INGENIEUR
The ninth change is about platform support.
At present, AI is a job that can only be done by
highly skilled experts. There are not enough
mature, stable, and extensive automation tools.
Producing AI models is complex work that takes a
lot of time and effort.
Moving forward, we need a one-stop platform
that provides the necessary automation tools,
making it easier and faster to develop AI
applications. When this platform is in place, AI will
become a basic skill of all application developers,
even all ICT workers.
The last change is about talent availability.
Lack of AI talent, especially data scientists, has
long been seen as a major obstacle to AI progress.
Data scientists are scarce and will remain so in
the future.
Addressing this challenge requires an AI
mindset. That means providing intelligent,
automated, and easy-to-use AI platforms, tools,
services, and training and education programmes
to foster a huge number of data science engineers.
These people must be equipped with the ability to
deal with massive volumes of basic data science
tasks.
The AI workforce will be organised in a
pyramidlike structure, with a large number of data
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science engineers working with data scientists
and subject matter experts. This is how we can
help resolve the scarcity of AI talent.
These ten changes do not represent the full
picture of AI technology, talent, and industry
development. But if we can drive these changes,
they will lay a solid foundation for future AI growth.
Huawei’s AI strategy
These ten changes are what Huawei expects to
see in the AI industry. They are also the inspiration
behind Huawei’s AI strategy.
To drive these ten changes, our AI strategy
includes the following five priorities:
Invest in AI research: Develop basic capabilities
in data and power-efficiency, for example, using
less data, computing resources and power;
build secure and trusted platforms; and develop
automated and autonomous machine learning
for computer vision, natural language processing,
decision and inference, and so on.
Build a full-stack AI portfolio:
● ●
Deliver abundant and affordable computing
power.
● ●
Provide an efficient and easy-to-use AI
platform with full-pipeline services.