Big data and artificial intelligence (AI) power everything that the business does – the global director of digital innovation, Greg Chambers, said: “Artificial intelligence is the foundation for everything we do. We create intelligent experiences. Artificial intelligence is the kernel that powers that experience.”

What Problem Is Artificial Intelligence Helping To Solve?

Marketing soft drinks around the world is not a “one-size-fits-all affair”. Coca-Cola products are  marketed and sold in over 200 countries.

In each of these markets there are local differences concerning flavours, sugar and calorie contents, marketing preferences and competitors faced by the brand.

This means that to stay on top of the game in every territory, it must collect and analyse huge amounts of data from disparate sources to determine which of its 500 brands are likely to be well received. The taste of their most well-known brands will even differ from country to country, and understanding these local preferences is a hugely complex task.

How Is Artificial Intelligence Used In Practice?

Coca-Cola serves a large number of its drinks every day through vending machines. On newer machines, typically the customer will interact through a touch-screen display, enabling them to select the product they want and even customise it with “shots” of different flavours. The company has begun fitting these machines with AI algorithms allowing them to promote drinks and flavours that are most likely to be well received in the specific locations where they are installed.

The vending machines can even alter their “mood” depending on where they are located – with machines in a shopping mall displaying a colourful, fun persona, those in a gym more focused on achieving performance, and those in a hospital appearing more functional.

Coca-Cola also uses AI to analyse social media and understand where, when and how its customers like to consume its products, as well as which products are popular in particular localities. With over 90% of consumers making purchasing decisions based on social media content, understanding how its billions of customers are discussing and interacting with the brand on platforms like Facebook, Twitter and Instagram is essential to its marketing strategy. To do this, Coca-Cola analysed engagement with over 120,000 pieces of social content to understand the demographics and behavior of its customers and those discussing the products.

Another application of AI was in securing proof of purchase for the company’s loyalty and reward schemes. When customers were asked to manually enter 14-digit product codes printed on bottle caps into websites and apps to verify their purchases, uptake was understandably low due to the unwieldy nature of the operation.

To encourage more customers to engage with these schemes, Coca-Cola worked to develop image recognition technology that allows purchases to be verified by taking a single smartphone picture.

What Technology, Tools And Data Were Used?

Coca-Cola collects data on local drink preferences through the interfaces on its touch-screen vending machines – over 1 million of them are installed in Japan alone.

To understand how its products are discussed and shared on social media, the company has set up 37 “social centers” to collect data and analyse it for insights using the Salesforce platform. The aim is to create more of the content that is shown to be effective at generating positive engagement. In the past, the process of creating this content was carried out by humans; however, the company has been actively looking at developing automated systems that will create adverts and social content informed by social data.

It also uses image recognition technology to target users who share pictures on social media inferring that they could be potential customers. In one example of this strategy in action, Coca-Cola targeted adverts for its Gold Peak brand of iced tea at those who posted images that suggested they enjoy iced tea, or in which the image recognition algorithms spotted logos of competing brands. Once the algorithms determined that specific individuals were likely to be fans of iced tea, and active social media users who shared images with their friends, the company knows that targeting these users with adverts is likely to be an efficient use of their advertising revenue.

For purchase verification, off-the-shelf image recognition technology proved to be insufficient for reading the low-resolution dot matrix printing used to stamp product codes onto packaging. So, Coca-Cola worked to develop its own image recognition solution using Google’s TensorFlow technology. This used convolutional neural networks to enable machine recognition of codes that could often appear differently depending on when and where they were printed.

What Were The Results?

Analysis of the data from vending machines by AI algorithms allows Coca-Cola to more accurately understand how the buying habits of its billions of customers varies across the globe.

It uses this to inform new product decisions – for example, the decision to launch Cherry Sprite as a bottled product in the United States was taken because the data showed that this was likely to be a winning initiative.

Computer vision analysis and natural language processing of social media posts, as well as deep learning-driven analysis of social engagement metrics, allows Coca-Cola to produce social advertising that is more likely to resonate with customers and drive sales of its products.

Applying TensorFlow to create convolutional neural networks enabled scanners to recognise product codes from a simple photograph, increasing customer engagement with Coca-Cola’s different loyalty programs around the world.

Key Challenges, Learning Points And Takeaways

• If you sell hundreds of different products across multiple countries, perceptions and customer behaviour can vary greatly from market to market. Understanding these differences helps tailor specific messages for different markets, rather than relying on a one-size-fits-all approach
• When you’re dealing with global brands, user data from social media or generated through your own systems (such as vending machines) is vast and messy. AI provides a viable method of structuring this data and drawing out insights
• Computer vision technology such as image recognition tools can analyse millions of social media images to help a brand understand when, how and by whom its products are enjoyed
• As well as making marketing decisions, brands that are fully invested in AI are beginning to use it for designing new products and services

This is an edited extract from Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems, by Bernard Marr, with Matt Ward (published by Wiley, April 2019).

