Ten years ago, the most forward-thinking companies were just starting to dive into the potential of data and analytics. Since then, brands have moved from using analytics to answer what customers are doing to exploring the how and why, and also to figure out what they will do in the future. The Wharton Customer Analytics Initiative (WCAI) is celebrating its 10th anniversary this year and has seen every step of that evolution. Knowledge@Wharton recently sat down with Wharton marketing professors Eric Bradlow, Peter Fader and Raghuram Iyengar to discuss how the field has developed over time, and what they expect to be the key trends over the next decade. Bradlow and Fader are the founding directors of WCAI, and Bradlow and Iyengar are the current co-directors. An edited transcript of the conversation follows. Knowledge@Wharton: When WCAI launched ten years ago, what was the environment like in the field of analytics? What were some of the initiative's key goals? Peter Fader: Even though the initiative started 10 years ago, the idea started about a decade before that.

Do plants have a mind? "My work is not about metaphors at all," says Monica Gagliano. "When I talk about learning, I mean learning. When I talk about memory, I mean memory." Gagliano, an evolutionary ecologist, is talking about plants. She's adopted methods from behavioral experiments used to test animal intelligence and found that plants respond in a similar manner. The results of her research suggest plants might possess intelligence, memory and learning, although the mechanisms at play may be fundamentally different from those of humans and animals. Her book "Thus Spoke the Plant" will be out this fall. She's received equal amounts of attention and criticism from colleagues and the media. Her work was introduced to the public in an in-depth primer on plant intelligence that came out in The New Yorker in 2013 called, Intelligent Plant.

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Today my guest on Singularity 1 on 1 is Vernor Vinge -- the very person who coined the technological singularity as a term. Currently Vernor Vinge is putting the final touches on the sequel to A Fire Upon the Deep. The new book is titled The Children of the Sky and is already available for pre-order on Amazon, though it is not expected to ship until October 2011. Despite his busy schedule Prof. Vinge still managed to give us over an hour of his time and during our conversation I ask him to discuss issues such as: his childhood and early interest in science fiction; his desire to make sense of the universe; his definition of the technological singularity and the story behind the term; his now classic 1993 NASA paper; his favorite science fiction books and authors; major milestones on the way towards the singularity and our chances to survive such an unprecedented event. As always you can listen to or download the audio file above or scroll down and watch the video interview in full.

In an interview with Bloomberg, Accenture's charismatic CEO, Pierre Nanterme, was asked what the companies'big bets' currently are, and his answer was very clear – Artificial Intelligence (AI). Everywhere I look, and everything I read about the next frontier in digital points towards AI. The big consultancies are building infrastructure to deliver this, organisations like Facebook and Amazon are already using AI and are planning big things for the technology in the future. But, are we, as customers ready for the next wave of innovation? Artificial Intelligence is no longer Sci-Fi, it has arrived and is developing fast – huge advances in the development of natural language processing, cognitive computing and machine learning have ensured this.

Recent statistics about the global chatbot market are encouraging for businesses: global monthly active users on the four top messaging apps topped that of the four top social networks in 2015 and continues to do so. The market is expect to reach $1.23 billion by 2025! Like any marketing tool, a chatbot is a great opportunity to add value to customer interactions. While it's easy (and exciting) to get caught up with developing cool new functions or adding useful integrations to your next bot, you should first establish an important foundation by asking yourself: "What persona should this chatbot have?" Experienced online marketers are familiar with "buyer personas" and "user personas" -- strategic tools that help businesses identify their ideal customer (buyer) or end user.

Machines are getting better and better at analyzing complex health data to help physicians better understand their patients' future needs. In a study out today in Nature Digital Medicine, an advanced algorithm evaluated de-identified electronic health records of more than 216,000 adult patient hospitalizations to predict unexpected readmissions, long hospital stays, and in-hospital deaths more accurately than previous approaches. I caught up with one of the authors, Nigam Shah, MBBS, PhD, an associate professor at Stanford, to learn about the new study and discuss the implications for artificial intelligence in medicine. What is deep learning and how does it fit in the larger universe of artificial intelligence? Deep learning is one of several machine learning techniques that can be used to build intelligent systems.

In January 2018, I entered a Kaggle competition called the Mercari Price Suggestion. The competition lasted three months and ended a few weeks ago. The challenge was to build an algorithm that automatically suggests product prices to online sellers, based on free-text descriptions, product categories and a few other attributes. I joined the competition a month before it ended, eager to explore how to use Deep Natural Language Processing (NLP) techniques for this problem.Those four weeks competing were a sequence of curiosity, engagement, and excitement. I ended up with a single end-to-end Deep Learning model (no ensembles) implemented in Tensorflow, which landed me in the the 35th position (out of 2,384 teams) in the Private Leaderboard.

Currently co-founder and CTO at Nudge.ai, which uses artificial intelligence to help salespeople find useful trigger events at their target accounts. Letting AI do the heavy burden of research allows sales professionals to focus on selling, while never missing a chance to turn latent demand into active demand. Prior to that, co-founder and CTO of Eloqua, a company I helped guide to a market-leading position in marketing automation, while growing it to a $100 million revenue run rate, through its IPO on the NASDAQ, and to ultimate acquisition by Oracle. Tell me about your early career. It may seem strange considering that Nudge.ai is not my first software startup, but I'm not even originally a software guy.

Many businesses are deploying Big Data applications for competitive advantage, yet many of these businesses are "learning on the job," using trial and error to do the best they can, with mixed results. To provide guidance, I spoke with two leading practitioners of data science discuss how this rapidly evolving technology is used in business today. S. Clark: I think one of the biggest challenges toward that cultural gap is just around trust. Human beings trust each other, and developing trust between two people has a sort of defined process. Usually, it just takes time. It takes many examples of someone saying they're going to do something and then doing it.