal policy in reinforcement learning.

AgentLens is a production-assessed benchmark for interactive code agents that evaluates the entire trajectory — instruction following, tool usage, self-verification, error recovery, and communication — rather than just pass/fail. It pairs formal verification with LLM-written trajectory reviews and side-by-side comparisons to provide readable explanations of scores. Useful for model diagnosis, version comparison, and regression detection. Open-sourced on GitHub.

China is implementing a sweeping higher education reform, eliminating thousands of outdated degree programs while rapidly expanding offerings in artificial intelligence and other emerging technologies. Between 2021 and 2025, over 12,000 undergraduate programs were cut and 10,000 new ones introduced, affecting more than 30% of the country's university courses. This strategic realignment is driven by rising youth unemployment and China's ambition to become a global leader in advanced technologies. Programs in humanities and arts are disproportionately reduced, while fields like AI, robotics, and data science are prioritized to align universities with national industrial goals. This contrasts with financially-driven program cuts often seen in US higher education, as China's government-led initiative aims to address labor market demands and enhance economic competitiveness.

Figment is a personal AI you can text, curious about you and proactively finding ways to help while feeling like a friend. It has its own 24/7 computer and browser, and friends experienced many magical moments during two weeks of testing.

The main bottleneck for AI infrastructure is grid interconnection, not energy shortage. Queue times have ballooned from 20 months to 55 months. Market mechanisms work, but grid planning lags.

This article explores how AI automation threatens the economic development model of poor countries that rely on exporting cheap labor and services. It traces the historical ladder of development from agriculture to manufacturing to services, noting that manufacturing employment is peaking earlier in developing countries. Service exports like IT and call centers are also at risk, with early indicators showing reduced hiring of new graduates. While cheaper human labor may temporarily compete, rapidly falling AI costs could eventually eliminate that advantage, leaving poor countries with fewer pathways to growth.

A comprehensive guide to the best Character AI alternatives in 2026, comparing Polybuzz, Chai, Silly Tavern, Swerve, and chatbrat.ai, with a focus on personality, memory, and social arcade features.

SlopWatch is a Chrome extension that lets users rate webpages for AI-generated content. Community ratings produce a 'Slop Score' to indicate how likely content is AI-generated. Currently rated 4.3/5, it aims to increase transparency online.

Current AI introduces the Open Source Gap Map v0.1, a living visualization of the open source AI landscape based on surveying over 24,626 projects, assessing openness, capability, and adoption, to identify high-leverage gaps and rally community efforts.

Ghost is a real-time AI interview coach that provides instant, natural answers during job interviews. It works in under 3 seconds, offers four tone modes, and is free to start with a pro version at $12/month.

Ant Group's Robbyant has released LingBot-VLA 2.0, an Apache-2.0 vision-language-action model for cross-embodiment robot manipulation. The 6B checkpoint is pretrained on roughly 60,000 hours of data, spanning 50,000 hours of robot trajectories across 20 robot configurations and 10,000 hours of egocentric human video. It maps every embodiment into a single 55-dimensional canonical action space, covering arms, dexterous hands, waists, heads, and mobile bases. A token-level, auxiliary-loss-free Mixture-of-Experts action expert scales capacity without adding a load-balancing loss. Dual-query distillation from LingBot-Depth and DINO-Video adds geometric and temporal supervision for future-aware control. On the GM-100 generalist benchmark it outperforms π0.5 and LingBot-VLA-1.0 on both evaluated platforms.

KPMG survey finds nearly a third of execs struggle to understand costs as companies rethink deployments.

Ant Group's Robbyant has released LingBot-VLA 2.0, an Apache-2.0 vision-language-action model for cross-embodiment robot manipulation. The 6B checkpoint is pretrained on roughly 60,000 hours of data, spanning 50,000 hours of robot trajectories across 20 robot configurations and 10,000 hours of egocentric human video. It maps every embodiment into a single 55-dimensional canonical action space, covering arms, dexterous hands, waists, heads, and mobile bases. A token-level, auxiliary-loss-free Mixture-of-Experts action expert scales capacity without adding a load-balancing loss. Dual-query distillation from LingBot-Depth and DINO-Video adds geometric and temporal supervision for future-aware control. On the GM-100 generalist benchmark it outperforms π0.5 and LingBot-VLA-1.0 on both evaluated platforms.

On-policy distillation provides dense per-token supervision for reasoning models, but its effectiveness varies. This research introduces a training-free diagnostic framework that quantifies the alignment between distillation signals and the ideal gradient at the per-token level. Findings show that distillation guidance aligns better on incorrect rollouts, and the optimal context depends on student capacity and task, with no universal best configuration.

This paper introduces SRLM, a framework that augments recursive language models with self-reflective program search using uncertainty signals (self-consistency, reasoning trace length, verbalized confidence). It achieves up to 22% improvement over RLMs and shows that recursion itself is not the primary driver of performance.

Learn how GPT-5.6 powers Microsoft 365 Copilot with stronger AI capabilities across Word, Excel, PowerPoint, Chat, and Cowork for faster, higher-quality work.

Multimodal large language models (MLLMs) have recently shown strong performance in visual understanding, yet they often lack temporal awareness, particularly in egocentric settings. Apple researchers propose Temporal Global Policy Optimization (TGPO), a reinforcement learning algorithm that uses verifiable rewards to incentivize temporal reasoning over frame-level shortcuts.

Serving 8.9 million developers, Ollama has raised $88M from Benchmark, Theory Ventures, 8VC, Y Combinator, and many incredible angel investors.

Jarred Sumner details the rewrite of Bun from Zig to Rust using AI coding agents. The TypeScript test suite served as a conformance suite, enabling automated porting. The rewrite cost $165,000 in API tokens, and the new Rust version has been live in Claude Code since June 17th, with 10% faster startup on Linux.

SpaceXAI has launched Grok 4.5, its smartest model yet, trained with Cursor for coding, agentic tasks, and knowledge work. Priced at $2/M input tokens and $6/M output tokens, it serves at 80 TPS and leads on Harvey's Legal Agent Benchmark. The model showcases significant token efficiency, using 4.2x fewer output tokens than Opus 4.8 on SWE Bench Pro, and is available in Grok Build and Cursor.

Skillburst is a platform that enables non-technical team members to use AI workflows built by experts inside tools like Claude, Cursor, or ChatGPT without code. It addresses the problems of workflows getting lost in chat threads, copies going out of date, and non-technical teammates missing out. Engineers manage skills in GitHub, while Skillburst syncs, governs, and updates them for everyone else. The platform offers review, versioning, rollback, and upcoming analytics. Pricing starts free with Pro and Business tiers.

Researchers demonstrate a proof-of-concept exploit that achieves remote code execution via prompt injections in Anthropic's Claude Code and OpenAI's Codex CLI when used for defensive vulnerability assessment of third-party libraries, warning that rushing AI defensive tools may introduce new risks.

A YouTube video titled 'The AI Bubble We need to talk' discusses concerns about a potential bubble in the AI industry.

OpenAI finally upgraded the model used by ChatGPT voice mode. The new GPT‑Live model can delegate complex tasks to GPT-5.5 in the background while maintaining conversational flow, greatly improving utility. The author reports an initial bug where the model laughed inappropriately, which OpenAI has since mitigated.

Modal, which just raised a $355M Series C, is shifting focus from developer experience to agent experience. In this podcast, CTO Akshat Bubna explains why Kubernetes was never designed for bursty AI workloads and how Modal provides sandboxes, elastic inference, and GPU snapshotting for the agent era.