Web 2.0 connects people with social media and mobile.
Web 3.0 could connect physical things with automation.
The Internet of Things (IoT), both the concept and the necessary features (e.g., infrastructure, tools, and protocols), are gaining momentum.
Each successive stage of the web relies on previous stages. The previous stage becomes the assembly language of the next stage. If static web content can be generated automatically, there is then engineering bandwidth to tackle dynamic web content.
The number of processes that can be automated continue to increase. We are now the cusp of the next generation of web automation - the cost of aggregating the information from the physical items, from consumer products to industrial processes, is dropping below the return-on-investment threshold.
The potential amount of data from this transition is staggering. The previous two versions of the web each redefined "big data." We are on the cusp of another inflection point. There isn't enough engineering bandwidth to make sense of this data with static / human-based systems.
Machine learning is the tool to leverage the promise of Web 3.0.
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