Computer Vision: Picturing The Future Of Retail
It’s no big secret that we live in a consumer-driven society.
The buyer is king and retailers have to keep up with current trends through investing time and money in data-informed insights to shape their core business strategies.
Big Data will always play a part in influencing how retailers operate and market their products and brands. Advancing deep learning algorithms are increasingly being used to power the development of brands and products that consumers want with greater knowledge on the individual, personal buying experience.
Emotion plays a huge part in marketing and brand building
But, it’s not all stats and figures anymore. The future of retail could be led by computer vision and mixed reality technologies to transform the way we shop and interact with our favourite brands. Emotion plays a huge part in marketing and brand building, so retailers are now looking at innovative technologies that push the boundaries of interaction and emotion in the buying experience.
There’s been a lot of buzz around Oculus Rift, Samsung Gear, and PlayStation VR recently, but we’re also seeing start-ups breaking onto the scene with more retail-led applications for computer vision and mixed reality tech.
Outdoor giants The North Face have used Virtual Reality as a means ...Read More on Datafloq
Is AI the Key to Eternal Life?
Life after death is a topic that has kept some of the greatest minds occupied for millennia. It’s something we tend to shy away from talking about, but unfortunately, death and grieving are inevitable realities of being human. With ground-breaking research happening in Natural Language Processing and Artificial Intelligence, could technology hold the answer we’ve been looking for?
When you suffer loss, there is a longing to speak to the deceased again – and technology is making this possible. Death today comes with the uncanny nature of leaving behind a digital footprint, a legacy of social media posts, videos, pictures and text messages – what are the living meant to do with these? Feed them into an artificial neural network and create a chatbot version of the deceased, obviously.
These controversial projects are looking to how we can leverage deep learning to extend our lives by imitating an extension of life through a chatbot, or ‘griefbot’ – yes, you’re right this is very Black Mirror.
We’ve come a long way since ELIZA, Joseph Weizenbaum’s computer program from the mid-1960’s that responded to questions like a psychotherapist by using predetermined phrases, simply repeating back the user’s questions in different formats to form an ...Read More on Datafloq
How to Gear Up For A Driverless Future
There’s been a lot of talk lately about autonomous cars with countless companies proclaiming they’ll be the first to release this revolutionary tech. Competition is heating up between companies like Volvo, Google, Uber and Tesla to name a few. Uber piloted self-driving cars in Pittsburgh last month, overseen by a Driver and Engineer. Singapore-based software developer nuTonomy has also launched trials into self-driving cars with hopes to launch them in 2018 for public use.
Each year, a mammoth 1.2 million people are killed on the world’s roads, with 90% of these tragedies being down to ‘human error’ – drunk driving, tiredness, road rage, visual impairment. The technology used in creating the driverless car makes it possible to reduce the number of fatalities.
There are numerous systems working together to power driving the car. Lidar Sensors, highly accurate sensing systems that work by rotating and bouncing pulsating laser light off of the surroundings. This produces ‘time-of-flight’ measurements of range, accurate to the centimetre, producing millions of data points per second. The car is able to maintain a precise position thanks to ultrasonic sensors in the wheels. Altimeters, gyroscopes and tachymeters are also at work to make sure the car keeps the correct and ...Read More on Datafloq
4 Ways Big Data and Machine Learning Are Helping Conservation
The interdisciplinary field of computational sustainability is using machine learning algorithms to analyse and extract valuable insights from sets of Big Data gathered from environmental fields. It’s not just about having large data sets or advanced pattern finding algorithms – it’s how we use them. The following projects highlight how Machine Learning and Big Data are helping conservation efforts of all kinds.
The ambitious Earthcube project has been in development the past five years and aims to produce a living 3D replica of Earth to serve scientists of different disciplines. It has been built upon interconnected projects that use computer science, big data, and geoscience among various other branches of learning. There is a gold mine of data when it comes Earth sciences that have been collected over years of study and research that has the potential to benefit environmental causes greatly. Earthcube funds a variety of projects, such as the Coral Reef Science & Cyberinfrastructure-Network (CRESCYNT). By using species databases, image analysis software and 3d mapping they can monitor the decline of the coral reef’s structural changes, disturbances, coral disease, sea temperatures and coral bleaching. The research will allow for a greater understanding to help protect and preserve what ...Read More on Datafloq