About the authors: Bernard Marr is the founder and CEO of Bernard Marr & Co and an internationally best-selling business author, futurist, keynote speaker and strategic advisor to companies and governments. He is one of the world’s most highly respected voices and a renowned expert when it comes to topics such as artificial intelligence and big data. Marr advises many of the world’s best-known organisations on strategy, digital transformation and business performance. He is the author of Big Data in Practice: How 45 Successful Companies used Big Data Analytics to Deliver Extraordinary Results and Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance, both published with Wiley.

Matt Ward is the research lead for Bernard Marr & Co. Matt has a background in investigative journalism and spent the last few years working closely with Bernard Marr on the latest technology topics. Matt is an expert and experienced writer in the field of business technology and artificial intelligence, where he has worked with companies such as IBM, Intel, Citibank and NASA.

 Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, , and Cyber Security & .

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Pepper will be attempting to explain topics such as AI and robotics to The Commons Education Select Committee.

“If we’ve got the march of the robots, we perhaps need the march of the robots to our select committee to give evidence,” Committee chair Robert Halfon told Tes.

“The fourth industrial revolution is possibly the most important challenge facing our nation over the next 10, 20, to 30 years.”

AI and robotics will drastically change our societies, and not always for the better. There will be serious challenges ahead.

It’s rare to hear of AI being discussed without the potential impact on jobs. Low-skilled workers, in particular, are most threatened by automation replacement.

The Select Committee will be looking to understand what impacts the fourth industrial revolution will have and how the negatives can be reduced. They’re hoping Pepper can help, though it all feels somewhat a gimmick.

“This is not about someone bringing an electronic toy robot and doing a demonstration,” said Mr Halfon. “It’s about showing the potential of robotics and artificial intelligence and the impact it has on skills.”

Pepper is equipped with four microphones, two HD cameras, and a touchscreen on its chest for displaying information when needed.

We caught up with Pepper at MWC earlier this year:

Fortunately, Pepper is experienced with public speaking after featuring on stages around the world. The robot could perhaps even offer advice to some leading tech company CEOs on coming across more human.

 Interested in hearing industry leaders discuss subjects like this? Attend the co-located AI & , and >

(Image Credit: Pepper at Opening Ceremony of the 28th Tokyo International Film Festival by Dick Thomas Johnson under CC BY 2.0)

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Irakli started with a positive note that’s easily forgotten: never has the world been more safe, connected, and prosperous.

“We have developed technologies which have the potential to solve problems we never thought were possible,” says Beridze. “Most of them are related to the UN’s sustainable development goals.”

World-Changing Benefits

A look at the statistics provides evidence of a huge reduction in those dying from violence or living in extreme poverty. Many of the greatest threats we face today are shared challenges such as climate change, disease, and dwindling resources.

AI is a powerful tool which can help with all these challenges and more if we, as humankind, choose to use it this way. Alternatively, it could pose an existential threat.

Here are just some of the ways Beridze expects AI to aid the UN towards its goals:

Beridze dives deeper into some other potential benefits of AI to societies. A couple of the most interesting suggestions are its use to improve health and wellbeing, and to maintain peace, justice, and strong institutions.

Starting with health, Beridze highlights the use of AI to analyse large quantities of healthcare data in order to make scientific breakthroughs. Furthermore, it could be used to predict and project disease outbreaks to reduce mortality rates.

The impact of AI on healthcare is among our most covered subjects here on AI News. There are exciting developments on a near-daily basis.

Next up is the potential for AI when it comes to peace, law, and governance. Beridze believes AI can be integrated within an ‘e-government’ to reduce discrimination, prejudice, and corruption.

AI currently has a well-documented bias problem. However, solutions are becoming available to ensure the algorithms behind AIs are fair and do not favour any part of society over another. It’s ultimately easier to make a machine less discriminate than a person.

Global powers are seeking to establish themselves as leaders in AI. China and the US continue to be dominant by pumping billions of cash into developments, while smaller economies are playing to their own strengths.

Countries such as Japan are strong in fields such as robotics. The EU has the highest number of service robot manufacturing. Meanwhile, the UK is known for its leadership in ethics and strong academic attributes with leading universities.

