Five facts on how new technologies are disrupting traditional industries

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Artificial Intelligence (AI) is at the core of the current technological revolution. From machine learning to neural networks, a host of techniques associated with AI is changing our world, profoundly impacting every industry and forever altering every area of human endeavor.

Many believe AI is a thing of the future; that it still belongs solely in the realm of science fiction. They couldn’t be more wrong. AI is here, and it is here to stay as it empowers businesses to improve their bottom lines, give buyers a more enjoyable experience, and allow doctors to make more accurate diagnoses. Along with deep learning and computer vision, AI is trailblazing a path towards a new future we can’t even imagine TBH. Let’s explore some of the ways AI technologies are disrupting traditional industries.

Companies are Harnessing The Power of Personalized Ads

As the retail market becomes ever more crowded, companies are using AI-enabled personalization to differentiate themselves to the consumer. For this, many rely on machine learning, an AI technique based on letting systems teach themselves. You can see this manifest itself in a GIF or MEME and ads that float around platforms such as TikTok and Twitter.

Machine learning helps e-commerce firms create targeted campaigns to attract more buyers. Machine learning algorithms help digital marketers improve their advertising efforts by making better use of the growing amounts of data available. Through this AI technique, marketers can engage in advertising with better knowledge of the customer—who they are, what they are most likely to be interested in, when is the optimal time to connect with them, etc. This is used relentlessly by the likes of Google, Yahoo, Facebook, Yandex, and others.

According to a report by Boston Consulting Group, companies who use machine learning for personalization have seen sales increases of up to 10 percent compared to companies that do not use these techniques.

The Way We Shop is Changing

The way we pay has changed dramatically in recent years. From credit cards—once the state-of-the-art payment technology—the industry moved on to online payments and online wallets. Now we have mobile payments via smartphone apps and a QR code

Amazon is pushing the boundaries even further. In 2018, Amazon launched the Go stores, revolutionizing the shopping experience. This chain of stores is based on “Just walk out” or “cashier-less” technology, allowing customers to pick up the items they need and simply walking out the door. Shoppers skip the checkout entirely; after leaving the store, they are sent a receipt of their purchases through the Amazon Go app.

Chatbots are Improving the Customer Experience

Chatbots, also known as conversational AI, is another technology that has taken the world by storm. Chatbots allow companies to quickly and efficiently address customers’ main queries and problems. 

An excellent example of a company that uses this technology is Sephora, the French cosmetics manufacturer. Visitors to Sephora’s website can “try on” its lipstick and eyeshadow on a photo of themselves that they share with a bot. The bot’s AI technology identifies the user’s facial features, using augmented reality to apply these makeup tests.

As they replace humans, these chatbots are saving companies millions of dollars in salaries. At the same time, they are improving the customer experience immensely—the most advanced chatbots are now capable of answering open-ended questions very much as a human would.

Investing May Never Be the Same

Even investing has the potential to be fundamentally altered by AI. A case in point is a piece of software created by Bob Goodson, the Director of Quid AI. In 2009, Goodson was challenged to develop software that predicts which 50 companies would become successful startups in the future.

Ironically, the venture capital (VC) industry, which fueled the creation of computing, is one of the last business domains to introduce computing to decision-making. Picking startups winners was—and still is—dominated by the belief that machines do not play a role in such tasks. VCs also by and large missed the boat on Bitcoin and Tezos.

This made it all the more shocking when eight years after Goodson’s machine issued its predictions, Businessweek magazine reviewed his list. Businessweek found that about 20 percent of the companies the computer chose was valued at a billion dollars! It included names like Evernote, Spotify, Etsy, Zynga, Palantir, Cloudera, and OPOWER.

Doctors can Do More with Less

A subset of machine learning, deep learning is another AI technique attracting attention due to its flexibility. The technique is inspired by human brains. Deep learning systems are composed of layers of virtual ‘neurons.’ Each neuron is tasked with merely adding up the inputs coming into it and deciding whether to fire off a signal to the next layer of neurons.

Deep learning has applications in every industry. In the medical field, for example, it is being used to help doctors diagnose illnesses. The Chinese startup Infervision is using deep learning and image recognition to diagnose possible lung cancer with X-rays. Perhaps it can help eventually in the area if nutrition to help the world secure healthy water and other nutrients such as magnesium, potassium, cinnamon, and others.

China faces a severe shortage of doctors, especially qualified radiologists, which means radiologists wade through hundreds of scans each day to spot signs of cancer in their patients. Infervision is using deep learning to empower radiologists, enabling them to diagnose cancer more accurately and efficiently than ever before.

From changing the way we shop to how we invest our money, AI and a host of associated technologies are changing the world in profound ways. As the benefits of these technologies become more evident, companies are upping their investments in research to make machines think better and more efficiently.

FAQ

What is deep learning?

Deep learning is a subset of artificial intelligence and computer learning where machines learn to do tasks humans do by analyzing data and sets.

Is deep learning useful and how does it work?

An excellent example of a company that uses this technology is Sephora, the French cosmetics manufacturer. Visitors to Sephora’s website can “try on” its lipstick and eyeshadow on a photo of themselves that they share with a bot. The bot’s AI technology identifies the user’s facial features, using augmented reality to apply these makeup tests.

What is deep learning vs machine learning?

A subset of machine learning, deep learning is another AI technique attracting attention due to its flexibility. The technique is inspired by human brains. Deep learning systems are composed of layers of virtual ‘neurons.’ Each neuron is tasked with merely adding up the inputs coming into it and deciding whether to fire off a signal to the next layer of neurons.

Additional Resources:

MIT Deep Learning Lectures

How Does A QR Code Work?

Huawei and 5G

Stanford University Research on Deep Learning

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