AI - why it's doomed to fail if connections to the application are not addressed

Posted on August 24, 2018

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Artificial intelligence was once the domain of science fiction movies, but in the modern world AI applications are rapidly becoming fact.

Technology is evolving to the point where self-driving cars and smart digital assistants are becoming a reality, with many applications being designed to assist business with their operations.

But a chain is only as strong as its weakest link. Do you have the right network connections between the provider, the customer and the AI prospect to ensure smooth operations?

The rise in artificial intelligence applications in Australia

There are many real world AI applications that are assisting Australian businesses today, like chatbots.

These automated customer assistants give consumers 24/7 access to enterprise for support on a range of issues, while also providing a 'human' face for them to interact with.

A primary example of this is 'Nadia', the chatbot being used by the Federal Government to assist clients during the rollout of the National Disability Insurance Scheme (NDIS).

Nadia is a computer generated face voiced by Academy Award winning actor Cate Blanchett that can answer any question about the NDIS, which is a new and, at times, confusing scheme that would require many human workers manning a support centre.

Virtual assistants are also being rolled out by businesses, using voice recognition and natural language processing (NLP) to take commands and execute jobs using the business’s IT systems.

Why connections are critical for AI to be successful

Tools that use AI and machine learning are changing the way we do business, but there is a catch—network latency.

Many of these AI systems require enormous amounts of data to operate which can slow down your networks. In worst case scenarios, these systems can be slowed to the point of being inoperable while big data analysis can become unreliable.

To prepare for the future of AI, which could well include self-driving cars linked to your business network and other robotics and drones, systems need to be upgraded today.

Solutions to assist your AI applications

No business wants to wait until their network is overloaded to realise they need to upgrade. It can result in costly downtime, reduced revenue and expensive upgrades applied with haste.

With AI becoming a reality, now is the time to prepare your network layer to optimise for low latency for the data use these applications will require in the future.

Vocus recommends reviewing the annual IT budget and analysing current and emerging technologies to see where there is room to upgrade your systems data, network connectivity and cloud systems to accommodate future AI systems.

New dedicated network approaches that combine DCs with cloud systems can be cost effective methods to improve your network and data solutions with scalability for the future demands AI systems will require.

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