The results of the experiment sheds light on the origin of learning and the adaptability in non-neural organisms not related to evolution. Perhaps it also has some implications for the evolution of machine learning.
The day is coming when being able to sort these things out becomes paramount. Best to think about it now than to wait and find your projects derailed or, find yourself pegged as neatly as an insect to a collector's board.
I'm hoping you'll join me at the Excellence in Journalism event where I'll be on the panel discussing tips and tools for journalists and editors in finding the truth in big data. Like all industries, journalism is data-driven these days. But also like other industries, many professionals are still struggling to master big data tools. We panelists will be focused on sharing specific and useful information with leading journalists on perfecting their big data skills, selecting data sources, and picking big data tools.
At issue were "unfair business practices" which covers the gamut from price discrimination, redlining and identity theft to data collection and brokering abuses. Some states, like Massachusetts' attorney general, do have "some regulatory tools to tackle this issue, including the state's consumer protection law and the ability to put forth regulations." Are we in for a patchwork of conflicting state laws?
Big data has moved from a trend to a given even though not all companies are comfortable with the tools yet. Indeed, many big data projects are still focused on the low hanging fruit and the big fields of information in the harder data warehouse terrains are largely left unharvested. But things are progressing and everyone pretty much accepts that data-driven is the only way forward. The question is, what comes next?
First Google bought Nest to up the ante in smart home analytics. And that was pretty cool since it also heralded the onset of the IoT age in earnest. What could possibly make the stakes more evident than Google plunking down a cool $3.2 billion for a frickin' home thermostat, eh? But now Seeley International, a major air conditioner manufacturer, is also turning to data analytics in its air conditioners sold worldwide and we have to wonder how all those smart things are going to work together – or not.
These days, disruption is the only thing you can count on and this one is fairly easy to see coming. Plan for it now.
EY report: Insurers are lagging badly; most 'can't build a fully functional data ecosystem on their own'
EY, formerly known as Ernst & Young, released a new sensor data survey focused on insurers. They found the insurance sector vulnerable to disruption since it still primarily relies on customer self-reporting and is lagging behind in using new data sources, such as from wearables, telematics and other sensors. While insurers who move first to using new data sources can, according to EY, become the industry disruptors, they'll have to be innovative about how they get the data because most "can't build a fully functional data ecosystem on their own."
Protest rallies are popping up everywhere and the intensity of resistance is growing. Companies everywhere should not see this as solely a backlash against government, but a signal that consumers are not accepting big data intrusions as inevitable. Indeed, they're becoming more agitated and more mobilized. This bodes ill for companies who are still ignoring privacy issues.
Investor trends are not the same as predictive analytics because far too much stock market movement is merely knee-jerk reactions with precious little data to aim the kick. But there are those that think big data's very bad day in the stock market is a strong indicator of a slowdown in overall business spending. After all, the thinking goes, if the biggest, baddest, hottest tech – big data – isn't hitting earnings forecasts, then businesses must be seriously curtailing tech purchasing.