Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. In her Day 2 Keynote at 17th Cloud Expo, Sandy Carter, IBM General Manager Cloud Ecosystem and Developers, and a Social Business Evangelist, discussed why this matters, how innovation will benefit, and how to foster an interest in tech. Learn why women need to take risks and embrace failure to give them the courage to crash through the glass ceiling. Sandy will share some of her own experiences and advice with five career hacks to help women get ahead, because talent is not enough.

I often get asked on how to get started with Machine Learning. Most of the time, people have troubles understanding the maths behind all things. And I have to admit, I don't like the maths either. Math is an abstract way of describing things. And I think the way machine learning is described is too abstract to understand it easily. I probably try to describe things with foo code or a bit of JS to explain what I'm talking about.

At Dreamforce, Artificial Intelligence or "AI" was the buzzword of the year. We saw the launch of Salesforce Einstein and many other companies refining their messaging towards how AI will transform sales, marketing, and even customer success process. The vision behind this is bold and Einstein, if it delivers, will transform how people engage with customers. Yet I'm concerned about the viability of these products at scale: most CRM and marketing automation data isn't high quality enough to deliver on the promises of AI. We're all focused on how to make our applications smarter, but few, if any companies, have data governance policies with regards to how sales reps input data or how marketers capture inbound customer data.

A new algorithm can visually discern malignant skin lesions from less dangerous ones. A team from the Stanford Artificial Intelligence Laboratory set up a machine-learning AI to teach itself to diagnose cancer by looking at skin lesions just as a doctor would during an exam. The team tested the algorithm against 21 board-certified dermatologists, and it performed just as well as its human counterparts. "We realized it was feasible, not just to do something well, but as well as a human dermatologist," Sebastian Thrun, an adjunct professor in the Stanford Artificial Intelligence Laboratory, said in a statement. "That's when our thinking changed. That's when we said, 'Look, this is not just a class project for students, this is an opportunity to do something great for humanity.'"

Artificially intelligent computer systems are now able to recognise skin cancer just as well as human scientists, according to a new report. Researchers from Stanford University used the internet to gather 130,000 pictures of skin lesions, representing over 2,000 different diseases. They then used these pictures to train an artificial intelligence algorithm - originally developed by Google to differentiate between cats and dogs - to tell the difference between cancerous and non-cancerous lesions. After training the algorithm, they tested it on 370 high-quality, biopsy-confirmed images, and compared its responses with those of 21 professional dermatologists. In its diagnoses of the skin lesions, which represented the most common and deadliest skin cancers, the algorithm matched the performance of the dermatologists.

The smart parking industry continues to evolve as an increasing number of cities struggle with traffic congestion and inadequate parking availability. While the deployment of sensor technologies continues to be core to the development of smart parking, a wide variety of other technology innovations are also enabling more adaptable systems--including cameras, wireless communications, data analytics, induction loops, smart parking meters, and advanced algorithms. The future of the smart parking market is expected to be significantly influenced by the arrival of automated vehicles (AVs). Several cities around the world are already beginning to trial self-parking vehicles, specialized AV parking lots, and robotic parking valets. For example, in Boulder, Colorado, ParkPlus is working on deploying the first fully automated parking garage in the Western United States through Boulder's PearlWest mixed-use development.

In AI, is data more important than algorithms? In AI, is data more important than algorithms? I hope you are not expecting a simple black or white answer to this question. Whether data or algorithms are more important has been debated at length by experts (and non-experts) in the last few years and the short version is that it depends on many details and nuances that take some time to understand. I answered a pretty similar question some time ago in this Quora post: In machine learning, is more data always better than better algorithms?

Connected cars made big news at the Consumer Electronics Show in Las Vegas this month. It's not surprising with this year's buildup of buzz surrounding autonomous and connected vehicles, and the ecosystem of technology that is feeding them. Gartner forecasts 21 million new automobiles will be equipped with data connectivity, either through a built-in communications module or tethered to a mobile device in 2017. However, amidst the opportunities for a range of technologies to merge our various worlds of data and to sense both vehicular and human conditions, several hurdles remain before connected cars become mainstream. Ogi Redzic, senior vice president for connected vehicles at the Renault-Nissan Alliance, stands next to the Nissan Motor Co. Intelligent Mobility IDS Concept electric vehicle during the 2017 Consumer Electronics Show (CES) in Las Vegas, Nevada, U.S., on Thursday, Jan. 5, 2017.

One thousand people will have their minds monitored at the same time while watching the new sci-fi movie MindGamers on March 28. The one-night event, MindGamers: One Thousand Minds Connected LIVE will take place in select movie theatres nationwide, presented by Fathom Events and Terra Mater Film Studios. The event will be the "world's first mass mind collective" Fathom Events said. The minds of one thousand people will be simultaneously connected through cloud technology while watching the sci-fi movie by wearing a cognition headband. The headbands will allow scientist to track the audience members' minds (all at once) and create an image of the "mass-mind state."

IBM said it is offering support for Google's open source machine learning technology TensorFlow with its PowerAI software. The next wave of IT innovation will be powered by artificial intelligence and machine learning. We look at the ways companies can take advantage of it and how to get started. The move highlights ongoing collaboration between tech giants in the AI space including Google, Nvidia, IBM, and AMD. According to IBM, TensorFlow has become popular among enterprises looking to use deep learning frameworks.