For the Gartner Group, AI “Edge” will quickly become the standard thanks to a decisive advantage: thanks to the machine learning functions integrated in a microcontroller, manufacturers can analyze and interpret the data locally. This allows them to eliminate latency in decision making and can act quickly and securely because the data remains at the edge and does not need to be transmitted to the cloud. Processing and analysis is done in a very energy-efficient microcontroller, while architectures that use pre-processed neural networks on servers are still very energy-intensive.
As Gartner explains in its report, “The 3 Barriers to AI Adoption”, AI skills and data availability are two of the three barriers to entry that slow the adoption of AI and its mass deployment in enterprises. In a traditional model, data set and data scientists are inseparable for the success of any project. However, building a relevant data set and the availability of data scientists to work on that data and develop algorithms based on deep learning (Deep Neural Network) are the prerequisites for solution development.
Thus, industrialists no longer have to resort to these increasingly rare expert profiles and data sets that are difficult to build in order to develop machine learning solutions in the “Edge”. Semiconductor manufacturers have understood this. They are investing more and more in this type of technology, and several of them have formed partnerships with Cartesiam. They allow their customers to keep control of their data by having it analysed directly at the source (Edge), where the signal is transformed into data, rather than in the cloud.
Les signaux analysés à la source peuvent être variés et variés. Il peut être l’assistant intelligent éolienne, l’apprentissage et ensuite la surveillance des vibrations d’une machine comme Bob fait. L’objectif est de détecter les anomalies et d’effectuer des opérations de maintenance prédictive dès que nécessaire. Cette solution, basée sur NanoEdge™ AI de Cartesiam, est déjà massivement déployée dans des entreprises européennes de toutes tailles et, plus récemment, aux Etats-Unis. D’autres clients de Cartesiam, à la fois des bureaux d’études et des clients finaux, travaillent sur des solutions basées sur NanoEdge™ AI mais en utilisant différents signaux tels que le son, la magnétométrie, la pression ou les polluants atmosphériques.
Every year, 40 billion microcontrollers are sold, 15 billion of which are linked to the global economy. These components are integrated in all everyday objects, from coffee machines to air conditioners to cars and, of course, in all connected objects. It is in this integrated AI market that Cartesiam aims to become the world leader.
“Being identified in the Gartner Hype Cycle 2019 as one of the 3 suppliers of the Edge AI brick is a great honour and recognition for the entire De Cartesiam team. Our technology is the result of several years of research and development where we chose to rewrite, from algebra, all the machine learning algorithms so that they can operate in an environment as frugal as that of a microcontroller. “commented Joel Rubino, CEO and co-founder of Cartesiam.
He added: “This is how we created NanoEdge™ AI, a next generation machine learning engine. With our technology, we enable design offices and manufacturers to easily integrate machine learning functions into all everyday objects. We are several years ahead of our global competitors. This explains our rapid international expansion and the recognition of the Gartner Group.
Founded in 2016 and based in Toulon with offices in Paris and New York (USA), Cartesiam is a French software publisher whose mission is to develop artificial intelligence solutions on microcontrollers. NanoEdge™ AI, an innovation developed by Cartesiam, provides cognitive functions (Machine Learning) to microcontrollers integrated in connected objects. Whatever their industry, Cartesiam thus brings immeasurable benefits to its customers involved in projects integrating microcontrollers: simple deployment, secure environment, rich analysis and reduced energy costs. The company has around twenty employees. The company, co-founded by Marc Dupaquier, François de Rochebout, Michel and Joel Rubino, is located in Toulon for research and research and in Paris and New York for sales and marketing.