There’s a now famous quote from Russian President Vladimir Putin speaking about AI which said: “Whoever becomes the leader in this sphere will become the ruler of the world.”

Putin’s quote was received in many ways. Some believe it was simply a matter of fact, while others saw it as confirmation of a potentially reckless race between world powers to become a leader.

AI-as-a-Threat

Regardless of what states do, criminals will seek to exploit AI for their own gain. This could take many forms, but one clear example is that of impersonation.

During Google’s I/O conference this year, the company showed off its Duplex demo where an AI assistant called a hair salon on a user’s behalf and was convincing enough to pass for a human. By training such a system with someone else’s voice, fraud could be completely automated.

Beridze will be meeting with Interpol next month to discuss the new risks posed by criminals using artificial intelligence, and how law enforcement agencies can work to counter them.

“When talking about the good sides of AI, we should never forget about the possible risks,” warns Beridze. “One of the biggest risks is the pace of development with how quickly it’s being developed and how fast we can adapt to that.”

One major concern is the potential impact on jobs. Low-wage workers are particularly threatened by automation.

“We don’t really have any solutions,” Beridze says. “We have some ideas that have been put on the table such as; Universal Basic Income, retraining of the population, some even say to slow down the pace of innovation.”

Other concerns highlighted by Beridze includes automated weapons, superintelligent systems like SkyNet famously depicted in the Terminator movies, and using things such as bots to influence democratic processes.

Solving International Verification

One of the most interesting uses for AI is for the verification of incidents where nations do not trust each other. This has perhaps been seen most often between Western nations and Russia where there’s still a clear level of distrust.

Take the recent chemical attack in Salisbury, UK on a former spy and his daughter. Western nations agreed it could only have been carried out by Russia. For its part, Russia denies the allegations and claims to have been locked out of seeing any evidence.

Beridze served as a special projects officer at the OPCW (Organisation for the Prohibition of Chemical Weapons) prior to joining UNICRI.

The OPCW is an independent organisation working alongside the United Nations that investigates chemical attacks. Members of OPCW represent around 98 percent of the global population.

Until a ruling last week, the OPCW was prohibited from assigning blame for a chemical attack. In Salisbury, the organisation stated it agreed with the UK’s findings the nerve agent of the kind first developed by the Soviet Union.

There have also been multiple chemical attacks in Syria. One particularly devastating attack in Douma was to be investigated by the OPCW but investigators claim they were blocked from accessing the site by Syria and its Russian allies.

Investigators were eventually provided access over a week after. However, Chlorine – at least one of the suspected chemicals used – is notoriously difficult to detect even a day after because of its gaseous state.

Russia and Syria both reject claims that chemical weapons were used. Moscow has offered several narratives on Douma, claiming simultaneously that there never was an attack and that it was the work of rebels in the area.

France said it was likely the evidence is gone, and the USA accused Russia and Syria of tampering with the site.

When everyone is pointing the finger at each other, there needs to be independent verification. Whenever people are involved there’s nearly always some accusations of foul play.

A provably unbiased, open-source AI which examines the evidence could be the answer.

“The time has come where we should employ technologies like AI and blockchain to start verification of issues where countries do not trust each other,” says Beridze. “We need to make a major leap from a system created in the [19]40s, to 80 years down the road where we live in a completely different world.”

Beridze’s session highlighted both the near-limitless potential for AI to have a positive impact on the world, or it could just as easily be devastating.

One thing is for sure, AI will transform our world. For better or worse, that’s up to all of us.

You can watch our interview with Irakli Beridze below:

Find out more about AI Expo and the next event here.

What impact do you think AI will have on the world?

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The new startup, Landing.ai, chose this industry to begin with as “it is through manufacturing that human creativity goes beyond pixels on a display to become physical objects. By bringing AI to manufacturing, we will deliver a digital transformation to the physical world.”

Ng believes AI technology is well suited to addressing the challenges facing manufacturing — such as variable quality and yield, inflexible production line design, inability to manage capacity, and rising production costs.

Landing.ai is partnering with one of the world’s most well known manufacturers, Foxconn, on the project. Many in the tech sphere will know Foxconn as the chosen manufacturer of Apple for many of their products.

Together, the companies say they are developing AI technologies, talent, and systems that build on the core competencies of both companies.

Ng believes AI will “revitalise” manufacturing jobs in the US and globally. Rather than replace jobs, he believes the next wave of manufacturing jobs will pay higher but also require new skills — therefore large-scale training or retraining will be required.

Back in September, we reported on research from Capgemini showing that — despite popular opinion — AI is creating new jobs.

Are you looking forward to seeing what Landing.ai can achieve?

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