Business demand for machine learning is rapidly rising. It's no longer enough for data scientists to build solutions by hand. Prolifics' Data Science in a Box solution helps recognize the full potential of artificial intelligence and machine learning in the context of building data models, consuming business data, and deploying models to production. Tune in to our Data Science in a Box webinar to learn more about our cutting-edge data science automation solution. Find out how it can help you make sense of your collected data, quickly and easily build predictive data models, and gain faster time to value from your data.

Getting Over Ranking Factor Studies in the Era of Machine Learning September 25, 2018 Posted by Mordy Oberstein Just admit it, SEO is scary. Between the inherent complexity of what we do and Google not exactly being the epitome of clarity, the ground that is doing SEO can be a bit shaky at times. That's pretty much why we're obsessed with what works and what doesn't work and are vigilantly on the lookout for content that offers a bit of light at the end of the tunnel. In the not too distant past, I wrote a piece highlighting how machine learning has impacted rank volatility (in that rank is considerably more volatile). At the time, we touched on what machine learning means for understanding how ranking works and how the process directly influences rank. Here, we'll get into the nitty-gritty of it all by analyzing the holy of holies of optimization information, ranking factor studies, particularly niche ranking studies by asking one very simple question .... Do ranking factors studies still apply in a world where machine learning and intent reign supreme, and if so, to what extent? Recap of Machine Learning's Impact on Rank The increase in rank volatility aside, in what for all intents and purposes was "Part I" of this post we discussed how machine learning impacts rank qualitatively, i.e., what rank "looks like" as a result of RankBrain and the like. Since I'm a nice guy, let me recap (and expand on) what we said there so that you don't have to comb through the last piece trying to glue together all of the pieces to the puzzle. Machine Learning Sets Site Proportions In serving up results that align to user intent, Google uses machine learning to determine the proportion of sites to meet that intent or those intents. OK, Mordy, say that in English, please?! If you'll remember, in the last post I took a very straightforward search term, buy car insurance, and showed that Google sees two (or really more than two) intents embedded in that phrase: to buy an actual insurance policy and to get information about doing just that. How should Google handle these two intents?

The mention of "Indian classical music" does not inspire images of cutting-edge technology, artificial intelligence, or smart devices. Ranade is a 38-year-old classical vocalist and software engineer based in Pune. He lent his music and technology skills to create NaadSadhana, an iOS app that uses artificial intelligence (AI) to help users practice classical music. Released on the App Store in July, NaadSadhana provides machine learning-based tuning feedback, tanpura, tabla, and swaramandal simulations to help students improve their pitch, rhythm, and performance. While iOS users can find many apps available providing similar features, NaadSadhana is unique in how it uses machine learning to simulate a live-concert experience.

Improving business productivity and performance majorly depends on collecting the data and effectively analyzing it. With the growing popularity of IoT, there will be an obvious surge in data that will require better infrastructure and smarter Data Science approaches. Internet of Things (IoT) is not a separate piece of the latest technology but a convergence of various complementing technologies that contribute towards production optimization, predictive maintenance, asset monitoring and management, new products and services, etc of the businesses. It is expected that, by 2020, more than 20 billion devices will be connected. This depicts the enormous volumes of data that will be generated from these devices.

If you thought cybersecurity was a challenging and often weird part of the tech industry, be prepared for it to get even odder. The next couple of years will bring a new range of threats that will take tech security far beyond its traditional boundaries and will require a whole new set of skills and alliances. One example: tech analyst Forrester predicts that deepfakes could end up costing businesses a lot of money next year: as much as $250m. That might happen in a couple of ways. There's the risk to your share price if someone creates a deepfake of your CEO apparently resigning from the company.

Do you feel flustered with trends? Confused when a new fashion statement starts ruling the market? Do you have an online retail store but do not know what to stock; what a new trends in eCommerce in 2019 will look like? Then this post is just for you; follow the tips down below and make your decision-making process a bit easy. Are you able to showcase AI powered related products, upsell items and frequently bought together products on your online store?

The key role of enterprise services in Orange's plans for growth was spelled out clearly by Orange Group's Chairman and CEO, Stéphane Richard, when he presented the Group's five-year strategy, Engage2025, in Paris in early December. He said, "The enterprise market is changing profoundly to become data-driven, multi-cloud based and end-to-end cybersecurity…more than ever we believe in convergence of the technical and IT business, and we intend to accelerate the transformation of the B2B business. "The best proof of IT convergence is the skyrocketing demand for virtualised and on-demand services such as SD-WAN. We have a clear edge over conventional digital services companies in that we have the IT know-how. We are prepared for the challenges…of creating the right partnerships and automating and digitising the processes with the benefits of data analytics and AI". Multiservice integration services (MSI) are one of the areas in which Orange Business Services has invested heavily to gain that edge, a claim supported by testimony from Gartner and more importantly, from its customer Sony. In July, Sony Group announced it had chosen Orange Business Services to consolidate and transform the communications infrastructure of its two largest operating companies, starting with a harmonised network to improve user experience globally. Orange will be Sony's principal global provider, delivering a fully automated, intelligent network for all global business units over time. The solution will be built on Orange's Flexible SD-WAN and will connect more than 500 locations in over 50 countries across five continents. The plan is to deliver better performance, security and scalability. "Orange innovation, integration capabilities and international network are the catalysts that will allow us for the first time to bring our regional operating companies under one umbrella," said Makoto Toyoda, Chief Information Officer, Sony Group. "Only Orange could deliver a platform with the scale and scope to cover all the moving pieces of our international business.

Girone: My talk is going to be about what we do and how we process big data and what the challenges are around this. I will be giving a short introduction of CERN. How many people know about CERN here? Ok, so I'll skip the introduction maybe. I will then concentrate on computing and describe a little bit the challenges and the environment that today we work on. Most of my talk is going to be about what comes next in terms of machine, the machine is going to be upgraded, and computing and storage needs, which already are huge today, are going to go even higher. I'm going to discuss a little bit how we have started our R&D program about this. CERN is certainly a wonderful place to work. It has been created, founded by the member states of Europe just after the Second World War to give the opportunity to physicists, scientists, in general, to come together after a big war and work together. This is actually what we still do today. It has been built across two different countries.

A delegation of members of the European Economic and Social Committee (EESC) visited three Finnish technological hubs to assess the potential benefits and dangers of artificial intelligence for our society. They stressed that all future developments must encompass three pillars: product safety, consumer trust, and solidarity in health and social care. Artificial intelligence applications can increase people's wellbeing, but the potential risks need to be taken seriously. The products that are emerging as a result of new technologies and the digital revolution are in general extremely helpful and can have a wide range of uses in all areas of our lives, from dispensing medicines to curing loneliness. However, they need to be handled with care, as they are not always as straightforward as they may seem.

A Polish start-up has developed the first application in a suite of artificial intelligence (AI) tools dedicated to crop monitoring, yield optimization and management of outdoor hemp fields. "We'll be able to accurately predict when flowers will be perfect for a harvest. That's important not only because cannabinoids content can drop more than 35% if collected too late, but it's also critical from a logistics point of view," said Marcin Marczak, CEO at the developer, Green Cube Solutions. "With the limitations on available equipment, good planning is the key to a successful harvest." The technology being developed by Łódź-based Green Cube is an "integrated end-to-end platform that will support farmers from soil preparation through harvest and up to product distribution," Marczak said.