10 Companies using Machine Learning in interesting ways :
When asked what advice he’d give to world leaders, Elon Musk replied, “Implement a protocol to control the development of Artificial Intelligence.”
If left unchecked, he reasoned that machine learning technology would outgrow its developer and see it (us) as no longer an essential part of the process.
Artificial intelligence and machine learning are the technologies of the future world ! Few fields promise to “disrupt” (to borrow a favored term) life as we know it quite like machine learning, but many of the applications of machine learning technology go unseen.
In this article, we’ll uncover how it’s happening and look at 10 companies using machine learning in interesting ways that change our lives, even if we don’t know it yet.
1. IBM’s Watson :
IBM may be one of the oldest tech companies. Still, their highly renowned ML-based “Watson” natural language question and the answering system ensure they keep up with modern developments, and in turn, creating new revenue markets within healthcare.
Improved organizational performance, effective diabetes management, advanced oncology care, and ameliorated drug discovery are prominent trends of Watson that are transforming the healthcare sector.
2. Google — Neural Networks and ‘Machines That Dream’ :
Google’s mission is to enable every business to have access to Machine Learning technology. And they’re using their Neural Network (computing systems loosely based on the biological neural networks of an animal’s brain) research to ensure it happens.
Google services, for example, the image search and translation tools use sophisticated machine learning. This allows the computer to see, listen and speak in much the same way as humans do.
The most visible developments in Google’s neural network research has been the DeepMind network, the “machine that dreams.” It’s the same network that produced those psychedelic images everybody was talking about a while back ( in 2014).
Expecting more to come , following the classic research.
3. Facebook — Rise of the Chatbot Army :
Chatbots not only match their human counterparts when it comes to customer service & satisfaction , but have the potential to far exceed us, and Facebook’s leading the way in discovering the same .
Facebook also uses AI technology to enable image recognition to help identify the faces in a photo, so it can prompt the user to tag it.
Facebook employs machine learning for interpreting and making predictions about the interest of the users. By assessing the likes of the user, their friend’s likes as well as location data, Facebook uses the information for deciding the content which it feels its user will enjoy through features like Facebook Watch.
Facebook has quietly built and deployed an artificial intelligence programming tool called SapFix that scans code, automatically identifies bugs, tests different patches and suggests the best ones that engineers can choose to implement.
4. Apple :
Apple’s artificial intelligence (AI) chief says that Apple is using machine learning in almost every aspect of how we interact with our devices, but there is much more to come.
By using Core ML, developers gain access to machine learning tools to perform common tasks which include image recognition. In 2018, Apple introduced Create ML, a toolkit that makes it possible for developers to learn the basics of how to build machine learning models.
Another area where Apple makes excellent employment of Artificial Intelligence is in case of its virtual assistant Siri that uses voice queries as well as a natural language user interface (UI) for functioning and which can make calls, send text messages, respond to questions, and offer recommendations.
Siri can adapt to the users’ language, searches, as well as preferences.
5. Tesla:
Tesla is currently employing a large team of machine learning engineers working on the self-driving neural network. Each of them works on a small component of the network and they plug in their results into the larger network.
The Tesla system consists of two AI chips in order to support it for better road performance. Each of the AI chips makes a separate assessment of the traffic situation for guiding the car accordingly.
The assessment of both chips is then matched by the system and followed if the input from both is the same.
6. Baidu — The Future of Voice Search :
Google isn’t the only search giant that’s branching out into machine learning. Chinese search engine Baidu is also investing heavily in the applications of AI.
Baidu’s R&D lab Deep voice ML system can learn to replicate and reproduce the components that make up the human voice, such as accent, pitch, and pronunciation, in just three seconds.
And apparently, it’s almost impossible to distinguish from the real thing.
7. Twitter :
Twitter has revealed that it’s using machine learning to crop photos to show the most interesting parts. In the current functionality, photos are cropped off without recognizing what’s in them and what should be shown on the user’s timeline.
Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. As part of its purpose of advancing AI for Twitter in an ethical way, Twitter Cortex is the core team responsible for facilitating machine learning endeavors within the company.
8. Tailor Brands — AI Designers at Your Fingertips:
Can a machine create logos?
If it can, how, and what will it make? These are just some of the questions we encounter on a daily basis here at Tailor Brands. They come from all sides; customers, investors, new hires, and company veterans. As the Chief Technology Officer of Tailor Brands, it’s my responsibility to try and make these answers clear, especially the “how” part.
Since Tailor’s logo generator is a machine that designs, it’ll walk you through how they do it — specifically, how the “This or That” part of Tailor works. Internally, we call the “This or That” step “Ash” (named after Ash Ketchum of Pokemon), and it figures out how to map someone’s personal taste and desires and match it to their visual style so they can design a brand based on their preferences.
This process is a significant part of the decision-making algorithms they employ.
9. Netflix :
Netflix is one tech giant that has put Artificial Intelligence and data at the heart of its operations.
There are many ways in which Netflix uses Machine Learning . They may be:
a). Content Quality:
Netflix works on a supervised quality control algorithm that passes or fails the content such as audio, video, subtitle text, etc. based on the data it was trained on.
If any content is failed, then it is further checked by manually quality control to ensure that only the best quality reached the users. After all, you probably wouldn’t watch Stranger Things on Netflix if the subtitles were wrong or the audio was lagging behind the video.
b). Recommendation system :
Netflix uses their recommendations system that is based on a machine-learning algorithm that takes into account your past choices in movies, the types of genres you like, and what moves were watched by users that had similar tastes like yours.
This movie recommendation algorithm is very important for Netflix, as they have thousands of options of all types and users, are more likely to get confused in choosing what to watch next than actually watching anything.
c). Auto-generated Thumbnails:
Netflix uses personalized auto-generated thumbnail images that are created according to the individual user’s tastes in movies. Netflix uses machine learning to analyze your movie and series choices and understand what sort of thumbnail you are most likely to click.
d). Streaming Quality:
Netflix uses machine learning algorithms to predict the viewer patterns and understand when there will be general increases and decreases in viewers of spikes in viewing a certain movie or show.
Then they can cache the regional servers that are much closer to the viewers so that there is no log in streaming or loading times even during peak popularity periods.
10. Pinterest — Improved User-Content Discover :
Pinterest is a social network and image sharing service where people discover and save images, that in August 2020 had more than 400 million monthly active users saving more than 240 billion of pins.
Pinterest uses machine learning to identify content in line with items previously pinned by users and to recommend new products to its users. Its algorithms therefore inspire people by proposing them items that they might not have been initially searched.
Conclusion :
In this blog we discussed some interesting machine learning — applications in Top Companies , but these are just a handful of examples , apart from these companies, there’s plenty of others like these that have employed Artificial Intelligence & machine learning in cool and appealing ways.
While this threatens the role of humans in various traditional occupations, it also opens up a whole new avenue of opportunities that has the scope of rising in the near future.
Thanks for reading ! Have a great day ahead !