Framework
AutoCode: A New AI Framework that Lets LLMs Create and Verify Competitive Programming Problems, Mirroring the Workflow of Human Problem Setters
[ad_1] Are your LLM code benchmarks actually rejecting wrong-complexity solutions and interactive-protocol violations, or are they passing under-specified unit tests? A team of researchers from UCSD, NYU, University of Washington, Princeton University, Canyon Crest Academy, OpenAI, UC Berkeley, MIT, University of Waterloo, and Sentient Labs introduce AutoCode, a new AI framework that lets LLMs create…
Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends
[ad_1] In this tutorial, we explore Ivy’s remarkable ability to unify machine learning development across frameworks. We begin by writing a fully framework-agnostic neural network that runs seamlessly on NumPy, PyTorch, TensorFlow, and JAX. We then dive into code transpilation, unified APIs, and advanced features like Ivy Containers and graph tracing, all designed to make…
Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-Efficiency
[ad_1] Sakana AI has released ShinkaEvolve, an open-sourced framework that uses large language models (LLMs) as mutation operators in an evolutionary loop to evolve programs for scientific and engineering problems—while drastically cutting the number of evaluations needed to reach strong solutions. On the canonical circle-packing benchmark (n=26 in a unit square), ShinkaEvolve reports a new…
Automating FOWLP design: A comprehensive framework for next-generation integration
[ad_1] Fan-out wafer-level packaging (FOWLP) is becoming a critical technology in advanced semiconductor packaging, marking a significant shift in system integration strategies. Industry analyses show 3D IC and advanced packaging make up more than 45% of the IC packaging market value, underscoring the move to more sophisticated solutions. The challenges are significant—from thermal management and…
Building a Hybrid Rule-Based and Machine Learning Framework to Detect and Defend Against Jailbreak Prompts in LLM Systems
[ad_1] In this tutorial, we introduce a Jailbreak Defense that we built step-by-step to detect and safely handle policy-evasion prompts. We generate realistic attack and benign examples, craft rule-based signals, and combine those with TF-IDF features into a compact, interpretable classifier so we can catch evasive prompts without blocking legitimate requests. We demonstrate evaluation metrics,…
Google AI Introduces Personal Health Agent (PHA): A Multi-Agent Framework that Enables Personalized Interactions to Address Individual Health Needs
[ad_1] What is a Personal Health Agent? Large language models (LLMs) have demonstrated strong performance across various domains like clinical reasoning, decision support, and consumer health applications. However, most existing platforms are designed as single-purpose tools, such as symptom checkers, digital coaches, or health information assistants. These approaches often fail to address the complexity of…
Meet Elysia: A New Open-Source Python Framework Redefining Agentic RAG Systems with Decision Trees and Smarter Data Handling
[ad_1] If you’ve ever tried to build a agentic RAG system that actually works well, you know the pain. You feed it some documents, cross your fingers, and hope it doesn’t hallucinate when someone asks it a simple question. Most of the time, you get back irrelevant chunks of text that barely answer what was…
Alibaba Qwen Team Releases Mobile-Agent-v3 and GUI-Owl: Next-Generation Multi-Agent Framework for GUI Automation
[ad_1] Image source: Marktechpost.com Introduction: The Rise of GUI Agents Modern computing is dominated by graphical user interfaces across devices—mobile, desktop, and web. Automating tasks in these environments has traditionally been limited to scripted macros or brittle, hand-engineered rules. Recent advances in vision-language models offer the tantalizing possibility of agents that can understand screens, reason…
Build vs Buy for Enterprise AI (2025): A U.S. Market Decision Framework for VPs of AI Product
[ad_1] Enterprise AI in the U.S. has left the experimentation phase. CFOs expect clear ROI, boards expect evidence of risk oversight, and regulators expect controls consistent with existing risk management obligations. Against this backdrop, every VP of AI faces the enduring question: Should we build this capability in-house, buy it from a vendor, or blend…
Zhipu AI Unveils ComputerRL: An AI Framework Scaling End-to-End Reinforcement Learning for Computer Use Agents
[ad_1] In the rapidly evolving landscape of AI-driven automation, Zhipu AI has introduced ComputerRL, a groundbreaking framework designed to empower agents with the ability to navigate and manipulate complex digital workspaces. This innovation addresses a core challenge in AI agent development: the disconnect between computer agents and human-designed graphical user interfaces (GUIs). By integrating programmatic…