AI

 

 

As we seek to harness the power of AI, one of the first questions that AI programs may need to answer concerns analytical adequacy: Is there data, and is it of sufficient quality to address the specific business need? So, I am working on Data format and a quality of that , which makes it incompatible with AI approaches. To make AI-ready data, I am focusing on :

1. Build a use case–specific data catalog

2. Evaluate the quality and completeness of data sets

3. Aggregate prioritized data sources

4. Gauge the data’s fit

5. Govern and execute

 

By adopting a mission-based data strategy, governments and private sectors can avoid many common roadblocks and immediately focus their technical talent, knowledge, and limited budgets on the subset of data needed for prioritized use cases. This strategy avoids creating data and tool capabilities without a plan. The iterative process—translating mission priorities into requirements and data engineering tasks, generating AI-ready data, and translating data into insights—keeps investments focused and maximizes their impact. https://medium.com/@proflilisaghafi/the-impact-of-right-data-on-the-power-of-ai-2d2f4e6e7f4f

 

 

 

 

 

 

( My AI courses for IT and  Management /Communication  )
Communication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence .ecent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way.