AI Research Conversational AI LLM Natural Language Processing 
Topbots
OCTOBER 10, 2023
Source: rawpixel.com Conversational AI is an application of LLMs that has triggered a lot of buzz and attention due to its scalability across many industries and use cases. While conversational systems have existed for decades, LLMs have brought the quality push that was needed for their large-scale adoption.
Topbots
APRIL 29, 2024
Here are a few that might worth your attention: Reasoning with Language Model Prompting: A Survey. This paper, first published in December 2022, may not cover the most recent developments in LLM reasoning but still offers a comprehensive survey of available approaches. Large Language Models Cannot Self-Correct Reasoning Yet.
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Marktechpost
MAY 29, 2024
With significant advancements through its Gemini, PaLM, and Bard models, Google has been at the forefront of AI development. Each model has distinct capabilities and applications, reflecting Google’s research in the LLM world to push the boundaries of AI technology.
Marktechpost
DECEMBER 12, 2023
Thanks to the success in increasing the data, model size, and computational capacity for auto-regressive language modeling, conversational AI agents have witnessed a remarkable leap in capability in the last few years. In comparison to the more powerful LLMs, this severely restricts their potential.
Topbots
AUGUST 22, 2023
Large Language Models (LLMs) present a unique challenge when it comes to performance evaluation. Unlike traditional machine learning where outcomes are often binary, LLM outputs dwell in a spectrum of correctness. auto-evaluation) and using human-LLM hybrid approaches. This requires building a custom evaluation set.
Marktechpost
JULY 3, 2023
With the release of the latest chatbot developed by OpenAI called ChatGPT, the field of AI has taken over the world as ChatGPT, due to its GPT’s transformer architecture, is always in the headlines. Almost every industry is utilizing the potential of AI and revolutionizing itself.
Topbots
OCTOBER 4, 2023
The basic difference is that predictive AI outputs predictions and forecasts, while generative AI outputs new content. Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., Sign up for more AI research updates.
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