Data science companies are increasingly looking at portfolios when making hiring decisions. One of the reasons for this is that a portfolio is the best way to judge someone's real-world skills. The good news for you is that a portfolio is entirely within your control. If you put some work in, you can make a great portfolio that companies are impressed by. The first step in making a high-quality portfolio is to know what skills to demonstrate.

After we Save and Activate our process, we are now ready to test it.

US department store Macy's have announced the pilot of "Macy's On Call," a mobile web tool that allows customers to interact with an AI-powered platform, via their mobile devices. "Macy's On Call" leverages IBM's Watson technology, via Satisfi, an intelligent engagement platform, to deliver a first-of-its-kind solution that will enhance the customer in-store shopping experience at 10 test locations nationwide. The mobile companion, accessed via a mobile browser, allows customers to input natural language questions regarding each participating store's unique product assortment, services and facilities and receive a customized response to the inquiry. There are a number of ways that customers may request information. For example, a customer could type, "Where are the ladies shoes?" or type a combination of brand and product inquiry such as "INC dress," and they will receive the relevant response and location of that product in the store.

Tech City News held a roundtable attended by a variety of AI experts, who discussed the potential of AI and the ethical challenges posed by the technology. Yessi Bello Perez, our reporter, has more. Just last year, Stephen Hawking – arguably one of the world's brightest minds – predicted artificially intelligent computers would overtake humans at some point over the next century. Although it may have seemed like an outlandish statement at the time, the truth is that since Hawking's appearance at the Zeitgeist conference in London, artificial intelligence has reached buzzword status among the highest echelons of the global tech scene. AI-focused investors have emerged, funding in the space is soaring, tech giants are acquiring AI startups – and pouring significant resources into researching the technology – and the community is avidly discussing the technology's potential and its ethical implications.

In the enterprise support field, there's a trend to have self-service bots replace human assistants. In fact, by 2020, Gartner estimates that customers will manage 85 percent of their brand relationships without talking to a human, and brands are answering this call for more self-service. However, there will occasionally be a point at which self-service tools alone will not satisfy. Sometimes circumstances call for a live, human interaction. Virtual assistant chatbots are usually the first point of contact.

It won't help you find Pikachu, but a new mobile tool from Macy's will assist shoppers in navigating the store. The department store retailer is piloting "Macy's On Call," a solution that lets in-store customers use their mobile phones to interact with an artificial intelligence (AI) platform powered by IBM Watson. The Satisfi intelligent engagement platform provides the connection between the mobile tool and the Watson platform. Macy's On Call, accessed via a mobile browser, allows customers to input natural language questions about the store's unique product assortment, services and facilities. These can include store navigation details, as well offerings such as the myStylist personal shopper program and buy-online-pickup-in-store counters.

Artificial intelligence is certainly affecting everything we do. And much of that innovation with AI comes from venture funding. So it's no surprise that one day, someone would think of mixing these two things. It, in its own words, is "The world's first Venture Capital fund powered entirely by Artificial Intelligence." According to the site, The AIVC is 100% data driven. It uses historical data and advanced predictive algorithms to make investment decisions, much like a normal VC would.

Artificial intelligence has replaced big data this year as the most talked about new set of technologies. As with big data five years ago--behind the hype, the confusion generated by an ill-defined term, and the record funding by VC--we are starting to see emerging investments and practical applications where it matters most--in enterprises. A new report from Narrative Science, based on a survey of 235 business executives conducted by the National Business Research Institute (NBRI), sheds light on the state-of-AI in enterprises today and in the future: 38% of enterprises are already using AI technologies and 62% will use AI technologies by 2018. Keep in mind that "AI technologies" is a broad term that includes machine and deep learning, recommendation engines, predictive and prescriptive analytics, automated written reporting and communications, and voice recognition and response. Big data has spawned the current interest and increased investment in artificial intelligence.

First was the Monte Carlo tree search, an algorithm that rather than attempting to examine all possible future moves instead tests a sparse selection of them, combining their value in a sophisticated way to get a better estimate of a move's quality. The second was the (re)discovery of deep networks, a contemporary incarnation of neural networks that had been experimented with since the 1960s, but which was now cheaper, more powerful, and equipped with huge amounts of data with which to train the learning algorithms. The combination of these techniques saw a drastic improvement in Go-playing programs, and ultimately Google DeepMind's AlphaGo program beat Go world champion Lee Sedol in March 2016. Now that Go has fallen, where do we go from here? Following Kasparov's defeat in 1997, scientists considered that the challenge for AI was not to conquer some cerebral game.

Artificial intelligence platform startup that seeks to automate the notification and messaging process to personalize consumer experience is seeking a Machine Learning Engineer. The Machine Learning Engineer will develop the recommendation models and systems behind this AI platform. Benefits include competitive compensation package, equity, bonus, full benefits, paid time-off, and a great team work environment with company outings and collaborative work culture. This startup has received close to 20M in funding, and this is a ground floor opportunity to apply industry data science experience and develop something from scratch. You will be able to see your impact on the core product!