Machine-to-machine (M2M) learning is an integral apart of the expanding world of Industrial IoT. Over the past few months we have given attention to manufacturing and its current digital disruption, but have failed to show the direct impact smart M2M and IoT technology is having on the industry. So, this week we are diving deeper into the term machine learning and how it connects to manufacturing both today and in the future. Before we get to our news round up let's start by re-defining M2M, to ensure we are all on the same page with its purpose and meaning. Gartner has defined machine-2-machine communications as "something used for automated data transmission and measurement between mechanical or electronic devices."

The composition of the C-suite is changing to take better advantage of data. Data-savvy executives are replacing their traditional counterparts, new roles are being created, and leaders generally are finding themselves under pressure to understand the value and impact of data, analytics, and machine learning. "As the C-suite becomes increasingly filled with analytical minds and more data scientists are hired, a cultural shift naturally takes place. Some of the new, fast-growing executive roles [include] chief data scientist, chief marketing technology officer, [and] chief digital officer. All are aligned with the growing demand and anticipation for AI," said David O'Flanagan, CEO and cofounder of cloud platform provider Boxever.

Nvidia's microprocessors have long been the chips of choice for computer game addicts who crave realistic graphics as they chase aliens or battle enemy soldiers. The same powerful semiconductors are now being put to new uses at companies including Alibaba, Facebook, Google, and Microsoft. Nvidia's graphics chips underpin speech recognition systems, software to develop gene therapies, and programs that transform satellite photos into detailed maps. Researchers at DeepMind, a Google-owned lab in London, harnessed thousands of Nvidia's K40 graphics processors, which cost 3,000 apiece, to train a computer to play Go, an ancient board game. In what was praised as a milestone in artificial intelligence, DeepMind's machine beat a European Go champion in five out of five matches last year.

In just five years, every important decision made by businesses will be aided by cognitive systems that understand, learn and augment our decision making, according to IBM's chairman and CEO, Ginni Rometty. Speaking at the vendor's Thinkforum in Sydney on Tuesday, Rometty proclaimed the world is on the cusp of the next disruptive wave of technology driven by cognitive platforms that can take massive stores of data within an organisation and turn it into competitive advantage. "Regardless of role, every industry will be disrupted," she told attendees. "Every industry has its Uber or Tesla, and many people say they are going to be a technology company of some kind. An important question is: When everyone is digital, who wins? "Digital for all has to be the foundation, but it's not the destination.

Trying to think of a practical, real world use of Machine Learning? Bank and financial institutions have regulatory requirements to monitor account activity for money laundering activities. Regulators around the world take these monitoring and reporting requirements very seriously. However, the big challenge facing anti-money laundering (AML) efforts is that money laundering rarely appears in the activity of a single person, business, account, or a transaction. Money launderers have gotten quite sophisticated.

Financial institutions have a regulatory requirement to monitor account activity for anti-money laundering (AML). Regulators take the monitoring and reporting requirements very seriously as evidenced by a recent set of FinCEN fines. One challenge with AML is that it rarely manifests as the activity of a single person, business, account, or a transaction. Therefore detection requires behavioral pattern analysis of transactions occurring over time and involving a set of (not obviously) related real-world entities. For large transactions, banks file Currency Transaction Reports (CTR) that are used by FinCEN for processing and analysis.

Below is what happened in search today, as reported on Search Engine Land and from other places across the web. Can machine learning be applied to your PPC accounts to make them more efficient? Columnist David Fothergill describes how he utilized machine learning to find new keywords for his campaigns. Inadvertently ruining your newly redesigned website's SEO can be a nightmare. Columnist Will Scott explains four mistakes you must avoid before you launch.

A few months ago I tried out an augmented reality program by ModiFace that lets you try on makeup live -- you can tilt your head, make a funny face, even angle the camera for better light, and the makeup moves with you. It isn't perfect, but it's neat, and I shared it around to my friends. So when I heard that Facebook was now supporting a Modiface app to let you try out lipstick through Facebook Messenger, I was there! I quickly opened Messenger and plugged the app into my conversations. The bot appeared right away, and it seemed promising.

Talking to WIRED before his speech at WIRED Health, Kyu Rhee, IBM's chief health officer, took from his pocket one of the iconic pieces of medical equipment: the stethoscope. The stethoscope is celebrating its 200th anniversary – the first, monaural version was created by the French doctor René Laennec. Despite technical advances – and the rise of other non-invasive techniques for internal examination – the stethoscope still means "doctor": according to a 2012 research paper, carrying a stethoscope makes a practitioner seem more trustworthy than any other piece of medical equipment. "It's amazing how medicine in some ways still leverages this piece of technology," said Rhee. "But I believe that in the next 200 years a cognitive system like Watson will be a part of every healthcare decision, for every stakeholder." IBM Watson's cognitive approach to computing absorbs data – structured and unstructured – and produces answers.

Artificial intelligence is still surrounded by an aura of mystery, and it would be tough to find a better illustration than the story in the news last week about a British grandmother who includes "please" and "thank you" in all her Google searches. "Please translate these roman numerals mcmxcviii thank you," read the search request from May Ashworth that ultimately went viral when her grandson tweeted it on Twitter. "I thought, well somebody's put it in, so you're thanking them," Ashworth reportedly explained. "I don't know how it works, to be honest. It's an endearing tale that drew notice from Google itself, but it also underscores the way AI, in particular, has been something of a black box.