Machine learning is changing the face of technology, not to mention the way we do things. Machine learning is giving devices the ability to become increasingly smarter, allowing them to make decisions on their own and provide a better experience. This technology continues to expand, with the percentage of businesses investing globally expected to reach 64% by 2023.How Machine Learning Apps are Changing the Face of TechnologyMachine learning, on a global scale, makes mobile platforms easier to use, improves the customer experience, maintains customer loyalty and helps create consistent user experiences. It’s no surprise that Machine Learning as a service market is predicted to reach $5,537 million in 2023.Not only is it improving user experience, machine learning enhances apps in a variety of ways, delivering many benefits:
- More personalized experience
- More relevant ads
- Predictive user behavior
- Enhanced user engagement
- Improved security
- Self-driving cars
Companies like Google who have created these autonomous vehicles need to teach a computer how to take over driving using digital sensors. This requires using large amounts of data to build algorithms.
One of the most popular areas of deep learning is voice search and voice assistants. More homes report owning one of these devices, like Siri, alexa and Cortana. These devices are becoming smarter all the time, delivering better, more intuitive search results for users.
- Automatically adding sounds to silent movies
In this task, the system must synthesize sounds to match a silent video. The system is trained using 1000 examples of video with sound of a drumstick striking different surfaces and creating different sounds. A deep learning model associates the video frames with a database of pre-recorded sounds in order to select a sound to play that best matches what is happening in the scene.
This technology translates words or phrases into another language. This has been around for many years but can now done on mobile devices and includes translation of texts and images.
- Automatic text generation
Text-to-talk technology is not new, however, it is constantly improving. Mobile devices and assistants have learned natural syntax, as well as how to spell, punctuate and form sentences.
Harvard scientists used Deep Learning to teach a computer to perform viscoelastic computations, these are the computations used in predictions of earthquakes. Until their paper, such computations were very computer intensive, but this application of Deep Learning improved calculation time by 50,000%. When it comes to earthquake calculation, timing is important and this improvement can be vital in saving a life.
Futures markets are seeing great success with the implementation of neural finance networks. Investors can more accurately predict trends and successes in futures markets.
Image recognition aims to recognize and identify people and objects in images as well as to understand the content and context. Image recognition is being used widely in gaming, tourism, social media, retail and more.
- Automatic handwriting generation
This technology generates new handwriting examples for objects from a variety of writing samples. This allows for an understanding of pen movements to generate new letters and examples.
The field of advertising has been revolutionized by deep learning. Machine learning allows for more predictive, intuitive ad matching based on user searches across a variety of platforms. Have you ever looked at an item online and had it pop up in your news feed later that day? That’s a solid example of machine learning.
Image colorization is adding color to black and white photographs. Generally, the approach involves the use of very large convolutional neural networks and supervised layers that recreate the image with the addition of color.
- Energy market price forecasting
This provides a window into price fluctuations and availability from the energy grid. This helps suppliers bid on energy to offer the best pricing to consumers.
- Neural networks for brain cancer detection
A team of French researchers noted that spotting invasive brain cancer cells during surgery is difficult, in part because of the effects of lighting in operating rooms. They found that using neural networks in conjunction with Raman spectroscopy during operations allows them to detect the cancerous cells easier and reduce residual cancer post-operation.
Automatic image captioning is the task where given an image the system must generate a caption that describes the contents of the image. Once you can detect objects in photographs and generate labels for those objects, you can see that the next step is to turn those labels into a coherent sentence description.
- Healthcare-related deep learning
AI is completely reshaping life sciences, medicine, and healthcare as an industry. Innovations in AI are advancing the future of precision medicine and population health management in unbelievable ways. Computer-aided detection, quantitative imaging, decision support tools and computer-aided diagnosis will play a big role in years to come.Appek is the premier app design company serving a variety of industries. Our technology continues to improve as we’ve begun to design apps for machine learning for both IOS and Android platforms. Contact us today to learn more and start planning your app design strategy today.