Artificial intelligence and machine learning are some of the most significant technological developments of recent times. However, they still remain underestimated in terms of application throught 2019.

10 Incredible examples of AI And Machine Learning ML in practice. We want to see how machine learning is applied in real life?

Here we have compiled 10 companies that effectively use new technologies in their strategy.

1. YELP - IMAGE CURATION

Although Yelp, a popular reviews site, doesn’t seem like a high-tech brand, it actively uses machine learning to improve its user experience.

Classifying images into façade / interior categories seems like an easy task for a person, but a computer can handle it quite difficult.

Photos are important for Yelp no less than user reviews, which is why the company makes a lot of efforts to improve the efficiency of working with images.

A few years ago, the brand decided to turn to machine learning and first applied photo classification technology. Algorithms help company employees select categories for images and put down tags. The contribution of machine learning is hard to overestimate, because the brand has to analyze tens of millions of photos.

2. PINTEREST - CONTENT SEARCH

The main function of the Pinterest social network is curation of content . And the company is doing everything possible to increase the efficiency of this process, including the use of machine learning.

In 2015, Pinterest acquired Kosei, a company specializing in the commercial use of machine learning (in particular, content search and recommendation algorithms).

Today, machine learning is involved in every aspect of Pinterest’s business operations, from moderation of spam and content searches to monetizing ads and reducing the number of unsubscribes from newsletters. Not bad.

3. FACEBOOK - THE ARMY OF CHATBOTS

Facebook Messenger is one of the most interesting products of the largest social platform in the world. All because the messenger has become a kind of chatbot laboratory . When communicating with some of them, it is difficult to understand that you are not talking to a person.

Any developer can launch it on the basis of Facebook Messenger. Thanks to this, even small companies are able to offer customers excellent service.

Of course, this is not the only machine learning application on Facebook. AI applications are used to filter spam and low-quality content; the company also develops computer vision algorithms that allow computers to “read” images.

4. TWITTER - NEWS FEED
One of the most significant changes in Twitter in recent years is the transition to a news feed based on algorithms.

Now users of social networks can sort the displayed content by popularity or by publication time.

The basis of these changes is the use of machine learning. Artificial intelligence analyzes each tweet in real time and evaluates it according to several indicators.

The Twitte algorithm primarily shows those entries that are more likely to please the user. Moreover, the choice is based on his personal preferences.

5. GOOGLE - NEURAL NETWORKS

Google has an impressive technological ambition. It is difficult to imagine the field of scientific research in which this corporation (or its parent company Alphabet) would not have contributed.

For example, in recent years, Google has been developing aging technologies, medical devices, and neural networks.

The company's most significant achievement is the creation of machines in DeepMind that can dream and create unusual images.

Google is committed to exploring all aspects of machine learning, which helps the company improve classical algorithms, as well as more efficiently process and translate natural speech, improve ranking and predictive systems.

6. EDGECASE - CONVERSION RATES

For a long time, retailers have been trying to combine shopping in online and offline stores. But only a few really succeed.

Edgecase uses machine learning to enhance its customer experience. At the same time, the brand seeks not only to increase conversion rates, but wants to help those customers who have a vague idea of ​​what they want.

By analyzing the behavior and actions of users that indicate their intention to make a purchase, the brand makes online search more useful and brings it closer to the experience of shopping in a traditional store.

7. BAIDU - THE FUTURE OF VOICE SEARCH

Google is not the only search giant that masters machine learning. Chinese search engine Baidu is also actively investing in the development of AI.

One of the most interesting developments of the company is Deep Voice, a neural network capable of generating synthetic human voices that are almost impossible to distinguish from real ones. The system can imitate features of intonation, pronunciation, stress and pitch.

The latest Baidu Deep Voice 2 invention will significantly affect the efficiency of natural language processing, voice search and speech recognition systems. It will be possible to apply the new technology in other areas, for example, interpretation and biometric security systems.

8. HUBSPOT - SMART SALES

HubSpot has long been known for its interest in technology. The company recently acquired Kemvi, a brand specializing in machine learning.

HubSpot plans to use Kemvi technology for several purposes: the most significant is the integration of machine learning and natural language processing DeepGraph with an internal content management system.

This will allow the company to more effectively define “triggers” - changes in the structure and management of the company that affect day-to-day operations. With this innovation, HubSpot will be able to more effectively attract customers and provide a high level of service.

