planning
planning on Beyond Market Intelligence: a running collection of 4 stories we have gathered and hand-picked because they are worth your time. Every post here touches on planning in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around planning, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
What Can I Actually Do with a Small Language Model?
Small Language Models (SLMs) are gaining traction, and understanding their practical capabilities is key. While they may not rival larger counterparts, thoughtful planning unlocks significant value. You can effectively leverage SLMs for a range of operational scenarios, from streamlined content generation to localized data analysis. By acknowledging and accommodating their limitations, you can empower workflows and improve productivity. As DeepSeek's V4 Flash demonstrates, even top-ranked models can face challenges in real-world agent tasks, highlighting the importance of realistic expectations.
Planning/RL for a stochastic single-player merge puzzle: afterstates, previewed chance events, and long-horizon throughput [D]
Planning and reinforcement learning for this stochastic merge puzzle—characterized by afterstates, previewed chance events, and long-horizon throughput—present a unique challenge. We're exploring AI strategies for a single-player game resembling 2048, but with a larger action space, stack constraints, and a crucial element: a previewed random tile drop. Leveraging an exact simulator, we're optimizing for both maximizing 9s in a single game and achieving a high throughput over a 30-minute period.
2026 NeurIPS: Where are you going? [D]
Navigating the 2026 NeurIPS landscape presents a key decision for US-based attendees: Sydney or Atlanta? This year's conference offers compelling options, prompting many to consider logistical and professional priorities. We’ve observed considerable discussion around this choice, mirroring broader questions about the future of AI research and collaboration. For those seeking deeper understanding of underlying methodologies, our recent article, "I never understood positional encoding until I read this article," offers valuable insights. Ultimately, planning ahead ensures a productive and enriching NeurIPS experience.
Embabel Agent Framework Reaches 1.0
Embabel Agent Framework has officially reached version 1.0, establishing a robust foundation for AI agent development within the Java ecosystem. This framework empowers Java and Kotlin developers to define agents as typed domain objects, leveraging the established Spring AI infrastructure. Embabel’s design combines flexible planning with predefined state machines, supporting multiple model providers for adaptable agent workflows.