The adoption of AI-enabled business solutions continues to grow popularly across the tech industry. In post on the GPT-3 built by Open AI, we highlighted as an example of how AI might change the customer support sector. This is just one of the examples of the sectors the innovation of artificial intelligence could potentially disrupt.

However, admittedly, the excitement around the innovation from AI runs into gridlocks as businesses seeking to execute their ideas run into data problems. In a number of cases, there seems to be a continuous gap between our brilliant ideas and execution. This article seeks to address what we consider as the missing link to executing AI into efficient business models that will profit everyone involved from the businesses to the end-consumer.

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What do we understand as bias? Can bias be good or destructive in everyday human interaction? Is bias in humans different from bias in AI? There are a number of questions associated with bias in the AI industry. As businesses deploy AI solutions, care must be taken to avoid setting up models that come off as discriminatory to both consumers and regulators.

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The release of the GPT-3 (Generative Pre-trained Transformer 3) language model by Open AI has been greeted with enthusiasm and excitement. Several commentators have hailed the development of the language solution as a crossroads in natural language processing (NLP). Many are confident that the language model will help businesses make better use of their AI models. The model, which has only been released to a few beta users has shown how efficient it could be in generating quick responses to emails, speaking to your favorite thinker, or generating code.

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Artificial Intelligence is shaping the transformation of our world in many ways. From travel to tourism, to fashion, the influence of AI is leading to advancements that were barely imagined a few decades ago. But what feeds AI? While deep insights into the industry, real-time information and actionable recommendations are easy wins by Artificial Intelligence in almost every industry today, data is the lifeblood of artificial intelligence.

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