Building Scalable Multi-Agent Systems(MAS) Using GripTape
Multi-agent systems (MAS) represent a transformative approach in artificial intelligence, where multiple autonomous agents collaborate to solve complex problems and ...
Tag: scalable
Swarm: A Complete Guide to Lightweight Multi-Agent Orchestration for Scalable and Dynamic Workflows with Code Deployment
Swarm is an innovative open source framework designed to explore the orchestration and coordination of multi-agent systems. It is developed ...
This AI article explores process reward models and reinforcement learning: Advancing LLM reasoning with scalable data and scaling over test time
Scaling up large language models (LLMs) and their training data has now opened up emerging capabilities that allow these models ...
Stanford Researchers Introduce BIOMEDICA: A Scalable AI Framework to Advance Biomedical Models of Vision and Language with Large-Scale Multimodal Datasets
The development of VLM in the biomedical domain faces challenges due to the lack of large-scale, annotated, and publicly accessible ...
MiniMax-Text-01 and MiniMax-VL-01 Released: Scalable Models with Flash Attention, 456B Parameters, 4B Token Contexts, and Next-Generation Accuracy
Large Language Models (LLM) and Vision-Language Models (VLM) transform natural language understanding, multimodal integration, and complex reasoning tasks. However, a ...
Hypergrid Fields: Efficient Gradient-Based Training for Scalable Neural Network Optimization
Hypernetworks have attracted attention for their ability to efficiently adapt large models or train generative models of neural representations. Despite ...
Neural Networks for Scalable Temporal Logic Model Verification in Hardware Verification
Ensuring the accuracy of electronic designs is essential, as hardware failures are permanent in post-production and can compromise the reliability ...
This AI article from Microsoft and Novartis introduces Chimera: a machine learning framework for accurate and scalable retrosynthesis prediction
Chemical synthesis is essential in the development of new molecules for medical applications, materials science and fine chemistry. This process, ...
UCLA and Apple Researchers Present STIV: A Scalable AI Framework for Image and Text-Conditioned Video Generation
Video generation has improved with models like Sora, which uses the Transmission Transformer (DiT) architecture. While text to video (T2V) ...
This AI article introduces SuperGCN: a scalable and efficient framework for CPU-driven GCN training on large graphs
Graph Convolutional Networks (GCN) have become integral in the analysis of complex graph-structured data. These networks capture the relationships between ...
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