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Conversational AI use cases for enterprises

IBM Journey to AI blog

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. This sophisticated foundation propels conversational AI from a futuristic concept to a practical solution. billion by 2030.

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Is Artificial Intelligence relevant to insurance?

IBM Journey to AI blog

After the success of Deep Blue, IBM again made the headlines with IBM Watson, an AI system capable of answering questions posed in natural language, when it won the quiz show Jeopardy against human champions. Continued advancement in AI development has resulted today in a definition of AI which has several categories and characteristics.

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AI News Weekly - Issue #342: $1 billion gamble to ensure AI doesn’t destroy humanity - Jul 20th 2023

AI Weekly

In the News Top 10 AI Tools Cooler Than ChatGPT For our list of AI tools cooler than ChatGPT, we conducted extensive research and considered various factors such as performance, versatility, innovation, user-friendliness, integration, and industry impact. Powered by pluto.fi It’s easier said than done.

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Generative AI use cases for the enterprise

IBM Journey to AI blog

Tools such as Midjourney and ChatGPT are gaining attention for their capabilities in generating realistic images, video and sophisticated, human-like text, extending the limits of AI’s creative potential. Existing content can be reimagined and edited using AI tools.

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Code Smarter, Not Harder: Streamline Software Development with Generative AI

Topbots

However, the emergence of generative AI has reshaped the software development landscape, driving unprecedented productivity gains. A McKinsey study reveals that developers using generative AI tools can write new code nearly twice as fast , document code in 50% less time, and refactor code in 30% less time.

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The risks and limitations of AI in insurance

IBM Journey to AI blog

Risk and limitations of AI The risk associated with the adoption of AI in insurance can be separated broadly into two categories—technological and usage. Finally, establish policy enforcement measure to set the norms, roles and accountabilities, approval processes, and maintenance guidelines across AI development lifecycles.

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How AI saves money and improves banking complaint handling

Snorkel AI

AI can also help banks better understand the root causes of complaints and develop more effective strategies to address and prevent them in the future. Banks can use these models to fine-tune their interactive voice responses and train conversational AI to automatically respond to queries over chat, email, and text.