As Web 3.0 continues to develop and various projects build out important infrastructure to scale a decentralised web to the masses, many of these protocols can be viewed as public utilities to be used by new emerging market applications.

This article summarises machine learning and its relation to data silos before introducing Outlier Ventures’ first step into apps in the Convergence Ecosystem.

Token design is perhaps the most discussed and exciting aspect of the entire process. A huge database of cryptographic primitives have emerged, and new ones are introduced almost every week.

Today, a world without machine learning is hard to imagine. From voice assistants to the analysis of medical data to self-driving cars, these algorithms power the latest and most advanced technologies. All this is enabled by large amounts of data, provided by individuals and businesses.

The first phase of token creation should start with an understanding of the ecosystem itself. In the Discovery Phase, we propose a process for token teams to formulate and align on the problem they are actually trying to solve. The fundamental question of “Why a token?” seems like a simple one, but getting internal alignment on the answer is harder then it seems. The discovery phase is all about determining and aligning on the particular characteristics of your business model, and defining the requirements for your token design.

Outlier Ventures today published the Q3 report in its State of Blockchains series, which provides an overview into blockchain investment and market trends worldwide. The report reveals a range of insights into the market, three of which are: