data quality


Quality of Data is Holding Back AI Development at Ports

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AI has the potential to revolutionize the performance of terminal operating systems (TOS), intelligent modules and machines, but Dr. Saanen has found that a lack of "solid information" across the entire supply chain will hinder its development. In an interview with Port Technology (above), Dr. Saanen gave the example of how accurate reporting of a ships' outgoing baplie was "still a rare event". Saanen said: "Today, the quality [of information] is quite poor. "We're dealing with input which is at best so-so, and we're trying to feed powerful algorithms with that. "We have to address that."


For AI to Change Business, It Needs to Be Fueled with Quality Data

@machinelearnbot

There's no doubt that AI has usurped big data as the enterprise technology industry's favorite new buzzword. After all, it's on Gartner's 2017 Hype Cycle for emerging technologies, for a reason. While progress was slow during the first few decades, AI advancement has rapidly accelerated during the last decade. Some people say AI will augment humans and maybe even make us immortal; other pessimistic individuals say AI will lead to conflict and may even automate our society out of jobs. Despite the differences in opinion, the fact is, only a few people can identify what AI really is.


Expert View: How AI Is Changing BI Articles Chief Data Officer

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We see data becoming more of a core competency within companies, with full-fledged departments devoted to it. These are made up of a chief data officer and a team handling data ops and another team managing data quality. The change is gaining momentum, and we believe that in the next 5 years every company with more than 500 employees will have these functions. The ability to turn data into insights gives companies a competitive advantage, and the sooner they advance to this, the sooner they will see the fruits of this important business advantage. We also see access to data becoming democratized within companies, with greater access within companies to core datasets and having the analytical capabilities at their fingertips so they do not need to run to a BI specialist for every report.


AT&T Labs' Mazin Gilbert on AI, quantum computing, data collaboration and 5G

ZDNet

Dr. Mazin Gilbert, AT&T Labs' vice president of advanced technology, is placing his research bets on software defined infrastructure, big data, artificial intelligence and ways to scale and optimize the telecom giant's network. But first Gilbert needs some help from the open source community to bring the data sharing that'll enable many of these advances. We caught up with Gilbert last week in New York City to talk shop. 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.


Data management to navigate regulatory complexity

@machinelearnbot

At the centre of financial services risk management and regulatory compliance is the convergence of data from a huge range of information silos, departments, product lines, customers and risk categories. Risk and finance are at the end of an extensive chain, examining the consolidated threads, uncovering issues and spotting patterns. Because new regulation such as FRTB forces the issue, many organisations run into difficulty, unable to resolve the enormous data integration task. Without good data management, argues Martijn Groot, VP Product Management, Asset Control, obtaining the right information to provide to regulators is like trawling cloudy waters; there will always be uncertainty as to the resulting catch and its quality. The banking sector remains in the middle of reform, with investment in risk and compliance continuing to rise.


Bad Data Is Ruining Machine Learning, Here's How To Fix It

@machinelearnbot

In a recent interview with us, Vijay D'Souza, Director of the Center for Enhanced Analytics at the US Government Accountability Office, noted that, 'Regardless of the goals, it's important to understand the quality of the data you have. The quality determines how much you can rely on the data to make good decisions.' As it stands, bad data is ruining companies' data initiatives. This is one of the primary reasons why just 25% of businesses are successfully using their data to optimize revenue, despite the tremendous resources being pumped into them. IBM estimates that bad data is costing organizations some $3.1 billion a year in the US alone, while in Experian's Data Quality survey, 83% of companies said their revenue is affected by inaccurate and incomplete customer or prospect data.


Hype or Not? Proven Value from Artificial Intelligence

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My new favorite vlog to follow is that of Simone Giertz. She is a Swedish inventor, maker and a robotics enthusiast. She is your real life, modern and feminine version of Dr. Emmet Brown (from the movie Back to the Future). Even better, she builds artificial intelligence/robots to help her with the mundane daily tasks like brushing teeth or making a bowl of cereal. I doubt that these robots are truly useful, but they are funny.


Google Artificial Intelligence 'Alpha Go Zero' Just Pressed Reset On How To Learn

@machinelearnbot

Remember (vaguely) how you learned to walk, talk, ride a bike, or drive? It was messy and full of mistakes, but the skills you learned that way stayed. Outside of living systems, it's been challenging to structure strong enough algorithms to take in "real life experience" and develop sticky, adaptable behaviors for artificial intelligence. "It starts from a blank slate and figures out only for itself, only from self-play, and without any human knowledge, or any human data, or features, or examples, or intervention from humans. It discovers how to play the game of Go from first principles," says DeepMind's professor David Silver.


How Can Machine Learning Affect Your Organizational Data Strategy?

@machinelearnbot

One of most significant difficulties confronting undertakings today is Data Security and Data Privacy. The rise of high information advances, for example, Big Data, Machine Learning (ML), and the Internet of Things (IoT) in the Data Management scene has now started another enthusiasm for Data Governance. With so much multi-channel information streaming into a joint association, the issues of Data Quality and Data Governance are accepting prime significance. The present undertaking information, on account of cutting-edge information advancements, is currently gathered, sorted out, and stored in multi-layered, investigation stages, which makes comprehensive details taking care of and Data Management techniques more unpredictable than any other time in recent memory. To put it plainly, endeavor information can't be viewed as reliable without a decent Data Strategy set up.


Can Creativity Be Implemented in AI?

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Artificial intelligence (AI) takes the power of computing systems to a different level. It is amazing to even think that a computing system can emulate human beings. There are many fantastic examples of AI in various areas of our lives. That said, computing systems are still considered limited in their capabilities because they cannot think creatively like human beings. While AI can process and analyze complex data, it still does not have much prowess in areas that involve abstract, nonlinear and creative thinking.