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How NLP is turbocharging business intelligence

Flipboard

Natural language processing (NLP), business intelligence (BI) and analytics have evolved in parallel in recent years. NLP has shown potential to make BI data more accessible. But there is much work ahead to adapt NLP for use in this highly competitive area. Integrated NLP-enabled chatbots have …

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ChatBI: A Comprehensive and Efficient Technology for Solving the Natural Language to Business Intelligence NL2BI Task

Marktechpost

Both the Natural Language Processing (NLP) and database communities are exploring the potential of LLMs in tackling the Natural Language to SQL NL2SQL task, which involves converting natural language queries into executable SQL statements consistent with user intent. If you like our work, you will love our newsletter.

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Common Grounds: Unleashing innovation and growth through partnership

IBM Journey to AI blog

IBM and Intel have a long history of collaboration on data and AI products, including AI acceleration with IBM Watson NLP Library for Embed with OneAPI, the optimization of IBM Db2 on Intel Xeon platforms, and now, watsonx.data.

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AI Set to Raise Global GDP to $7 Trillion: Goldman Sachs

Analytics Vidhya

According to a recent report by Goldman Sachs, implementing Artificial Intelligence (AI) could increase the global GDP by 7%. The report states that as AI tools that use Natural Language Processing (NLP) continue to be integrated into businesses and society, they could help to drive up to $7 trillion in additional global GDP growth.

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How Macmillan Publishers authored success using IBM Cognos Analytics

IBM Journey to AI blog

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. A new strategy for data analytics and business intelligence Factors like this ultimately led the Macmillan team to realize that a new “modernized” approach around data analytics and business intelligence was needed.

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2024 Layoffs and LLMs: Pivoting for Success

The MLOps Blog

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Data scientists and NLP specialists can move towards analytical roles or into engineering to stay relevant. Are LLMs entirely overtaking AI and natural language processing (NLP)?

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IBM to help businesses scale AI workloads, for all data, anywhere

IBM Journey to AI blog

. “The media and entertainment industry has undergone a significant digital transformation, with viewers consuming content across different devices and platforms,” said Vitaly Tsivin, EVP Business Intelligence at AMC Networks. ” Notably, watsonx.data runs both on-premises and across multicloud environments.