Tonight, Scots will feast on haggis, neeps and tatties to celebrate the birthday of Robert Burns, the 18th century Scottish poet. Ever since his 1786 poem, 'Address to a Haggis', the savoury pudding has been memorialised as Scotland's national dish. However, according to an artificial intelligence chatbot, this cultural icon may not be what it seems. Bard, Google's free AI tool, claims the dish – made of offal, oats and spices – has its'historical roots in English culinary traditions'. It admits that haggis'plays a central role in traditional Scottish celebrations like Burns Night and Hogmanay', but it has a'complex and interconnected history'.

The FTC, fresh off announcing a whole new division taking on "snake oil" in tech, has sent another shot across the bows of the over-eager industry with a sassy warning to "keep your AI claims in check." I wrote a little while ago (okay, five years) that "AI Powered" is the meaningless tech equivalent of "all natural," but it has progressed beyond cheeky. It seems like just about every product out there claims to implement AI in some way or another, yet few go into detail -- and fewer still can tell you exactly it works and why. Whatever someone means when they say "powered by artificial intelligence" or some version thereof, "One thing is for sure: it's a marketing term," the agency writes. "And at the FTC, one thing we know about hot marketing terms is that some advertisers won't be able to stop themselves from overusing and abusing them."

Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Almost every confidential investment memorandum (CIM) for a tech-driven enterprise includes the company's mention of artificial intelligence (AI) or machine learning (ML) capabilities. But as with other investment buzzwords -- such as "subscription revenue" -- there is a tendency to use AI or ML to suggest complex, business-enabling, proprietary technology and processes to distinguish the offering as differentiated or technologically superior. This is often to garner higher valuation. We've all heard examples of AI failures that make for good headlines and provide interesting cautionary tales.

From the perspective of technology companies, one of the greatest challenges to developing cutting edge technology is ensuring that the innovation budget receives significant recognition among users, regulators and other stakeholders. Receiving recognition sometimes means publishing papers in peer-reviewed magazines, presenting in conferences and preparing press releases that showcase the advancements in technology. Though companies can sometimes grow to be very "optimistic" of perceived progress, some claims of progress lack the necessary proofs to ensure that developments are relevant. While AI potential applications can be varied and diverse, making sure that a system is sound, scalable, uses available datasets and can perform in a real-world environment is a daunting task. Sometimes the proposed approaches fail in their methodology as the data is simply not available to support industrialisation of the system; or, the system is not safe and confidentiality concerns remain about how the data will be used.

A team of engineering researchers from the University of Toronto has created an algorithm to dynamically disrupt facial recognition systems. Led by professor Parham Aarabi and graduate student Avishek Bose, the team used a deep learning technique called "adversarial training", which pits two artificial intelligence algorithms against each other. Aarabi and Bose designed a set of two neural networks, the first one identifies faces and the other works on disrupting the facial recognition task of the first. The two constantly battle and learn from each other, setting up an ongoing AI arms race. "The disruptive AI can'attack' what the neural net for the face detection is looking for," Bose said in an interview.

These days, marketers can't read about their profession without getting bombarded with wild claims about how AI is going to disrupt everything they do. And with the sales and marketing functions evolving so rapidly in recent years, marketers in particular must embrace an entrepreneurial spirit and constantly explore new technologies in order to give their team a competitive edge. That mindset shift, along with new consumer trends -- such as self-driving cars and intelligent voice-first products like Amazon's Alexa and Apple's Siri -- are bringing the possibilities of AI to the forefront of business-to-business marketing technology discussions. But all of this begs the question, "Which AI claims are hype and which are reality?" In order to know what a new technology like AI can bring to the table, it's important to fully understand the problems you're trying to solve.

These days, marketers can't read about their profession without getting bombarded with wild claims about how AI is going to disrupt everything they do. And with the sales and marketing functions evolving so rapidly in recent years, marketers in particular must embrace an entrepreneurial spirit and constantly explore new technologies in order to give their team a competitive edge. That mindset shift, along with new consumer trends--such as self-driving cars and intelligent voice-first products like Amazon's Alexa and Apple's Siri--are bringing the possibilities of AI to the forefront of business-to-business marketing technology discussions. But all of this begs the question, "Which AI claims are hype and which are reality?" In order to know what a new technology like AI can bring to the table, it's important to fully understand the problems you're trying to solve.