How is machine learning being used today? This blog is based off an article by the Economic Times.
1) Financial trading
Certain financial transactions already rely on automated programs. Machines are used to facilitate transactions that happen almost instantaneously. In the financial market, being the first to complete a transaction maybe the difference between making a profit or not. Today's machine learning software is being developed to 'learn' from certain scenarios so that, eventually, humans will no longer be needed to weigh in on critical decisions. Based on the knowledge and expertise the machine has already accumulated, a decision will be made.
2) Airline ticket pricing
Machine learning is already being used to determine if an airline ticket price will rise or fall within the next few days. The feature is available on websites like Kayak. There's a line graph on the left, indicating if the buyer should purchase the ticket or wait. These scenarios are made based on experiences the program has already collected.
The technology is also being used for trains bookings. Users on a wait list can determine the likelihood of purchasing a ticket.
3) Online ad placement
The possibilities are endless when it comes to advertising your product or service online. Millions of users visit a range of different websites, and manually placing your ad on a website is no longer an option. Instead, imagine a service where a machine can analyze certain websites, the users that visit the website, and then spits out an answer, recommending if your ad should be placed on the website or not.
Just recently, Xilinx invested with DeePhi Tech, a Chinese firm that was started just last year to facilitate the growth of machine learning applications.
"Xilinx FPGAs and MPSoCs provide the ideal combination of low latency and reconfigurability required for our inference solutions," said Yao Song, CEO at DeePhi Tech. "Xilinx's powerful platforms are already being used by DeePhi in commercial products from edge to cloud in smart surveillance and data center applications."
When we think of machine learning, we think of a full-scale robot. While machine learning has not progressed to that level just yet, it is on the rise, currently automating and facilitating certain tasks and which are impossible for the human brain to comprehend.
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Link to Xilinx press release.