A compositional evaluation framework for coding agents under realistic user requests is proposed, focusing on the evaluation of coding agents' ability to generate code that meets user requirements.
Key points
• The framework evaluates coding agents' performance in generating code that meets user requirements.
• The evaluation framework is compositional, allowing for the evaluation of individual components of the coding agent.
• The framework is designed to be scalable and adaptable to different coding tasks and user requirements.
The Stanford HAI is hiring an Education Program Manager to administer its scholar, fellow, and student programs. The role spans program operations, event logistics, participant onboarding, and coordination across faculty, mentors, and partner organizations.
Key points
• The Education Program Manager will be responsible for administering the scholar, fellow, and student programs.
• The role requires coordination across faculty, mentors, and partner organizations.
• The position is open to applicants with experience in program operations and event logistics.
The Data Science Clinic is a hands-on, project-based course for DSI students. Students work in teams on data science projects with real-world clients from industry, academia, and social impact organizations.
Key points
• The Data Science Clinic is a hands-on, project-based course.
• Students work in teams on data science projects with real-world clients.
• The course is designed to provide practical experience in data science.
DSI_UChicago - Organization hosting the information session
- Screenshot of the information session
Nordic Wind-Powered Empire
Datacentres are going off-grid in a Nordic wind-powered empire. Solar roofs, giant carparks, and zero CO2—Sweden/Germany leapfrogging the fossil era, one server at a time. Power costs fall, climate wins, ego loses.
Key points
• Datacentres are going off-grid in a Nordic wind-powered empire.
• The empire is powered by solar roofs and giant carparks.
• The goal is to reduce CO2 emissions and power costs.
DART-SD is a topology-aware self-distillation framework for multi-turn tool-calling agents. It models tool-use as a graph, finds the critical breakpoint, and supervises only the recovery steps. Outperforms SFT and RL across 5 benchmarks.
Key points
• DART-SD is a topology-aware self-distillation framework.
• The framework models tool-use as a graph.
• The framework outperforms SFT and RL across 5 benchmarks.
DAMP is a decay-aware mixed-precision recurrent-state quantization method. It reduces the precision of the recurrent state while maintaining the accuracy of the model.
Key points
• DAMP is a decay-aware mixed-precision recurrent-state quantization method.
• The method reduces the precision of the recurrent state.
• The method maintains the accuracy of the model.
Superhuman AI from Europe spots heart disease in under 2 seconds after learning from millions of ECGs. Faster triage for high-risk patients, slick fusion of Nordic AI grit with European healthcare rigor. Brainy heart, meet your rapid diagno…
Key points
• Superhuman AI from Europe spots heart disease in under 2 seconds.
• The AI learns from millions of ECGs.
• The AI provides faster triage for high-risk patients.
The past 24 hours in AI: • Supabase says ChatGPT sign-in is now a top login method • The Hugging Face incident reportedly had multiple agent waves • A primer maps LLMs, reasoning models and agents, plus Python setup with uv Read the full update: https://nocode.mba/newsletter?ref=xdaily…
Key points
• Supabase says ChatGPT sign-in is now a top login method.
• The Hugging Face incident reportedly had multiple agent waves.
• A primer maps LLMs, reasoning models and agents, plus Python setup with uv.
