The market for recommendation engines is predicted to grow by USD $3.57B in the next four years, according to a recent report from Technavio. What’s the story behind these growth numbers? We talked with MIT Professor of Electrical Engineering & Computer Science and co-founder of machine learning startup Celect, Devavrat Shah, about the findings from this recent report and to discuss his predictions for recommendation systems technology.

It’s more important than ever for professionals to build the skills and capabilities they need to drive innovation. In a recent McKinsey study, more than 75% of executives surveyed predicted that the COVID-19 crisis would create significant new opportunities for growth. Instead of simply adapting to it, innovators from all industries must embrace and leverage disruption to thrive.

There’s a story that John Wass likes to tell to illustrate the value of systems thinking. A CEO is holding the end of quarter meeting with their executive team. They go around the table, and everyone proudly reports that they’ve hit their KPIs. There’s just one problem. The CEO hasn’t achieved the company’s overall profitability goals. “Why,” the CEO asks, “Am I not doing great when all of you are?”

Although machine learning offers important new capabilities for solving today’s complex problems, more organizations may be tempted to apply machine learning techniques as a one-size-fits all solution.

The coronavirus pandemic has up ended the business world, education, and the workplace and landed us in a protracted moment of uncertainty and disruption. Companies are scrambling to manage distributed teams and coordinate work remotely, while retaining customers and finding new sources of revenue. Some must fully reinvent themselves to survive, as their traditional markets have shrunk or disappeared entirely.

Our abrupt and ongoing shift to remote work is having wide-ranging effects on design, engineering, and manufacturing industries, putting great pressure on organizations to be more agile, efficient, and flexible in a COVID-19 world.

Drawing on examples from manufacturing, retail and healthcare sectors, The Workforce Education Project's “roadmap for change” preliminary report from MIT Open Learning studied workforce challenges in the U.S. and developed case studies of how organizations are facing these challenges. The report presents a path forward to help expand both educational and job opportunities in the context of today’s workforce environment and demands.

There are more online learning resources to choose from than ever before. If you’re looking to learn emerging technologies or prepare your workforce for digital transformation an informational webinar can help you explore the content, structure, and learning outcomes of a prospective online course. Explore online courses and programs in topics like additive manufacturing, leadership, machine learning, negotiation, systems engineering, and quantum computing. Register to view any of the MIT-faculty led on-demand webinars below.

More professionals than ever are looking into online courses, including ones previously relegated to traditional classroom settings. Conventional wisdom once said that human skills like leadership and negotiation could not be learned online. However, this may no longer be the case. The Curve interviewed two online education experts at MIT about how educators and learners can improve the quality and efficacy of their next online course.

Finance is core to all business operations, but it isn’t the sole domain of MBA graduates and Wall Street analysts. All professionals benefit from strong finance understanding and capability as they make decisions, manage budgets, and work to advance new ideas and initiatives across their organizations.