Agents & Humans in Manufacturing was created with the intention of giving manufacturers — particularly engineers and operators — an intuitive platform that lets them build and procure easily Smart Agents without the need for coding tasks or any hand-engineering. We used the subtitle “A New Approach In Bringing Intelligence To Manufacturing” to motivate every engineer out there who still, in some ways, believe in intuitive creation and tinkering over theories and interventionism. We do not claim that we have created something new, but rather promoted a specifically overhauled understanding of how to bring intelligence to manufacturing the right way.

Why did we choose the name Squids, a cephalopoda community, are well known for their collaborative behavior through advanced signaling: emitting a skin dotted-pattern for communication. Furthermore, squids have the ability to learn through reinforcement; a quite similarity with the algorithms that power our services.

Although many of us today are surrounded by corporate entities promoting big data and cherry-picked forecasting tools up to the point where everything is becoming more complicated than simplified, a minority still has insights on what lies beyond this. It turned out that more data doesn’t insinuate better accuracy but instead, not surprisingly, more errors. The idea is to stop thinking about complex models within nature and to accept the fact that we live in a world that we cannot completely understand. Only when we start to accept this fact, can we eventually look into ourselves and how we are affected by this complexity around us. That is exactly why and where we promote payoff, utility and survival. We firmly believe, that this process of promoting unorthodox concepts — whether social, scientific or technological, especially nowadays during the age of decentralization, AI, and deep learning — comes from the stubborn minority that is willing to push beyond the mediocrity of models and forecasting in some domains, specifically manufacturing.

I don’t believe it’s an exaggeration to say that we live in times of great progress. Tremendous opportunities for innovation are open to us because of the wonder of the recent rise in AI and deep learning capabilities. Never before have so many people had access to super-computing and deep learning frameworks, which were only dreamed of by previous generations. Never before has the barrier to entry been so low for those who want to explore how deep learning and super computing frameworks could improve their lives. Knowledge about these technologies has never been shared so openly, and the access to learning has never been so easy before.

But at the same time, old ideologies, especially in the fields of statistics and mathematical modelling are becoming obsolete. This was due, of course, to the recent unfortunate economic and social events that occurred during the last decade. Those include the global financial crises, which can’t be dissociated from another unexpected event, to say the least, the Fukushima nuclear disaster. This was caused by a specific interventionist approach explained that it is due to the fact that we, humans, like the idea of certainty as much as we fear uncertainty.

So at this particular moment in time, when old ideologies are dying, and current technologies are in progress, offers a space for procuring industrial intelligence away from any complexity, with a new probabilistic approach that actually acknowledges rather than ignores natural errors and their hidden risks. We believe that it is time we accept nature and its complexity as something far beyond our understanding, challenging ourselves to improve our well-being, as a payoff function. We don’t pretend to have created something new but rather went back to the roots when manufacturing was run by humans with all their flaws and limitations, at times where interventionism was much less than today’s. It was also when hidden risks and unexpected events weren’t an issue. But, whatever the future holds, we hope you continue with us on this adventure and support us on our mission.