Rather than encoding specific rules that depict when a person is making a specific expression, we instead focus our attention on building intelligent algorithms that can be trained to recognize expressions. Through our partnerships across the globe, we have amassed an enormous emotional database from people driving cars, watching media content, etc. A portion of the data is then passed on to our labeling team, who are certified in the Facial Action Coding System...we have gathered 5,313,751 face videos, for a total of 38,944 hours of data, representing nearly two billion facial frames analyzed.
They got their start testing advertisements, and now are already working with a third of all Fortune 500 companies. ("We've seen that pet care and baby ads in the U.S. elicit more enjoyment than cereal ads -- which see the most enjoyment in Canada.") One company even combined their technology with Google Glass to help autistic children learn to recognize emotional cues.
The company is rolling the dice with its handling of the enterprise edition by also making those components open source and trusting that enterprises will pay for what they use in production.
An existing Python installation isn't required. During the setup process, SQL Server 2017 can pull down and install its own edition of CPython 3.5, the stock Python interpreter available from the Python.org website. Users can install their own Python packages as well or use Cython to generate C code from Python modules for additional speed.
Except it's not yet available for Linux users, according to the article. "Microsoft has previously announced SQL Server would be available for Linux, but right now, only the Windows version of SQL Server 2017 supports Python."
We (the developers) don't want to release "fixes" that users haven't accepted, but the code changes often include changes at all levels of the stack (database, DOAs, Business Rules, Webservices and multiple front-ends). Multiple code changes could be occurring in the same areas of code by different developers at the same time, making merges of branches very complex and error prone. Many fingers are in the same pie. Our team size, structure and locations prevent having a single gatekeeper for code check-ins... What tools and procedures do you use to prevent un-approved fixes from being deployed to production as part of the larger code change sets?
Fixes are included in a test build for users to test and accept -- but what if they never do? Leave your best answers in the comments. How woud you stop un-approved code changes from being deployed?
In addition, The Verge reports that if drivers look away for more than 30 seconds, "the car will know thanks to an infrared camera attached to the top of the steering column. Eyes closed? The car will know and start a sequence of alerts to get the driver's focus back on the road. It can even see through UV-blocking sunglasses." While the camera doesn't record or store data, it will flash a strip of red LED lights embedded in the top of the steering wheel "if the driver is caught not paying attention."
Cadillac plans to create and transmit an updated map every year, and will also regularly update its map by "constantly" checking the database from the Transportation Department, and deploying own trucks to draw new maps of construction areas.
DefenseCode says the exploit can be mitigated by enforcing Magento's "Add Secret Keys To URLS" feature, warning in a paper that the hole otherwise "could lead to remote code execution and thus the complete system compromise including the database containing sensitive customer information such as stored credit card numbers and other payment information." Magento has confirmed the exploit, says they're investigating it, and promises they'll address it in their next patch release.