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Google AI Releases ADK Go: A New Open-Source Toolkit Designed to Empower Go Developers to Build Powerful AI Agents Understanding the Target Audience The primary audience for the Agent Development Kit (ADK) for Go includes: Go Developers: Professionals who are already using Go for backend services and are looking to integrate AI capabilities without switching…
«`html Why Spatial Supersensing is Emerging as the Core Capability for Multimodal AI Systems Understanding the Target Audience The target audience for this article includes AI researchers, business managers in tech, and decision-makers in industries utilizing AI technologies. Their pain points revolve around the limitations of current AI models in processing complex video data and…
«`html Comparing the Top 6 Inference Runtimes for LLM Serving in 2025 Large language models (LLMs) are increasingly constrained by the efficiency of serving tokens under real traffic conditions. Key implementation details include how the runtime batches requests, overlaps prefill and decode, and manages the KV cache. Different engines make varying trade-offs on these axes,…
«`html Understanding the Target Audience The target audience for this tutorial primarily consists of researchers and professionals in the fields of bioinformatics, systems biology, and computational biology. This group includes data scientists, biostatisticians, and biologists who are interested in multi-omics data interpretation. Pain Points Difficulty in integrating and interpreting large-scale omics data from various sources.…
Moonshot AI Releases Kimi K2 Thinking: An Impressive Thinking Model that can Execute up to 200–300 Sequential Tool Calls without Human Interference Understanding the Target Audience The target audience for Kimi K2 Thinking includes AI researchers, business managers, and decision-makers in tech companies focused on AI integration. Their pain points often involve: Difficulty in implementing…
«`html Build an Autonomous Wet-Lab Protocol Planner and Validator Using Salesforce CodeGen for Agentic Experiment Design and Safety Optimization In this tutorial, we build a Wet-Lab Protocol Planner & Validator that acts as an intelligent agent for experimental design and execution. We design the system using Python and integrate Salesforce’s CodeGen-350M-mono model for natural language…
Google AI Introduces DS STAR: A Multi-Agent Data Science System That Plans, Codes, and Verifies End-to-End Analytics Google has unveiled DS STAR (Data Science Agent via Iterative Planning and Verification), a multi-agent framework designed to transform open-ended data science questions into executable Python scripts, regardless of the complexity of the data formats involved. DS STAR…
CMU Researchers Introduce PPP and UserVille To Train Proactive And Personalized LLM Agents The research team from Carnegie Mellon University (CMU) and OpenHands has taken significant strides in developing proactive and personalized large language model (LLM) agents through a new framework known as PPP (Productivity, Proactivity, Personalization). This approach addresses the limitations of current LLMs,…
Generalist AI Introduces GEN-θ: A New Class of Embodied Foundation Models Built for Multimodal Training Directly on High-Fidelity Raw Physical Interaction Understanding the Target Audience The primary audience for GEN-θ encompasses professionals in robotics, artificial intelligence, and business management sectors, particularly those involved in research and development, product management, and strategic implementation of AI technologies.…
«`html Understanding the Target Audience The target audience for this tutorial includes AI researchers, machine learning engineers, and business professionals interested in the application of reinforcement learning in developing intelligent agents. Their pain points often revolve around the complexity of integrating various cognitive functions such as planning, memory, and reasoning within AI systems. They seek…