Why we started an ML company part 2

It is now close to a year since our first blog post Why we started a machine learning consultancy which is still getting a lot of interest. So we thought it was time to do a part two, telling the story of where we are now and how much has changed.

So let’s take a look at what is happening in the industry and what has happened to neurospace over the past year.

The industry has seen change in terms of AI and ML and it seems like almost every industry is doubling down on ML to use for improving their business. Everything from retail to manufacturers are trying to reap the benefits by utilizing everything from recommender systems to outlier detection. The first major change for us after a year is that we are solely targeting manufacturing because we believe this is where we can make an impact. We are passionate about helping manufactures become better at what they do by utilizing their data. In our segment we are seeing different usages for ML e.g. predictive maintenance, better automation of machinery, better forecasting with a high number of sources, and computer vision for quality control.

In general we are moving from the industrial age to the digital age, and now into the age of data. Our purpose is helping manufacturers predict failure in machinery, help forecast better in production, and create better quality inspection methods.

What we have seen over the last year are two key challenges in moving towards utilizing data: Imagination and Competences. Imagination to see new possibilities where data and machine learning can give the company a competitive edge, and the competences to bring the new possibilities into production.

Imagination

We believe that ML is the technology that will be the biggest transformation in our lifetime. To imaging what machine learning can do in your production setup you need to buy the premise that ML has the potential to change the world. This is why we help our customers imaging what can be done when they collect data, use it to gain insight, and use this insight to become better at what they do. It is about imagining a new way of working, new standard operating procedures, and sometimes a completely new process.

To understand what machine learning can do in your company, you must have an idea of how machine learning algorithms work. The possibilities for using machine learning are endless, however it is the data that dictates these possibilities. This is why data correlations are key, and this leads us to the next challenge.

Competences

Data and ML competences are some of the hardest to come by right now which has resulted in data scientists to be one of the most promising jobs in 2019. Few manufactures have these competences in-house and therefore they need help either gaining the capabilities in-house or develop solutions which utilizes their data. This is why we try to help educate about what we do and what is needed to get start. Further, when engaged with a customer we help spear head the first pilot projects to show the value of data and machine learning while, in the process, educating the people around us so they can help make it a success and ensure that they keep producing value in the organization.

Our journey the past year

We have in the past year tried to understand the market, and position ourselves. In this journey we have spoken with a variety of potential customers from different segments, and are now offering solutions to manufacturing. Our focus on improving OEE with predictive maintenance, forecasting, and computer vision comes from what potential customers have expressed they need when talking with them. Additionally, it is the market we have the most knowledge about due to our previous work. By following the Lean Start-up-approach we have altered between creating hypotheses, and testing them on the market.

No the machine will not take our jobs

It requires good change management to implement solutions which will change the work processes and hereby how the work is done by the people in the organization. It is important to say that the machines will not take our jobs and there will still be work to do tomorrow for humans but it is likely to change what that work is. Humans are the most important part we have in the age of machine learning. Humans are brilliant at things like empathy, fuzzy logic, intuition, and decision making. Machines will not be able to do this but are brilliant at finding patterns across larger and complex data samples the human brain cannot, and repetitive tasks. People are a vital part of every business and will always be that. Jobs change all the time as we become better to remove the boring parts which in turn makes it possible to start doing more interesting valuable things for our companies. AI will change the same or more of our society in the next 20-25 years as the internet has done the last 25 years. It will disrupt and transform many industries including manufacturing and industrial segments. In the Western countries we can use this to become better at producing and manufacturing. One of the best sentences we have heard over the last year is “Now we are better than the Chinese ”.

It is about driving insight

Data is key - and the only solution to not having the data you need is to start gathering it. We help customers in collecting data to support insights which can create great business outcomes. Our processes is different from many others as we believe in being ambitious, starting small, and creating value fast.

We also see it as a continuous cycle where the company need to keep gathering data as new information will arise from new data which in turn leads to new insights and better decisions. To us insight is key as this is often the trigger to create valuable solutions which can be everything from quality inspection to automations.

Why we started an ML company

Using the right data to automate and improve processes, for decision-making, and for detecting anomalies such as breakdown on machines can create new or improve existing business areas. A business area that can give your company a competitive edge, and can be what makes you beat competition within the next 3-5 years. Without the imagination and competences this will not happen and this is why we are still here, we want to improve the industrial world as we know it today so we together can become better tomorrow.

// Rasmus Steniche, CEO @ neurospace