Page 55 - SAMENA Trends - September 2023

ARTICLE SAMENA TRENDS

generation, dialogue systems and other the generative AI model can generate new AI, especially in sensitive areas such as
tasks. By learning large amounts of text images similar to real images and even healthcare or finance. Ensure that the AI
data, generative AI models can generate repair damaged photos. This brings new system complies with data protection
new text similar to human language and possibilities for artistic creation, image and ethical guidelines.
even produce conversations. This provides processing and other fields. • Skills & Talent: Gen AI is a complex
powerful support for applications such as technology requiring skilled personnel
automated text generation and intelligent In the field of music creation, Generative AI to develop, deploy, and manage.
customer service. The Pangu NLP has made model can be used for music generation, Companies need to have the necessary
a significant breakthrough as it was distilled music recommendation and other tasks. talent in place before adopting Gen AI.
with a large amount of general knowledge in By learning a large amount of music data, • Compute Resources: Gen AI models can
the pre-training phase, allowing the model the generative AI model can generate new be computationally expensive to train
to embed industry knowledge bases and music similar to human music, and even and deploy. Companies must ensure
databases easily to acquire industry know- personalized recommendations can be they have the necessary compute
how efficiently. Huawei Cloud worked with made according to users' preferences. This resources before adopting Gen AI.
partners to develop the Pangu NLP model has brought new opportunities for music
for the Arabic language that supports creation and music promotion. Generative AI eases talent management
hundreds of billions of parameters with challenges
semantic understanding accuracy reaching The essential Generative AI checklist Companies can develop a structured way
95%, becoming No.1 in Arabic language A centralized data strategy is essential for to experiment with Gen AI to predict the
understanding. adopting Gen AI because Gen AI models future:
need to be trained on large amounts of data. Use Gen AI to forecast demand for skills
In the financial field, companies can use Collecting and preparing for training can be and talent. Gen AI can be used to analyze
generative AI to create financial models difficult and time-consuming if the data is data from various sources, such as job
scattered across different departments postings, social media, and industry
A Generative AI model is and systems. A centralized data strategy trends, to forecast future demand for skills

a machine learning-based makes it easier to manage and access the and talent. You can train Gen AI models
using historical data to learn patterns,
data, which can help to accelerate the Gen
technology that learns AI adoption process. correlations and trends in your workforce.
from large amounts of Before adopting Gen AI or any AI This information can be used to predict
future demand for skills and strategic
technology, organizations should consider
data and generates new several key factors to ensure a successful workforce plans that ensure that the
content. Compared with and responsible adoption of AI. These company has the right people in the right
factors include:
places with the right skills at the right time.
traditional AI models, this • Business Objectives: Clearly Define
technology is more flex- the business goals and objectives that Use Gen AI to predict employee turnover.

ible and creative and can Gen AI is intended to address, say in Gen AI can be used to predict employee
turnover based on various factors, such
improving customer experiences.
produce more diverse • Data Strategy: Gen AI models are as employee demographics, performance
results. trained on data; to ensure data quality reviews, and job satisfaction surveys.
and availability, it is essential to have This information can be used to develop
a centralized data strategy in place to strategies to reduce turnover and retain top
and forecasts to aid in decision-making ensure that the data is high-quality, well- talent.
and risk management. Huawei Cloud organized, and accessible to the Gen AI
provides resilient infrastructure, application team. Use Gen AI to simulate different workforce
modernization technologies that make • Ethical considerations: Gen AI raises planning scenarios. Gen AI can be used to
financial applications agile, and innovative several ethical concerns, such as simulate different workforce planning
AI and virtual human technologies that bias, transparency, and accountability. scenarios, such as the impact of new
build intelligence into businesses. For Companies must have a plan to address technologies, changing market conditions,
conventional financial institutions, Huawei these ethical concerns before adopting and mergers and acquisitions. This
Cloud focuses on AICC, digital interaction, Gen AI. We must develop and adhere to information can be used to develop
and digital banking for them to go digital. a responsible AI framework addressing contingency plans and ensure the company
In the field of image generation, generative ethical concerns. is prepared for any eventuality.
AI models can be used for image synthesis, • Regulatory Compliance: It is critical
image inpainting and other tasks. By to understand the regional and global
learning a large amount of image data, regulations that pertain to the use of the

55 SEPTEMBER 2023