Leveraging a comprehensive reference architecture for AI that significantly reduces time-to-insight

The Challenge

Increasingly, organizations that value business may have intellectual property (AI), machine learning (ML), and in-depth (DL) representatives; Leveraging Businesses generated by AI are expected to reach $ 3.9 trillion by 2022 (Gartner, 2018). As organizations utilize this technology, CIOs face the challenge of implementing new complex mechanisms that are implemented, transferred, and protected.

In this important role, the success challenge is growing against CIOs: it is estimated that 85% of AI projects will not deliver to their organizations (Gartner, 2018). For success, all aspects of AI development must be done directly to support a unique complex AI organization. Challenged by rigorous Leveraging testing in experience, organizations are often unreliable, creating data images that lead to costly attention, leading to lost productivity, and increased understanding time. Adding to the problem, the speed at which AI is evolving requires flexible, fragile structures that can remain fast as technology advances.

For new high-performance organizations (HPCs) and high-performance systems (PDAs), AI development can be costly and time-consuming, to take about two to three years of internal research. Bring AI-based products to market. 78% of AI projects have been suspended even if they cannot be provided (Dimensional Research, 2019).

Recognizing the need for a complete AI solution including design, software and software services, hosting, and management, CIOs are looking for the experience of single solution companies.

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