9. IBM - NEXT GENERATION HEALTHCARE

The largest technology corporation IBM is abandoning an outdated business model and is actively exploring new directions. The brand’s most famous product today is Watson Artificial Intelligence.

Over the past few years, Watson has been used in hospitals and medical centers where it has diagnosed certain types of cancer more effectively than oncologists.

Watson also has tremendous retail potential where it can serve as a consultant. IBM offers its license-based product, which makes it unique and more affordable.

10. SALESFORCE - SMART CRM SYSTEMS

Salesforce is the titanium of the technology world with a significant market share in customer relationship management (CRM).

Predictive analytics and lead assessments are the main challenges of today's online marketers, which is why Salesforce places high stakes on its Einstein machine learning technology.

Einstein allows companies that use Salesforce CRM to analyze every aspect of their customer relationship - from the first contact to the next points of contact. Thanks to this, they can create more detailed profiles and determine the most important points in the sales process. All this leads to a more effective assessment of leads, improving the quality of customer experience and expanding opportunities.

The future of machine learning
Some of the forms of machine learning listed above seemed fiction ten years ago. Moreover, each new discovery does not cease to amaze today.

What AI and Machine Learning trends await us in the near future 2020?

1. MACHINES THAT LEARN EVEN MORE EFFICIENTLY
Very soon, artificial intelligence will be able to learn much more efficiently: machines will improve with minimal human involvement.

2. AUTOMATION OF THE FIGHT AGAINST CYBER ATTACKS
The rise of cybercrime is forcing companies to think about defenses. Soon, AI will play an increasingly important role in monitoring, preventing and responding to cyber attacks.

3. CONVINCING GENERATIVE MODELS
Generative models such as those used in Baidu from the example above are pretty convincing today. But soon we will not be able to distinguish cars from people at all. In the future, algorithms will be able to create pictures, imitate human speech and even entire personalities.

4. QUICK TRAINING
Even the most complex artificial intelligence needs a huge amount of data for training. Soon, machine learning systems will require less and less information and time.

5. INDEPENDENT ARTIFICIAL INTELLIGENCE
For a long time, people have been wondering if artificial intelligence can be dangerous to humans.

In June of this year, Facebook’s artificial intelligence research team (FAIR) experts decided to disable one of the systems they created, as the bots began to communicate in their own language, which was incomprehensible to humans. Experts call for the introduction of regulation of this area of ​​technology in order to avoid the threat of artificial intelligence getting out of control.

In the future, this may lead to restrictions and even a slowdown in the development of this area. In any case, it is important to use new technologies for the benefit of mankind, and not to the detriment. And this requires strict regulation of the industry.

YOU KNOW Over 50% of advertisers will use AI in 2020

This conclusion was reached by the authors of the research “AI in marketing” from the Segmento advertising platform, who interviewed representatives of the 300 largest advertising companies. 20% of companies said they already use artificial intelligence for marketing purposes, they will join another 32% next year. The remaining 48% of companies refuse to use the technology because they lack the competencies to make a positive decision (33%), it will be difficult to find experienced specialists in the field of AI (27%) until they assess the possibility of using the technology (18%).

The most popular AI-based tools are programmatic purchase of media advertising and retargeting - returning a visitor to the advertiser's website (48% each), chatbots and big data analysis for making management decisions (38% each), personalizing a website or mobile application (29% ) Almost a quarter of companies predict AI customer satisfaction. The technology is least used to offer consumers individual prices for goods and services (5%). Companies also use AI to automate call centers and improve the quality of goods and services.

As a rule, advertisers turn to advertising agencies (47%) and AI-specializing companies (33%) to integrate relevant solutions into the marketing practices of their companies.

“In the case of artificial intelligence, it can be stated that so far the technology solves specific applied problems pointwise, and their spectrum is very limited. For a more substantial and comprehensive integration of AI, companies will have to conduct a global audit of their business processes.

Amram David

Senior Contributor at DFI Club
Amram is a technical analyst and partner at DFI Club Research, a high-tech research and advisory firm .He has over 10 years of technical and business experience with leading high-tech companies including Huawei,Nokia,Ericsson on ICT, Semiconductor, Microelectronics Systems and embedded systems.Amram focuses on the business critical points where new technologies drive innovations.
Amram David

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