As computer vision quietly spreads through our lives and landscapes, it’s entertaining and practical, powerful and flawed, amusing and disturbing. The same goes for AI as a whole. You can’t see it. But it’s everywhere.
“There were no conclusions,” said Henry Dills, a photographer and cellist who watched the performance dressed in a brown sport coat and a white scarf that reached past his waist. “These machines are starting to massively overshadow us. It used to be God. Now it’s machines.”
“There is an arms race in the nascent market for GPU-accelerated databases, and the winner will be the one that can scale to the largest datasets while also providing the most compatibility with industry-standard SQL.
MapD and Kinetica are the leaders in this market, but BlazingDB, Blazegraph, and PG-Strom also in the field, and we think it won’t be long before the commercial relational database makers start adding GPU acceleration to their products, much as they have followed SAP HANA with in-memory processing.”
“Ignoring AI now means the United States will lag behind more forward-thinking countries that invest in AI today. While the United States waits “50 to 100 years” for AI to become a reality of life, other countries will be doing the hard work, laying the necessary infrastructure, and gaining from machine learning, and the human learning that goes along with it.”
As a developer, there is too much out there to master everything. Don’t even try. Learn how you work best as a developer, build a toolset that fits you, and don’t try to have all the answers. Focus on learning how to find the answers quickly.
While companies commonly use these databases to store tempting troves of customer and financial data, they often do so with outdated and weak default security configurations. And while any type of database can be left open or unprotected, a string of breaches over the last few years have all centered around one type in particular: open-source “NoSQL” databases, particularly those using the popular MongoDB database program.