8 Companies Using Machine Learning in Cool 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.

And as few technologies are more progressive or disruptive in their advancement, he might have a point!

But before ML pulls a terminator on us, it's shaking up the corporate landscape, unlocking once closed markets, leveling playing fields by providing innovative solutions to long-standing problems, and making it easier for the little guys to compete with the corporate goliaths.

And that's pretty cool.

In this article, we'll uncover how it's happening and look at 8 companies using machine learning in cool ways that change our lives, even if we don't know it yet.

Chatbots not only match their human counterparts when it comes to customer service but have the potential to far exceed us, and Facebook's leading the way in discovering how.

Facebook Messenger is now a testing ground for chatbots, and if you use it, you're the subject, and you might not have even noticed it!

Chatbots are quickly becoming indistinguishable from humans when chatting via text because they have access to an immeasurable number of customer-related data points and can detect repetitive problems, patterns, and predict user issues. Meaning they are perfectly equipped for customer service agent roles and are an invaluable addition to modern business.

Facebook's also enabling SME to avail of the advantages by allowing third-party developers to submit a chatbot inclusion in Messenger. So, even if your resources are limited, you can still provide an excellent customer service level leveraging chatbots.

Nice one, Facebook.

Contentious, controversial, and borderline are some of the terms; users have chosen to describe Twitter algorithmically curated timelines.

So, why's it cool?

It's how Twitter's Machine Learning technology works out which tweets to promote first.

Twitter's Artificial Intelligence evaluates your tweets in real-time and rates them according to various metrics and your individual preferences. Ultimately, it's all about increasing your usage time, so they choose the tweets most likely to drive engagements.

Algorithmically curated feeds are a contentious issue. While the Twitter ML is highly innovative, you can't help but think it's missing the point, as users love Twitter for its spontaneity, or they thought they did!

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.

Recent research that got everyone talking was Google's Deep Dream computer vision program (released in 2014) that uses their neural network to develop dream-like psychedelic images.

But their research in this area goes much deeper. Google calls it "classic algorithms," and it reaches into virtually all aspects of machine learning, such as speech translation, language processing, breast cancer research, wind farm technology, and of course, predictive search ranking systems.

Expect much more to come.

While other review sites have come and gone, Yelp has remained the reviewer's favorite. And now, they're reinforcing their position by incorporating machine learning into their platform. Their goal is to enhance the user's experience even further by improving its image processing capabilities.

Its machine learning algorithms enable the company's human element, its staff, to use its picture classification technology to categorize and label millions of photos in a fraction of the time. Improving efficiency and helping businesses like yours; here's how:

Yelp tells us that businesses with over ten photos on their page get a massive 12 times more monthly customer connections. Further-more you can use your images to show potential customers your business's personal side and highlight your USP, products, and services.

Ultimately leading to an increased ROI, it doesn't get much cooler than that!

Since arriving in 2014, Tailor Brands has quickly become a champion for SME wanting to create or improve their logos. In 2018 Tailor brands took their platform to the next level by raising $15.5 million to grow and expand it with AI technology, the result being a platform that does far more than logos.

Their ML system now enables small businesses to create their entire branding strategy, from logos to websites, and even more importantly, a social media marketing tool kit.

Tailor Brands uses machine learning to match logo designs, fonts, and colors with brands and their market place. You provide the platform with your relevant company and marketplace information. It uses its extensive and self-updating system to find and match what elements are proven to work for you.

It's an excellent example of how AI can level the playing field and make products and services affordable to everyone.

Baidu is the Chinese equivalent to Google. They are also increasing their use of machine learning technology; one such development is their Deep voice technology that can create synthetic human voices using deep neural networks.

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.

The technology has the potential for improving virtual assistants like Alexa, Google Assistant, and Siri. It could have a massive impact on personalizing human-machine interfaces and the natural language processing systems used for voice search and voice recognition, along with numerous other uses, such as biometric security and real-time translation.

However, the central area is healthcare, as Baidu claims it will help those who've lost their voice communicate again, and that's very cool.

HubSpot bought the artificial intelligence and machine learning startup Kemvi back in 2017. The acquisition's focal point was its proprietary algorithm, DeepGraph, designed to equip salespeople with the tools required to improve relationships with prospective customers.

HubSpot tells us it's all about Data cleanliness; let's look at the features and benefits:

HubSpot's belief is the cleaner the data, the more-free time sales and marketing teams will have to do their job by converting leads into deals, and it, of course, makes perfect sense.

It does it by identifying potential sales prospects and collecting their contact information. The CRM also locates new market segments, creates and sends emails, integrates with Outlook, Gmail, Salesforce, and other software, and follows up and nurtures potential prospect relationships until they're ready for contact by the salesperson.

Now that's handy.

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.

Watson's now used in medical centers and hospitals worldwide and helps physicians diagnose and treat potential symptoms by inputting the patient's data.

It's also now being used within the retail sector to identify shoppers, provide recommendations, and alternative upsell options. As with all ML, Watson shows no signs of slowing down with its development.

What was it Elon said about ML again?!