The clear answer is NO as the conversion rates are 3-5% and there is 70% shopping cart abandonment rates. So, how do we solve this problem?

Responses to a White House request for information about the future of artificial intelligence show a continued divide between those who are ready to embrace intelligent machines and those who worry about a future in which robots run the world. The responses were made public this month after the White House Office of Science and Technology issued a call for input about how artificial intelligence technology is currently shaping the world, how AI is likely to develop in the future and what role the government should play in either encouraging or regulating development. The request for information drew responses from large corporations, such as IBM, Google and Microsoft, as well as from academia and private citizens. The responses show there still is little agreement about the future of AI. "The danger is not machines run amok, as suggested by some, like [Elon] Musk or [Stephen] Hawking (who know nothing about AI). The danger is, like nuclear weapons, what AI will allow us to do to ourselves. And it is not a remote possibility, but already happening: Uber, for example, is proposing a fleet of driverless cars. What happens when the profits associated with whole industries are not distributed across the whole world, but flow into the coffers of a single company or person?"

Dataiku DSS 3.1 introduces new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to their data science projects without having to write a line of code. The blending of visual code-free and free-form code-based transformations is one of the main strengths of Dataiku DSS for the prototyping and production of data applications. In addition to Python, R, SQL, Hive, Impala, and Pig, Dataiku DSS 3.1 now enables Apache Spark users to write transformations and interactive notebooks in Scala, bringing the power of Spark's native and most performant language to data analysts using Dataiku DSS.

This article is part of an MIT SMR initiative exploring how technology is reshaping the practice of management. Smart machines need ethics, too: Remember that movie in which a computer asked an impossibly young Matthew Broderick, "Shall we play a game?" Four decades later, it turns out that global thermonuclear war may be the least likely of a slew of ethical dilemmas associated with smart machines -- dilemmas with which we are only just beginning to grapple. The worrisome lack of a code of ethics for smart machines has not been lost on Alphabet, Amazon, Facebook, IBM, and Microsoft, according to a report by John Markoff in The New York Times. The five tech giants (if you buy Mark Zuckerberg's contention that he isn't running a media company) have formed an industry partnership to develop and adopt ethical standards for artificial intelligence -- an effort that Markoff infers is motivated as much to head off government regulation as to safeguard the world from black-hearted machines. On the other hand, the first of a century's worth of quinquennial reports from Stanford's One Hundred Year Study on Artificial Intelligence (AI100) throws the ethical ball into the government's court.

With every new technology and paradigm, there are a lot of misconceptions, but I'll try to set the record straight about the most common ones concerning bots. Wrong, most bots do not currently use AI, a lot of them will never need to use AI. Some bots use Natural Language Processing/Understanding to map what the user is saying to the bot to an actual intent. For example, there are many ways to say you want to book a ticket to a movie -- "I wanna book a ticket for later this evening", "I want to go to the movies tonight", "book me a ticket to a movie after 8pm"- all of these mean more or less the same, but for a developer it is quite hard to map these into an intent to book a ticket this evening. That is the most common use of AI today in bots, this is not what most people think about when they say artificial intelligence.

In order to compete with new digitally savvy competitors, retail banks must be agile and single-minded about putting the customer first. The truth is, most banks are not there yet; however, their customers are. Seventy-nine percent of customers say their banking relationships are merely transactional, according to the 2016 Accenture North America Consumer Digital Banking Survey. That is simply not good enough. Retail banks need to make themselves integral to their customers' lives.

To create a desirable future where humans and conscious machines are at peace with one another, treating our AI with respect may be a crucial factor in preventing the apocalypse Elon Musk, Stephen Hawking and Bill Gates fear. Like basic human rights, AI rights may include the right to liberty, freedom of expression, and equality before the law. But how will AI rights be different from human rights? The AI rights revolution may be contingent on intelligent machines being conscious, with the capacity to feel that they exist and consequently feel pleasure and pain.

In 2014 Google bought a UK-based artificial intelligence research lab called DeepMind for a hefty 530 million. Since then, DeepMind has made rapid progress in AI technologies, including health and gaming applications. The latest achievement of DeepMind is WaveNet, an AI computer program that can almost mimic the way humans speak. Experts say that WaveNet has "halved" the gap between machine-speak and a natural human voice. So what we're talking about here is more like Jarvis from Iron Man than Arnold Schwarzenegger in Terminator – or any of his other movies, for that matter!

Innovative technology in the retail world doesn't always mean flashy gadgets. In fact, most of the industry's most effective form of digital disruption is invisible. Machine learning technology continues to further integrate with consumers' daily lives, with new offerings such as Apple's personalized App Store or Amazon price optimization tools. These platforms are seamlessly providing a personalized online experience through algorithms that are invisible to the average user. Think about how Facebook, Netflix, Amazon and Google make smart inferences and recommendations for the consumer.