Machine learning is a certain type of artificial intelligence that allows the development of systems that can learn without being programmed to do so, or with only minimum startup logic. The primary way in which machine learning works is that the system develops knowledge or intelligence in response to continual exposure to new data.
The World Economic Forum just published a fascinating article charting the growth of the European startup scene, contrasting it to the larger tech ecosystems of Silicon Valley and Asia. If you’re a European founder, you’ve got cause to be optimistic — funding is easier to get, there’s so much innovation happening here, and tech talent is everywhere.
Today’s infographic comes from Funders and Founders and information designer Anna Vital, and it lists the important metrics to gauge traction and success of new startups.
Several years ago, a key challenge with launching a new tech startup venture was that there weren’t many precedents to follow.
- How do you scale a company?
- How do you measure growth and costs in a more meaningful way?
- Does the company have real traction?
The volume of potential use cases being tipped for blockchain are increasing day by day – yet few seem to be ready in practice – so, when I received an email suggesting that the next area ripe for disruption was the energy sector, I was interested to learn more. A lightly edited Q&A with Guy Halford-Thompson, founder and CEO of BTL Group, which develops and invests in blockchain technology, can be found below.