Super AGI Research Lab

Introduction In recent years, there has been a notable surge in the utilization of multi-agent systems powered by state-of-the-art Large Language Models (LLMs) to address a wide array of tasks, [...]

Introduction In our last blog, we discussed the challenges around Autonomous Software Development which is totally free from human intervention. Toward the end, we shared our stance on why startups [...]

Introduction The year is 2030. The latest company to get listed on NASDAQ has just 2 employees. There is a CEO, and a CTO and they are supported by a [...]

All of us have heard about the Mixture-of-Experts (MoE) architecture for LLMs. MoE divides models into separate sub-networks (or “experts”), each specializing in a subset of the input data, to [...]

Introduction In cognitive process automation, developing self-training modules is crucial. These modules can independently explore, learn, and adapt to complex and unfamiliar environments in the interface. They do this by [...]

A Comprehensive Exploration of Policy Optimization Algorithms and Frameworks Introduction Reinforcement Learning (RL) is an intriguing area of machine learning that deals with the actions of intelligent agents within an [...]

In part-1 of Towards AGI series, we discussed a core component of Agents - Memory. However, the early agent architectures, didn’t have Memory as a first class primitive. As we [...]

Agents are an emerging class of artificial intelligence (AI) systems that use large language models (LLMs) to interact with the world. In the 'Towards AGI' series, we aim to explore [...]

Introduction VEagle significantly improves the textual understanding & interpretation of images. The unique feature of VEagle is in its architectural change along with a combination of different components: a vision [...]

AutoNode is a significant progression in Robotic Process Automation (RPA), addressing the limitations of current systems through a synergistic integration of specialized AI models. This solution targets the inefficiencies and [...]

Introduction SuperAGI is focused on developing Large Agentic Models (LAMs) that will power autonomous AI agents. As part of this effort, we have been working on enhancing multi-hop sequential reasoning [...]

Retrieval-augmented generation (RAG) has made significant strides in enhancing the Language Model's (LLM) ability to provide contextual and informed responses by leveraging external knowledge bases. The process chiefly involves an [...]