What do broadband coverage and artificial intelligence have in common? Answer: “The last mile”. Both of these technologies are difficult to reach where they are most needed. Broadband is for households, especially households in rural areas. In the case of artificial intelligence, it is applications, especially those that are directly related to human work.
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Canadian startup Element AI has been committed to exploring and shaping this interface between artificial intelligence and human work since its establishment. “Our mission is to reshape the intelligent collaboration between man and machine. We make progress possible, further development feasible, and breakthrough credibility,” is the company’s motto.
Starting next year, Element AI will be allowed to perform this task on a larger scale. This startup was taken over by ServiceNow last month and aims to help the group “build the world’s smartest workflow platform.” With the help of the Now platform, users should be able to “work smarter and faster, optimize business decisions and open up new levels of productivity.”
Element AI is a good company. In the past 12 months alone, three other artificial intelligence startups-Loom Systems, Passage AI and Sweagle-have been taken over-and they have not found a “green artificial intelligence field” in ServiceNow. Before them, seven other AI experts joined ServiceNow: Appsee, Attivio, Parlo, SkyGiraffe, FriendlyData, Qlue and DxContinuum.
ServiceNow’s artificial intelligence activities have been coordinated under the leadership of Chief Artificial Intelligence Officer Vijay Narayanan since March last year. This experienced AI expert was the head of Pinterest content and discovery engineering, and was previously the head of Microsoft’s algorithm and data science solutions. One of his challenges at ServiceNow is to make AI part of the workflow.
“Machine learning has made tremendous progress in research,” Narayanan said. “But when it comes to applying and using machine learning to make real business contributions, I think it is not that effective. Machine learning uses data and training models to make a series of recommendations and communicate them to you, what users do next ——It will give you some hints or a series of recommendations. But most organizations find it difficult to translate these decisions and recommendations into actual actions.”
This is what Narayanan calls the “last mile problem” because AI platforms are usually located outside the area where actual work takes place. For most companies, it is still very difficult to integrate these two parts with each other and build a fully automated system for training models and performing actions. But this is precisely the reason for providing the company with relevant business results.
Photo: ServiceNow
“If you can bring high-quality AI capabilities to the workflow platform, then you are close to the last mile,” Narayanan explained. This not only provides a good opportunity for making specific recommendations based on analysis and forecasting, but also for activating and controlling actual measures.
But this is why Narayanan found his work at ServiceNow so attractive. “Can we use these AI capabilities for advanced, complete use cases and introduce them to the workflow platform natively? If you can do all of this work on a single platform with a unified data model and architecture, I think you It can increase very, very much after the contribution of artificial intelligence to the company.”
For this reason, Element AI should also play a special role in ServiceNow’s AI network, not just because it has an AI celebrity in its team, Yoshua Bengio-Bengio obtained the famous AI research map in 2018 Spirit award. On the contrary, because the work of Element AI is related to the workflow field, it is related to the core competence of ServiceNow. Therefore, the company will set up an artificial intelligence innovation center in Canada to accelerate customer-centric artificial intelligence innovation on the Now platform.
Centralized AI capabilities in Canada and the Service Now headquarters in Chicago, Kirkland, San Diego, Hyderabad, and Santa Clara will also be necessary because the challenges are great, even if the task is easy to formulate: “We have to work without a large number of data scientists Or the case of a machine learning engineer makes AI very easy to use,” Naranayan said.
If you want to understand how ServiceNow makes artificial intelligence part of the Now platform, you should look at AIOps, ServiceNow’s AI-supported IT service management.
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