New paradigms are emerging for training foundation models to interact with other agents and perform long-term reasoning. Program-Aided Language models (PAL) are a promising approach that uses LLMs to generate programs as intermediate reasoning steps while delegating the solution step to a runtime such as a Python interpreter."įoundation models pre-trained on diverse data at scale have demonstrated extraordinary capabilities in a wide range of vision and language tasks. The cohesion of language, multimodal perception, action, and world modeling is highlighted as a key step towards AGI, and the need for a paradigm shift towards cross-modal transfer and practical decision-making applications is emphasized. By continuing to research and develop these models, we may pave the way towards achieving a general artificial intelligence that can truly rival human intelligence. The potential for these models to operate across a wide range of tasks and domains, from language to vision, from few-shot prompting to decision-making and reasoning, is substantial. Overall, while the development of AGI systems presents significant challenges, the progress made so far with LLMs and their augmented and program-aided counterparts is promising. I have made an overall conclusion from the top five recent papers about artificial general intelligence and large language models for reasoning and Decision Making by OpenAI, Microsoft AI, Meta AI, Google AI Research Brain Team
0 Comments
Leave a Reply. |