AI technology is spreading into the most obscure industries. Here are 3 niche areas that machine learning will soon dominate.
Machine learning will be used to determine the next big thing in the fashion industry
India-based designers, Shane and Falguni Peacock, rely on IBM's Watson for newest fashion trend.
Here's how it works: IBM's Watson will sift through a variety of consumer pictures, searching for items that are popular among consumers. Watson will go through millions of images, tagging the most liked and shared images uploaded online. Popular items may have a certain shape and cut to them, an attractive pattern, or the material being used may be more comfortable and durable when compared with something similar. The trick is to learn what the consumer likes, produce the item, and market it.
Computers may soon be writing fiction - no, you can't make this stuff up
Japan's Nikkei Hoshi Shinichi Literary Award recently included an entry that was co-written by a human and a computer. The judges were told that there would be an entry co-written by a computer but did not know which entry this would be. The particular entry made its way past the first stage of the contest.
Computers are already being used to write news articles, or summarize news articles. If you take a quick peek through Reddit's news section, you can see a bot going through the more popular threads, providing a short summary of the linked news article.
Machines may soon sing your favorite songs
Voice synthesizers are already available in the market, and users can create 'singing' with two input materials: lyrics and melody. The vocals for this software are generated using the voices of popular singers and voice actors. The voices are blended together, and special effects, such as vibrato, are added to give a human quality to the synthesized sound.
Vocaloid songs are already popular. In fact, there are even concerts to showcase the popular songs. These have high attendance numbers.
Machine learning is already a given in a number of fast-growing fields, including autonomous vehicles and search engines. With every step and every new scenario, the computer will be better equipped to handle certain environmental inputs or search parameters, ultimately surpassing human capabilities.
Machine learning is used to enable ADAS technology.
ADAS technology is enabled with the use of several high-end hardware pieces, an FPGA, a CPU or a GPU. In all cases, an FPGA or a GPU will be used alongside a CPU. The FPGA or GPU will be included to provide additional processing power to the PCB board, lifting the CPU's total burden.
Companies like Tesla and Nvidia have partnered together to use the GPU/CPU combination to power the processing needs behind their ADAS technology. Meanwhile, Intel is leaning towards the FPGA/CPU combination. Intel solidified its agenda with the company's 2015 purchase of Altera FPGA.
ADAS systems use high-end FPGA to enable their processing power. At times, the ADAS system will need to come up with a split-second decision based on the input captured through the car's sensory system. For the system to work, it is imperative to use the best FPGA on the market.
Current top-sellers include Intel FPGA's Stratix 10 family, and Xilinx FPGA's Zynq-7000 SoC series.
Are you in the market for FPGA? Check out our list of FPGA to see if what you're looking for is available through EarthTron.
Do you know of any other niche areas that machine learning/AI is already a part of? Let us know in the comment section.