Noticeable Big Data Trends in Aerospace and Defence

Noticeable Big Data Trends in Aerospace and Defence

The US Department of Defense has opened its doors to major tech companies in the US. It is likely that major US tech companies will be under more pressure to assist the government in developing AI because the Chinese government is seeking to become a self-sustaining leader in the field.

Fremont, CA: The opportunities available to defence vendors that can leverage the power of big data are clear and wide-ranging, but it is not a one-size-fits-all solution, and businesses need to tailor their approach to their own specific requirements and use cases.

Trends in Technology

The key technological trends influencing the big data are listed below.

Artificial Intelligence Service (AI)

The US Department of Defense has opened its doors to major tech companies in the US. It is likely that major US tech companies will be under more pressure to assist the government in developing AI because the Chinese government is seeking to become a self-sustaining leader in the field.

Computing the Cloud

The importance of cloud computing to defence is growing due to the amount of data produced by military equipment. In addition, the cloud reduces the need for support and infrastructure for IT systems and provides significant scalability.

Edge of Computing

Specific use cases of edge computing include the maintenance of data processing and analytics close to collection points. The growth of edge computing is therefore closely linked to the Internet of Things (IoT). The deployment of 5G cellular technologies will provide a major stimulus for both IoT and edge computing.

Quantum Computing

The race to achieve quantum supremacy is well underway, with Google, IBM, and Microsoft leading the pack. IBM unveiled the first quantum computer for commercial use, Q System One, in March 2019.AI, and in particular machine learning (ML), is of benefit, as quantum computers should be able to complete extremely complex calculations. Quantum computing could open up new spheres of performance and scale for effort-intensive AI tasks such as classification, regression, and clustering.

Quantum Speedup

In order for AI to truly deliver on tough challenges such as the real-time optimization of a complex supply chain, new hardware will be needed. Quantum computers can solve a number of problems in parallel. This can greatly accelerate key facets of ML, such as reinforcement learning, as a computer can test a much larger number of "possibilities" to determine the course of action that leads to reward.

Check Out: Top Technology Companies in Aerospace Sector

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