To assist. Not replace.
Your organisation has extremely large data sets that require deep dive analysis, beyond the scope of a regular worker. Humans simply cannot perform this level of in-depth analysis. In order to reveal patterns, trends, and anomalies, you require an engine that learns from experience, for which no volume of data is too complex. You require deep learning artificial intelligence.
Humans become distracted and tired and sometimes make careless mistakes, especially with the mundane processes. When it comes to neural networks, this isn’t the case. Once trained, a deep learning model becomes able to perform thousands of routine, repetitive tasks within a relatively short time. Automation we design is to help people in their lives to make informed decisions, an application to assist and enhance jobs in industry, not to replace them.
In many organisation’s data is unstructured because much of it remains in different types of formats such as images, text, and so on, so for ML algorithms it can be difficult to mine unstructured data, hence the implementation of a DL engine. DL can mine big data.
The size of your data determines the value and potential insight. By analysing large volumes of data quickly and accurately, AI can assist in making better informed decisions.
Unstructured data ranging across currencies, formats and types? No problem for our deep learning engine. Pull together different formats and overlay variables.
Constant data incoming? Our deep learning engine learns from experience…so it simply gets better at analysing and extracting key insights from your data.
I keep saying that the sexy job in the next 10 years will be statisticians, and I’m not kidding.
Hal Varian, Chief Economist, Google
When decisions have to be made and later justified and scrutinised over, then it’s time to ensure you gain the competitive edge. Using programmable engines that can be refined and layered to make sense of complex data sets, searching for the hidden anomalies within an array of logs, reviewing previous decisions against criteria and analysing the possible outcomes; provide information that assists with making better informed decisions.
Humans have limited time and resources to process and analyse large datasets.
Data sets of any size can be reviewed with the Quantum Deep Learning module, system sets can be reviewed with Machine Learning algorithms in the Quantum ML module, likewise these can contribute to the AI module that leads the pack for providing results for the modern business.