Models Will Run the World - WSJ - 0 views
-
There is no shortage of hype about artificial intelligence and big data, but models are the source of the real power behind these tools. A model is a decision framework in which the logic is derived by algorithm from data, rather than explicitly programmed by a developer or implicitly conveyed via a person’s intuition. The output is a prediction on which a decision can be mad
-
Once created, a model can learn from its successes and failures with speed and sophistication that humans usually cannot match
-
Building this system requires a mechanism (often software-based) to collect data, processes to create models from the data, the models themselves, and a mechanism (also often software based) to deliver or act on the suggestions from those models.
- ...11 more annotations...
-
A model-driven business is something beyond a data-driven business. A data-driven business collects and analyzes data to help humans make better business decisions. A model-driven business creates a system built around continuously improving models that define the business. In a data-driven business, the data helps the business; in a model-driven business, the models are the business.
-
Netflix beat Blockbuster with software; it is winning against the cable companies and content providers with its models. Its recommendation model is famous and estimated to be worth more than $1 billion a year in revenue, driving 80% of content consumption
-
Amazon used software to separate itself from physical competitors like Borders and Toys “R” Us, but its models helped it pull away from other e-commerce companies like Overstock.com . By 2013 an estimated 35% of revenue came from Amazon’s product recommendations. Those models have never stopped improving
-
Third, incumbents will be more potent competitors in this battle relative to their role in the battles of the software era. They have a meaningful advantage this time around, because they often have troves of data and startups usually don’
-
Looking to produce more-resilient crops, Monsanto’s models predict optimal places for farmers to plant based on historical yields, weather data, tractors equipped with GPS and other sensors, and field data collected from satellite imagery, which estimates where rainfall will pool and subtle variations in soil chemistry.
-
Lilt, a San Francisco-based startup, is building software that aims to make that translator five times as productive by inserting a model in the middle of the process. Instead of working from only the original text, translators using Lilt’s software are presented with a set of suggestions from the model, and they refine those as needed. The model is always learning from the changes the translator makes, simultaneously making all the other translators more productive in future projects.
-
First, businesses will increasingly be valued based on the completeness, not just the quantity, of data they create
-
Second, the goal is a flywheel, or virtuous circle. Tencent, Amazon and Netflix all demonstrate this characteristic: Models improve products, products get used more, this new data improves the product even more
-
inVia Robotics builds robots that can autonomously navigate a warehouse and pull totes from shelves to deliver them to a stationary human picker. The approach is model-driven; inVia uses models that consider item popularity and probability of association (putting sunglasses near sunscreen, for example) to adjust warehouse layout automatically and minimize the miles robots must travel. Every order provides feedback to a universe of prior predictions and improves productivity across the system.
-
Fourth, just as companies have built deep organizational capabilities to manage technology, people, and capital, the same will now happen for models