How AI Will Revolutionize News as We Know It
The rise of the internet has changed every aspect of our lives. There is something online for every interest and need, often just a click of the mouse (or tap of a thumb) away. The consequences have been real, forcing entrenched business models to adjust – or be made obsolete.
Media is one of many sectors experiencing seismic shifts. While television has mostly managed to retain its place as America’s go-to stop for news through the hand-wringing about the potential death of print media – Pew Research Center issued a 2017 report detailing that 50 percent of America’s population gets their news from TV – that report also contained a surprising development: online news is gaining ground more quickly than expected. 43 percent of Americans now report they get their news on the internet – a five percent increase over the year before.
There are numerous reasons for this shift. The public is cooling on the interruptions and annoyance of TV advertising; Americans have also shown an increasing hunger for subscription media services offering high-quality content that matches their personal interests. An increasing amount of that content is video – Cisco reports that video will make up 82 percent of total consumer web traffic by 2021 (an increase of nine percent over 2016) – with “IP-delivered TV experiences as a key driver.”
Broadcasters and news outlets have been forced to adjust to this brave new world, and it hasn’t been without growing pains. A Reuters Institute research report, “The Future of Online News Video”, described most news organizations as being in “an experimental phase; they are nervous about the significant investment required, the difficulty of scaling video, and the uncertain path to commercial return.”
Artificial intelligence is providing a path forward – in fact, Chris Richardson, experienced digital media entrepreneur and CEO of Linius Technologies, wrote in Forbes that the future is well on its way for ultra-curated, personalized news content. Bloomberg’s Project Cyborg initiative is working to bring automation to journalism, says Richardson; The Associated Press is “embracing software to automate copy creation for investment and sports coverage, dramatically increasing the number of write-ups produced” while also “exploring automation and AI to surface political data to enable better, faster election reporting.” Meanwhile, broadcasters like RTVE and the BBC are researching how to “automate the production of news packages, sports highlight packages and the connection of content to viewer preferences through data mining techniques” and even detect and quell fake news reports.
Richardson envisions an algorithm-driven world where users’ interests and preferences will be the source of custom-tailored content. “Production costs are minuscule, the number of hyper-personalized video streams infinitely scalable, and the consumer experience hyper-targeted,” writes Richardson, before rhetorically asking: “Who wouldn’t be willing to pay for this type of hyper-personalized subscription service?” If research is any indication, AI is offering a profitable way forward for news organizations around the world.
If You’re Wondering When A.I. Will Start Making Market Predictions…
Guess what – it already is. Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generates trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.
Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:
- Finding stock patterns in the market
- Finding trends in the stock market
- Testing portfolios to see if they are well-diversified
- Back-testing statistics to see how different stock patterns generated trading results
- Making Predictions for price movements in the future, with “A.I. Rank” and level of confidence in the trade.
And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.
Contributor
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
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