Drones have arrived. We’ve seen a plethora of ideas springing up around drones and their potential uses for business – aerial surveying and reporting, real estate assessment, wedding photos, sports action photos, to name a few.
Our relentless focus on the importance of big data is often misleading. Yes, sometimes, deriving value from data requires an immense amount of that data. But the key for most innovators is that the size of the data isn’t the most critical factor — having the right data is.
It’s been an incredible year for digital marketing. 2016 saw numerous ups, downs, and unexpected trends. As we kick off 2017, prepare to see some game-changing opportunities and exciting developments that may impact your marketing plans.
Today’s competitive business world demands innovation. However, the burden of innovation has largely rested on startups. Large corporations are expected to out-think their rivals, but more often we see that they rely on minor product updates or acquisitions in place of home-grown innovation.
Now that Tesla has officially acquired SolarCity, it’s not wasting any time showing what the combined entity can do. Tesla has revealed that it’s running the island of Ta'u (in American Samoa) on a solar energy microgrid that, at 1.4 megawatts, can cover “nearly 100 percent” of electrical needs.
Scientists from the University of Central Florida (UCF) have created a supercapacitor battery prototype that works like new even after being recharged 30,000 times. The research could yield high-capacity, ultra-fast-charging batteries that last over 20 times longer than a conventional lithium-ion cell.
A team of researchers managed to make a synthetic pathway that converts CO2 into organic compounds faster than plants. Once the technology is successfully transplanted into living plants, we would be in for faster, less energy-intensive CO2 fixation.
Google researchers have worked with doctors to develop an AI that can automatically identify diabetic retinopathy, a leading cause blindness among adults. Using deep learning—the system detects the condition by examining retinal photos at a success rate similar to human opthamologists.