Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Since the first artificial intelligence (AI) program was written in 1951, researchers and technology professionals have worked tirelessly to develop highly sophisticated AI programs. One of the early pioneers of this type of technology was Alan Turing, an English mathematician and computer scientist. Turing understood that as humans, we combine information that is available to us with reason to make decisions.

MarketInsightsReports has published a report entitled Global Artificial Intelligence (AI) Verticals Market Research Report 2019 that is a detailed observation of several aspects, including the rate of growth, technological advances and various strategies implemented by the main current market players. The report is based on a collective analysis of data, which is obtained through primary and secondary research. It provides a systematic approach to the current and prospective scenario of this market. Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.

What goes into making plants taste good? For scientists in MIT's Media Lab, it takes a combination of botany, machine-learning algorithms, and some good old-fashioned chemistry. Using all of the above, researchers in the Media Lab's Open Agriculture Initiative report that they have created basil plants that are likely more delicious than any you have ever tasted. No genetic modification is involved: The researchers used computer algorithms to determine the optimal growing conditions to maximize the concentration of flavorful molecules known as volatile compounds. But that is just the beginning for the new field of "cyber agriculture," says Caleb Harper, a principal research scientist in MIT's Media Lab and director of the OpenAg group.

Today's artificial intelligence market is not easy to quantify. Besides the lack of consensus on a coherent definition for "artificial intelligence" as a term, the field's nascent stage of development makes it difficult to carve out silos or hard barriers of where one industry or application ends, and another begins. In one of our more popular recent articles, we aimed to derive a valuation of the artificial intelligence market, based on current market research and our own insights. In this week's article, I've set out to determine more of a "lay of the land" of the AI industry, including it's various segments and application areas. If you're interested in how developments in machine learning and AI might impact your own company or business, then keeping an eye on trends of industry and application growth is pertinent; we hope that this article will be a good jumping off point to some of the most thought-out assessments of AI and it's "segments" as we could collate from the web.

Sentient also released a new solution to AB testing called Sentient Ascend. Right now, the conversion rate optimization, CRO, industry, is based on AB testing, where you test a new design against an old design. "We decided we could transform this industry by completely dissolving the concept of AB testing, by thinking of the website no longer being a static property, but a dynamic property that is always evolving based on the way it interacts with your audience. We wanted to enable the marketer to make changes to quickly see market and conversion rate improvements. Our solution points to the fallacy of AB testing, where you come with a defined preconception of what to test against. We want to open the floodgates and show people that they don't have to limit themselves to a test. The number of possible combinations is so large that it's impossible to explore the surface exhaustively or comprehensively, except with an intelligent system that learns from every interaction, and understands from that learning what matters, what doesn't, and progressively builds solutions," says Blondeau.

It sounds absurd to think artificial intelligence could be used to generate a more human-like customer experience. But that's exactly how it's now being used. AI analyses huge amounts of behavioural and emotional data in a bid to communicate with us and deliver brand experiences that are more personalised and predictive. When Unilever turns to an AI bot to boost Lipton tea sales, GlaxoSmithKline uses machine-learning to dispense flu advice through interactive ads and Dutch airline KLM trials machine-learning in its social media chatbot for flyers, you know times are a changing. "AI is offering retailers new ways to make shopping hassle free. Modern cognitive systems can understand, reason, learn and interact in similar ways to a human being. This is a very fast-moving area," says Tony Maile, European retail leader at IBM Cognitive Solutions.

Today's artificial intelligence industry is not easy to quantify. Besides the lack of consensus on a coherent definition for "artificial intelligence" as a term, the field's nascent stage of development makes it difficult to carve out silos or hard barriers of where one industry or application ends, and another begins. In one of our more popular recent articles, we aimed to derive a valuation of the artificial intelligence market, based on current market research and our own insights. In this week's article, I've set out to determine more of a "lay of the land" of the AI industry, including it's various segments and application areas. If you're interested in how developments in machine learning and AI might impact your own company or business, then keeping an eye on trends in industry and application growth is pertinent.

Virtual personal assistants have become another self-fulfilling prophecy of technology. When Tony Stark talks to Jarvis in Iron Man, we want that level of interaction in real life, and making that happen becomes the area of study for hundreds of software developers and researchers (including, recently, Mark Zuckerberg). These virtual assistants are going to be a large part of the future mobile phones, whether you like them or not. All major mobile operating systems have a digital personality baked into their software -- Apple's Siri, Microsoft's Cortana, and Google Now -- and they all generally do the same thing. Siri, Google Now, and Cortana can all schedule appointments, set reminders, look things up on the internet, and few other simple tasks.

It's the premise of many science fiction novels and movies: Super-intelligent robot machines that can outsmart humans, if not terminate them entirely. But the prospect doesn't exactly frighten some of today's experts in the field. "It's a distraction," said Nigel Duffy, chief technology officer at AI software maker Sentient Technologies. More pressing issues, he said, revolve around the role algorithms play online in determining whether people are allowed to get a mortgage, or establish a line of credit. His remarks were echoed by others in the industry, during a panel discussion on Wednesday at an event in Silicon Valley focused on artificial intelligence.

If online retailers want to make more sales and retain customers, they better stop making those clients do all the leg work. Randy Dean, chief business officer at Sentient Technologies, urged the audience at WIRED Retail to stop expecting customers to use outdated interfaces that are essentially databases asking users to search, browse and narrow the field by selecting multiple options. Our internet connections have become infinitely faster over the past decade, yet retailers still expect customer behaviour to remain the same. "We need to change the way people interact with our products. We have to get rid of the filtering systems and search boxes, and let the products speak for themselves."