Inside CTO/CIO - July 2nd, 2019 |

Inside CTO/CIO (Jul 2nd, 2019)

Splinternet concerns/data science talent/tech innovation

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1. Training neural network models for natural language models may have serious environmental consequences. A single AI carbon model can produce nearly five times the emission produced of the average American car over its lifetime. Training the same AI model to work across different domains requires far more power than training the original model, according to a new paper published by computer science researchers at the University of Massachusetts. Quantum computing may help in reducing AI's carbon footprint. Benchmarking standards for quantum computing, which may ultimately solve certain problems that overwhelm conventional computers, are being developed -- SEARCHCIO

2. Trade tensions between the U.S. and China may lead to certain technologies being governed by different regulations in different geographies, according to Boston Consulting Group. Of particular concern is that the emergence of two tech worlds can have a big impact on the internet, a prospect that is being dubbed the "splinternet," says Hans-Paul Burkner. The Middle East, Africa, Australia and parts of Eurasia may find themselves the battlegrounds as China and U.S. tech companies fight for dominance. Resumption of trade talks between the U.S. and China may result in reducing friction between the two countries. - CNBC   

3. Time series databases are becoming mainstream as enterprises increasingly need to query, analyze and report on streaming data in real-time. Over the last two years, no database type has grown faster in popularity than time series databases, which were once a niche solution for applications such as running trading systems within a financial services firm. Time series data sets primarily have in common the arrival of data in time order, the recording of data arrival as a new entry and accommodating time-intervals that are either irregular or regular. The practice of recording every system change makes it possible to measure change, monitor how something is changing and predict how it may change in the future.-- TECHREPUBLIC

4. IT leaders are honing their expertise at hiring top data science talent. In the face of a data scientist shortage, CIOs need to convince potential employees that they will be able to do work that has direct benefits for the business and show them that the company has a clear vision and strategy for capitalizing on data. - CIO

5. Using AI for interrogating regulatory forms and identifying risks and anomalies could help provide better oversight for payment systems. A report commissioned by the Bank of England, titled the Future of Finance, says that there is concern over how means of payment are changing. It calls for the use of "reg-tech" technology to improve payment infrastructure so that banks will have a manageable and coordinated way to respond to auditors. - THE GUARDIAN 

6. The next challenge for sentiment analysis will be to capture the context and the tone of a sentence in product reviews and other social media. Researchers are currently working on how sentiment analysis systems can detect sarcasm or sincerity to better discern opinions that can help companies solve problems related to customer support and product feedback.  -- TOWARDS DATA SCIENCE

7. China is now the global leader in the deployment of transformative IoT services. The country is now the world's largest IoT market, accounting for 64 percent of 1.5 billion global cellular connections. As one example, the Jing 'an District has become a smart community, with over 500,000 IoT sensors covering over 37km (about 23 miles). -- TELECOMPAPER

8. Graph databases have more use cases as enterprises accumulate volumes of unstructured data. These systems have applications for master data management, compliance, identity management, and machine learning.-- 7WDATA

9. Companies are combining big data and human instinct to make business decisions but still struggle with how to merge these two inputs. Their revenue depends on how to balance the two factors. Experts provide their perspectives on how to approach the issue. -- DATAMATION

10. The big regulatory issues that the tech industry faces today revolve around AI, copyright laws and data privacy, but compliance with existing and upcoming mandates could stall innovation. Consumers gain protections against unwarranted intrusions as regulations catch up to the rapidly evolving tech industries.-- FORBES

Jennifer Zaino is a freelance writer and editor specializing in business, technology, healthcare and education. 

Editing team: Kim Lyons (Pittsburgh-based journalist and managing editor at Inside), David Stegon (senior editor at Inside, whose reporting experience includes cryptocurrency and technology), and Bobby Cherry (senior editor at Inside, who’s always on social media).

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