Tag: AI

We’re clearly moving into a world that is more disruptive and where there’s more randomness in our businesses and our lives. And that means that we need to think differently about how we interact. With the world moving forward, instead of focusing first on optimization and efficiency, we need to focus first on resilience and flexibility because when you do that, you create dramatically better outcomes over time. There are three basic things that you can do to increase your resilience and flexibility. The first and most important thing is to become aware of the range of things that are possible. If you believe that the range of things that are possible are only those that you’ve experienced in your lifetime, then we’re in for a big Surprise!

Despite all the hype about data, analytics, and primarily AI, it must be clear that people remain the key factor in projects. AI has zero value without data, and data has zero value if people are not bought into data as a concept. In the end, data is produced through people’s activities. That could be project plans, RAID logs, stakeholder maps, etc., but also presentations, meetings, reports, lessons learned, and so forth. Everything is data that we as people produce and need to feed into a data ecosystem for us to make continuous use of growing information and knowledge. And with such a workable data ecosystem, meaningful analytics can be applied that produce valuable insights for our project decisions.

In the VUCA world project complexity continues to grow. We are introducing new tools and methods like AI so we can gather more information and improve project control. But will this focus on technology help us dealing with rising levels of stress and anxiety in the project management workforce? Are we missing something in our quest to lead and control complex projects? Carole Osterweil talks to Bartosz Zych about using ideas from neuroscience to regulate emotions, reduce project complexity and realise the benefits of tools like AI.

Z Pawłem Nogą, konsultantem ds. deep learning, rozmawia Malwina Szopa Pawle, posiadasz szerokie doświadczenie w branży IT, poświęciłeś się całkowicie pracy w obszarze AI. Czy możesz przybliżyć naszym Czytelnikom, co skłoniło Cię do zainteresowania się tą dziedziną? Przypadek. Zajmowałem się głównie testowaniem oprogramowania i budowaniem zespołów odpowiedzialnych za szeroko pojęte QA. Pewnego dnia otrzymałem propozycję stworzenia od zera zespołu testującego sprzęt i oprogramowanie do deep learningu. Skorzystałem z tej oferty i tak zaczęła się moja już pięcioletnia przygoda z AI, a w szczególności z testowaniem jego wydajności.