IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately.

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Chatbots Life

MAY 3, 2023

What is Conversational AI? We all remember conversing with a Chatbot at some point in our lives. And we also remember having to then connect with a Human because the chatbot couldn’t understand our query. That is the perfect example of high-level conversational AI! How does Conversational AI work?

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Pragnakalp

FEBRUARY 1, 2024

Exploration of Dialogflow CX The weblog will provide an in-depth understanding of Dialogflow CX, highlighting its pivotal role in crafting intelligent conversational agents. Readers will gain insights into its features, functionalities, and its unique position in the realm of conversational AI platforms.

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Chatbots Life

MARCH 17, 2023

As pioneers in adopting ChatGPT technology in Malaysia, XIMNET dives in to take a look how far back does Conversational AI go? Photo by Milad Fakurian on Unsplash Conversational AI has been around for some time, and one of the noteworthy early breakthroughs was when ELIZA , the first chatbot, was constructed in 1966.

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Chatbots Life

MAY 16, 2023

Top 5 Generative AI Integration Companies Generative AI integration into existing chatbot solutions serves to enhance the conversational abilities and overall performance of chatbots. Generative AI integration service : proposes to train Generative AI on clients data and add new features to products.

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IBM Journey to AI blog

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” They are now capable of natural language processing ( NLP ), grasping context and exhibiting elements of creativity.

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NVIDIA

SEPTEMBER 7, 2023

According to a recent NVIDIA survey , the top AI use cases for financial service institutions are natural language processing (NLP) and large language models (LLMs). AI voice assistants can be trained on finance-specific vocabulary and rephrasing techniques to confirm understanding of a user’s request before offering answers.

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