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Essesystems – Artificial Intelligence rethought

True Innovations

 In last month’s blog post, I addressed the question of what is a disruptive innovation. When is an innovation disruptive and so profound, that entire markets are changed in their structures? What conditions must be met for a „Breakthrough Innovation“? 

Thinking about these questions, you will come to the conclusion, that innovations can take place at very different levels of a company. As a matter of fact, to create a breakthrough innovation, there doesn’t even have to be a company. A true innovation can also arise at the famous, so-called,  kitchen table or in a garage, in memory of the Hewlett Packard Story. An innovation may arise as a flash of inspiration, or even as a by-product or a spin-off of a day-to-day activity, perhaps, because one action failed and to one’s own surprise something extraordinary happened. In this case, the inventor usually needs an experienced consultant to accompany the idea in its entrepreneurial and business implementation. A former entrepreneur, who has already brought ideas to market maturity and successfully established a business-organisation, is certainly best suited at this point.

Based on these thoughts, I tried to discover general structures in our previous blog post: could it be possible, to strategically plan and develop innovations in a targeted manner? Are there criteria that must be met in general?

Today I would like to draw attention to a start-up that has succeeded in such a breakthrough innovation. 

Essesystems

Essesystems – Artificial Intelligence rethought

Artificial intelligence (AI) is revolutionary in its ability to transform the way every layer of an organisation works. One of those layers is design, which can be transformed using AI driven Generative Design. 

Essesystems is a start-up that is operating in the field of Artificial Intelligence and Generative Computing, the global team has over 50 years’ experience of working in this field. 

Essesystems wants to help small medium enterprises (SME) and larger enterprises on this journey. Essesystems, a private sector company, based in the UK, has developed a generative and intuitive AI based software platform, that can dramatically decrease the time, effort, and costs to design new, or revis existing, products or business processes, throughout the whole supply chain. Thereby making current processes far more efficient, fast, and cost effective. 

This will involve seeking out ways to disrupt markets and sustain their business to drive profit while funding investment and to mitigate risk while exploiting opportunity – for example by developing new products or services. 

What is the Breakthrough?

Today’s generative design systems make limited use of AI. Instead relying heavily on Machine Learning (ML), a subset of AI, that only has a limited learning capability and is used to automate existing processes and routine workflows, but lacks inferencing and reasoning. Today’s AI/ML systems apply patterns of learning on datasets to optimise decision making, but this approach consumes huge computational power and requires constant change due to change in processes, challenges and scenarios. 

Essesystems has developed the unique Esse Complex Adaptive System (ECAS), a generative AI design platform that uses a combination of AI driven perception, knowledge, learning and reasoning, together with symbolic programming language rather than the usual NPL (Natural Language Processing) statistical approaches. 

Designers or engineers using ECAS input their design goals, knowledge, and requirements such as materials, manufacturing methods, cost, spatial and weight constraints. ECAS uses AI to generate potential design solutions for the user to explore and refine within ECAS. 

A Big Data and AI Executive Survey by New Vantage Partners in 2019 found 77% of responders stated, that “business adoption” of big data and AI initiatives continue to represent a challenge for their organisation.

Pricewaterhouse Coopers (PwC) forecast that the accelerating development and adoption of AI will account for a 14% boost to global GDP by 2030.

ECAS is different to traditional generative design systems. ECAS needs limited compute resources, either in a company’s own data centre, or public cloud, and can create a product with minimal or limited data. 

For example, if all we know is that we want to design a product that helps to prevent transmission of Covid19 from one human to another, we may think of this as a mask, only because we have from our experience been told or used one. But ECAS has no constraints in creating a product or face covering – it may produce a bubble to put over our head, a face shield, a mask, or something that has never been thought of before. We don’t know, but whatever it is, it will be designed purely by geometry rather than simply mathematical based, and will meet the challenge that is set. 

Intuitive AI will enable a design once formed to adapt and transform itself based on ever changing conditions and criteria. 

ECAS AI is far more like a human designer. It makes heavy use of knowledge, that has been both input at first setup and learned and refined with use. Like a human designer it can quickly generate novel design solutions, but at computer speed. Traditional ML generative design systems are like employing thousands of inexperienced designers to create millions of designs and evaluate them all to choose the best few. 

ECAS can be used for any scale of product engineering. Ranging from a single consumer product up to a large complex system. ECAS can also be used to design and optimise business processes. 

Here is a link to the Essesystems website: www.Essesystems.co.uk 

I will keep you posted about the latest developments of Essesystems. You are invited, initiative teams and companies alike, to contact me and and ask for further information on ECAS and Essesystems, or to team-up with us in developing further intuitive AI. Everyone is asked to contribute hereto in a constructive manner. 

We are looking forward to learning about your ideas and your projects.