ESDS Knowledge Base


What are the problems in AI?

i.Lack of Technical Knowledge: In order to integrate, deploy as well as implement the AI applications in their enterprises, the organizations need to have knowledge of the current AI Advancements and technologies along with their shortcomings.

ii.Data Acquisition and Storage: The business AI systems depend on the sensor data for their inputs. Validation of AI requires a large volume of sensor data.

iii.Rare Workforce: The adoption and deployment of AI require specialists such as data scientists, data engineers, and other SMEs.

iv.Responsibility Issues: AI implementations require high responsibility. An individual needs to bear the burden for any malfunctions taking place in the hardware

v.Lack of Computing Speed: AI requires a high degree of computation speeds that are offered solely by the high-end processors. Large infrastructure requirements and associated pricing of the processors has resulted in hindrance in the generic adoption of AI

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