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Thursday, June 13, 2024

Generative AI: Closing adoption gap to boost benefits says data scientist - ITREALMS

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Closing the adoption gap on Generative Artificial Intelligence (Gen AI) would boost its benefits, says a data scientist and machine learning lecturer with the University of Lagos, Dr. Roselyn Isimeto, reports ITREALMS.
Generative AI: Closing adoption gap to boost benefits says data scientist - ITREALMS
Gen AI is artificial intelligence capable of generating text, images, videos, or other data using generative models, often in response to prompts.

Speaking on Building Innovative Large Language Models for a Digital Economy, at the Miva Open University Abuja IndabaXNigeria 2024 held recently, Isimeto said Gen AI is the technology with capacity to help Africans build the continent they want.

The IndabaX is an annual gathering of the African machine learning community that was initiated in 2017 in South Africa, aimed at advancing knowledge and skills in machine learning and artificial intelligence within across Africa.

She also described the benefits of Gen AI as closely linked to the 17 Sustainable Development Goals (SDGs). Noting that SDGs were adopted by the General Assembly of the United Nations (UN) since 2015 with the aim of fostering "peace and prosperity for people and the planet" among others. 

“Gen AI has the potential to help us achieve the SDGs,” she declared.

Isimeto urged for adoption of Gen AI so as to close the existing gap, as its benefits will show up, since it could be deployed in almost all facets of life and businesses. She attributed the current low adoption despite tremendous benefits that Gen AI brings to the fact that most companies in Africa do not know how to adopt Gen AI to solve their business problems. Additionally, she said, lack of adequate Gen AI skill-sets and  local datasets remain a challenge, stressing that building these data-driven applications require data, because it is the fuel that drives the innovations. “No data, no innovation,” she declared.

Business sectors where this technology could be used include “marketing and advertising” sector: as in tasks involving content creation, generation of personalized marketing copy; “customer service”: as in conversational agents, sentiment analysis, text summarization tasks; “finance and banking”: as in document generation, fraud detection; “healthcare and medicine”: as in medical diagnostics and treatment planning, drug discovery and development,  enhanced patient care and support; “media and entertainment” as in : music generation, video generation, image enhancement; “Education”: as in personalized learning experiences, empowering educators. Other sectors include agriculture, legal, real estate, manufacturing, retail, energy, Human resources, fashion, and so on.

Isimeto equally cited an instance with a case study of building a Large Language Model (LLM) application, pointing out that it involves several steps, “from understanding your requirements to deploying the application.”  

By following the steps, you can build a robust LLM application tailored to your specific needs. Isimeto further did a practical demo to help participants learn how to start building Gen AI applications.

To close the adoption gap, Isimeto advised organizations to consider innovations in product, process, business model, service, organizational, marketing, disruptive, and incremental respectively.

1 comment:

Anonymous said...

Great work!

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