99.2SEMar 26
Composer 2 Technical ReportCursor Research, Aaron Chan, Ahmed Shalaby et al. · berkeley, microsoft-research
Composer 2 is a specialized model designed for agentic software engineering. The model demonstrates strong long-term planning and coding intelligence while maintaining the ability to efficiently solve problems for interactive use. The model is trained in two phases: first, continued pretraining to improve the model's knowledge and latent coding ability, followed by large-scale reinforcement learning to improve end-to-end coding performance through stronger reasoning, accurate multi-step execution, and coherence on long-horizon realistic coding problems. We develop infrastructure to support training in the same Cursor harness that is used by the deployed model, with equivalent tools and structure, and use environments that match real problems closely. To measure the ability of the model on increasingly difficult tasks, we introduce a benchmark derived from real software engineering problems in large codebases including our own. Composer 2 is a frontier-level coding model and demonstrates a process for training strong domain-specialized models. On our CursorBench evaluations the model achieves a major improvement in accuracy compared to previous Composer models (61.3). On public benchmarks the model scores 61.7 on Terminal-Bench and 73.7 on SWE-bench Multilingual in our harness, comparable to state-of-the-art systems.
CYMay 4, 2022
A Perspective on K-12 AI EducationNathan Wang, Paul Tonko, Nikil Ragav et al.
Artificial intelligence (AI), which enables machines to learn to perform a task by training on diverse datasets, is one of the most revolutionary developments in scientific history. Although AI and especially deep learning is relatively new, it has already had transformative impact on medicine, biology, transportation, entertainment, and beyond. As AI changes our daily lives at an increasingly fast pace, we are challenged with preparing our society for an AI-driven future. To this end, a critical step is to ensure an AI-ready workforce through education. Advocates of beginning instruction of AI basics at the K-12 level typically note benefits to the workforce, economy, and national security. In this complementary perspective, we discuss why learning AI is beneficial for motivating students and promoting creative thinking, and how to develop a module-based approach that optimizes learning outcomes. We hope to excite and engage more members of the education community to join the effort to advance K-12 AI education in the USA and worldwide.
CVMay 13, 2020
Sustainable Recreational Fishing Using a Novel Electrical Muscle Stimulation (EMS) Lure and Ensemble Network Algorithm to Maximize Catch and Release SurvivabilityPetteri Haverinen, Krithik Ramesh, Nathan Wang
With 200-700 million anglers in the world, sportfishing is nearly five times more common than commercial trawling. Worldwide, hundreds of thousands of jobs are linked to the sportfishing industry, which generates billions of dollars for water-side communities and fisheries conservatories alike. However, the sheer popularity of recreational fishing poses threats to aquatic biodiversity that are hard to regulate. For example, as much as 25% of overfished populations can be traced to anglers. This alarming statistic is explained by the average catch and release mortality rate of 43%, which primarily results from hook-related injuries and careless out-of-water handling. The provisional-patented design proposed in this paper addresses both these problems separately First, a novel, electrical muscle stimulation based fishing lure is proposed as a harmless and low cost alternative to sharp hooks. Early prototypes show a constant electrical current of 90 mA applied through a 200g European perch's jaw can support a reeling tension of 2N - safely within the necessary ranges. Second, a fish-eye camera bob is designed to wirelessly relay underwater footage to a smartphone app, where an ensemble convolutional neural network automatically classifies the fish's species, estimates its length, and cross references with local and state fishing regulations (ie. minimum size, maximum bag limit, and catch season). This capability reduces overfishing by helping anglers avoid accidentally violating guidelines and eliminates the need to reel the fish in and expose it to negligent handling. IN conjunction, this cheap, lightweight, yet high-tech invention is a paradigm shift in preserving a world favorite pastime; while at the same time making recreational fishing more sustainable.