PolyNet – The first tool to automatically train and optimise a neural network; giving you better quality results in A.I. and machine learning.

During the course of our work on Facial Recognition, we have perfected a neural network training tool.

• It automatically selects the best weights.
• It computes the best architecture.
• It is a hands-off neural network optimiser.

We believe PolyNet is one-of-a-kind.

There are many companies and organisations currently using Machine Learning and Artificial Intelligence who have been getting good results, but they have also been getting a little frustrated –  as they feel results could possibly be better.

That’s exactly where we can help.

At the heart of your ML and AI, underlying everything – is the neural network.
Finding ways to choose the best configuration and therefore optimise the performance of your neural network, has been, at best, educated guesswork.
Until now. 

We are introducing a smart tool that gets right to the heart of the problem, automatically exploring, then analysing and computing with its onboard engine – to improve the structure and performance of the neural network.

Rather than making an educated guess, which is a manual task, it actually computes the solution. Taking away the elements of hunches and opinions inherent in existing methods.

That is the core difference we utilise to improve accuracy and, in the end, results from your ML and AI.

PolyChord is the maths engine driving the process. It was developed by Astrophysics Professors in Cambridge University in 2017, and has unique abilities to solve high-dimensional data problems. Exactly the problems relating to neural network configuration and behaviour. This same team has specifically adapted the PolyChord tool to explore and optimise the neural network – this new, adapted tool is called PolyNet.

So, how does PolyNet compare to other neural net training tools? Well, there are only one or two other tools in this space already. TensorFlow users will know that TensorFlow can help you to choose correct weights, for instance. However, TensorFlow is working on a different core principle to PolyNet, which means it can get stuck in one avenue of exploration.

PolyNet however, goes through the whole network and explores the entire space, making smart choices about both weights and structure so it can automate adjustments to optimise performace and functionality – the result being improved outcomes for the end user. PolyNet is a first; a ready-to-use solution that trains your neural network,  which you (meaning your technical team) can deploy in house, so your data never has to leave the building.

That’s the unique and key difference with PolyNet. As far as we know, no other current tool can help you make informed, machine-calculated choices about weights and architecture in this way.

We are currently offering demo’s of the system, as this is the best way for potential users to ask questions about PolyNet, explore the possibilities, and see how improvements can be gained. There has been a lot of interest. This demo is free to qualifying organisations and is given personally to key members of your team by senior personnel from PolyChord Ltd.  A successful demo may lead to trial use, trials are on a paid-for basis over two months.

We have flexible options with which to move forward after a successful trial (including fee-based, or as an alternative for some customers, metrics-driven performance-based with no front end fee). PolyNet is not aimed at small, low-budget users. It is a unique new cutting edge application which can confer a significant competitive advantage to organisations who have already progressed with ML and AI. Contact us to express an interest in a free demo. We are happy to demonstrate to serious enquirers without cost or obligation.

Use the contact form or email button below to find out more, leave a few details about your enterprise and request a technical pack. We will come right back to you.

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