Artificial intelligence (AI), in computer science, studies the phenomenon of human intelligence replicated by machines and, at the same time, is an engineering branch, that seeks to build instruments to support human decision. Together, science and engineering aim to allow machines to perform tasks that, when performed by humans, need the use of intelligence. But what is the path to artificial intelligence? What are its challenges? How can we apply it in practice?
It was precisely on these very current and pressing themes that Altice Labs and V21 – Technology Incubation Center got together to share on the 3rd June 2020 at 11:30 am, with a duration of 1 hour and 15 minutes, the 4th Moving Forward webinar on “Practical Paths for Artificial Intelligence“. The session featured speakers Nuno Maximiano, Analytics Portfolio and Cognitive Solutions Sales from IBM, Jorge Soares, Data Science Elite Team from IBM, Mário Rui Costa Head of Portfolio & Solutions Architecture of Altice Labs and moderated by Jorge Silva, Director/Head of IT/Europe by Huf Group.
Jorge Silva started the session by stating that there are several definitions for the concept in Artificial Intelligence and raised some questions, mainly to the companies that were present, IBM and Altice Labs: “What are the AI use cases?”, “How do we protect ourselves from AI?”, “How can we ensure that it is aligned with the purposes of humans, in order to remain unchanged?”, “How do we reinvent our society?”, “How do we safeguard data security and privacy?”, “How can companies use AI to capture new customers and find new business models?”. In fact, this field of research is not a universal solution, but it is a reference model that helps companies to identify possible workable opportunities.
Nuno Maximiano started by explaining how an Artificial Intelligence journey begins and how this computer science can be more or less complex. He stressed that the digital transformation has evolved a lot due to the pandemic that we are experiencing and companies had to adapt quickly to this challenge. The digital transformation includes people, processes and data, which are the engine for that same transformation. He also mentioned that the challenges or vectors to start or to help those who are still at an early stage of the AI journey are data, talent and confidence. Data is the lifeblood of AI, however sometimes its complexity slows down AI progress, talent has to do with knowledge and experience in teams, as supermen and superwomen are expected to work in this area , and confidence, as there is a lot of skepticism about AI, because the algorithms are sometimes complex which can generate some distrust in the process. He ended his speech by saying that “the path is made by walking” and that there is still much to be done also within organizations.
Jorge Soares complemented Nuno Maximiano’s intervention, by giving an insight into how IBM’s Data Science Elite team works, the services it provides and the value it can bring to organizations as an accelerator of their AI journeys. He highlighted the work organization of this team, and how it can help organizations to answer a set of structural questions for their journeys: “Why do I want AI?”, “What use case do we have on the table and what is its business value?”, that is, before starting a journey, it is necessary to ask these types of questions within the organization. He concluded by stating that each case is different and that each organization has its own data and specific path.
Mário Rui Costa talked about how the AI journey is evolving at Altice Labs, presenting a case study in the telecommunications industry, a proof of concept in partnership with IBM. He stressed that AI is a strategic investment of Altice Labs in its business model because there is in fact a window of opportunity to evolve processes and portfolio. In the Telecommunications and Digital Services industry there is an “ocean” of data, there is mature AI technology capable of extracting knowledge from the data and transforming processes. In order to realize this opportunity, it is necessary to invest and Altice Labs responded to the challenge by creating a specialized and multidisciplinary team to work with AI and monetize Telco knowledge. The shared case study “Mobile Network Site Down Prediction” illustrated how AI can be used to transform the reactive problem management paradigm in telecommunications networks to a proactive paradigm based on AI’s predictive capabilities.
After the Q&A session, Alcino Lavrador ended this 4th webinar by stating that Artificial Intelligence is one of the most challenging topics today and that data is the raw material for this new experience, so it is necessary to pay great attention to the veracity of this data. He also noted that data specialists, analysts or scientists are crucial in applying the right algorithms to the data. He highlighted the importance of previously selecting the problems to be solved, of finding out where the data is and how we can reach it, and of the existence of specialized teams to work with that data, culminating in the statement that “AI, in itself, is useless if we do not know how to identify and characterize the problems that we want to solve” and that can be crucial in the daily lives of people and society.