Quick entry: Implement AI projects with the cloud [Video]
Artificial intelligence is no longer just a dream in many companies, but is already part of everyday life. Increasing computing power from the cloud makes that possible.
In this article you will read about,
- which factors are responsible for the success of AI,
- why more and more companies rely on AI and
- why this would not be possible without the cloud.
Big data, cheaper storage capacities, ever increasing computing power: these three factors are largely responsible for the triumphal march of artificial intelligence. The further development and commercialization of AI projects is clearly picking up speed and the size of the company is no longer an issue. Whether corporate group, SME, or start-up: More and more companies from almost all industries are relying on AI applications such as machine learning tools. And successfully: According to an IDG study, around 70 percent of companies saw a positive impact just three months after introducing a machine learning solution in the form of increasing productivity rates, cost reductions, or the level of innovation.
However, even with all these positive effects, it’s important that anyone considering the use of AI in their own company should be aware that in addition to the necessary amount of data and its appropriate quality as well as qualified personnel, they will also need the required computing power. And this can quickly become an expensive undertaking. After all, building high-performance AI applications and training algorithms requires a lot of computing power. Making this power available from your own server room or data center in a timely and targeted manner rarely makes sense - not least because the computing resources are often no longer needed afterwards.
The alternative: run artificial intelligence from the cloud. Max Guhl from the A.I.-Team at T-Systems explains which cloud technology is particularly suitable for which AI application and what needs to be considered when making the choice.
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