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Marking a new era of “diagnosis by software,” the US Food and Drug Administration on Wednesday gave permission to a company called IDx to market an AI-powered diagnostic device for ophthalmology.

What it does: The software is designed to detect greater than a mild level of diabetic retinopathy, which causes vision loss and affects 30 million people in the US. It occurs when high blood sugar damages blood vessels in the retina.

How it works: The program uses an AI algorithm to analyze images of the adult eye taken with a special retinal camera. A doctor uploads the images to a cloud server, and the software then delivers a positive or negative result.

Continue reading “FDA approves AI-powered diagnostic that doesn’t need a doctor’s help” »

Artificial intelligence is being used for a dizzying array of tasks, but one of the most successful is also one of the scariest: automated surveillance. Case in point is Chinese startup SenseTime, which makes AI-powered surveillance software for the country’s police, and which this week received a new round of funding worth $600 million. This funding, led by retailing giant Alibaba, reportedly gives SenseTime a total valuation of more than $4.5 billion, making it the most valuable AI startup in the world, according to analyst firm CB Insights.

This news is significant for a number of reasons. First, it shows how China continues to pour money into artificial intelligence, both through government funding and private investment. Many are watching the competition between China and America to develop cutting-edge AI with great interest, and see investment as an important measure of progress. China has overtaken the US in this regard, although experts are quick to caution that it’s only one metric of success.

Secondly, the investment shows that image analysis is one of the most lucrative commercial applications for AI. SenseTime became profitable in 2017 and claims it has more than 400 clients and partners. It sells its AI-powered services to improve the camera apps of smartphone-makers like OPPO and Vivo; to offer “beautification” effects and AR filters on Chinese social media platforms like Weibo; and to provide identity verification for domestic finance and retail apps like Huanbei and Rong360.

Continue reading “The world’s most valuable AI startup is a Chinese company specializing in real-time surveillance” »

A futuristic plan for Shenzhen, China proposes self-driving car tunnels and drone-specific highway lanes.

Wizebit is proud to welcome Machine Learning guru Peter Morgan to its elite team of blockchain specialists and developers.

Peter is the author of the popular report, “Machine Learning is Changing the Rules: Ways Businesses Can Utilize AI to Innovate”, and brings years of real world experience designing, building, and implementing AI and IP networks for Cisco, IBM, and BT Labs.

As the first company to create a confidential smart assistant on the blockchain, Wizebit officially launched in 2018 with the mission of allowing personal data to be connected while remaining protected.

Continue reading “Wizebit: Machine Learning expert Peter Morgan joins our team” »

How close are we really to space travel? Our featured contributor Lola Akinmade Åkerström talks to Space Nation, a company that’s researching both space tourism and how space technology can help us on Earth.

Thanks to Google, it can often feel like there are no mysterious places left on earth to explore—and finding new places to call the ‘final’ frontier seems increasingly difficult. Even the Pacific Ocean’s Marianna Trench, at over 36,000 feet deep and arguably the most legit final frontier on earth, has been explored by Hollywood director James Cameron in a submersible. As a result, the past few decades have seen us looking upwards to the most mysterious of places: Our own galaxy.

Blockbuster movies set in space and fictional alien encounters continue to intrigue us. Space discovery programs on TV science channels continually pique our curiosity. Even kids’ cartoons such as the 1960s American series The Jetsons brought the concept of commercial space travel closer to us, thanks to its flying space cars, pod-like apartments, and a robot maid called Rosie.

NASA wants to go to Mars. SpaceX wants to go to Mars. Michio Kaku wants humanity to go to Mars so we can avoid extinction. The rest of us just want to see our species actually set foot on Mars. But first, the moon.

Think of the moon as a launchpad for the Red Planet. As LiveScience found out, Boeing’s Crew Space Transportation (CST)-100 Starliner is going to take advantage of our satellite as a blast-off point for the next frontier. Starliner (the name is about as sci-fi as you can get) is what happens when Boeing, which probably makes everyone think airplanes not spaceships, joins forces with NASA to develop a reusable space capsule that will be able to fly up to seven astronauts to the ISS. It will also be the world’s first commercial space vehicle.

Starliner is even autonomous. Meaning crews will spend less time on training and take off sooner. It only needs one astronaut to fly it, or more like assist it in flight, using tablets and touch screens.

Continue reading “Humans are going to infinity and beyond (or at least the moon) with Boeing’s Starliner” »

Machines don’t actually have bias. AI doesn’t ‘want’ something to be true or false for reasons that can’t be explained through logic. Unfortunately human bias exists in machine learning from the creation of an algorithm to the interpretation of data – and until now hardly anyone has tried to solve this huge problem.

A team of scientists from Czech Republic and Germany recently conducted research to determine the effect human cognitive bias has on interpreting the output used to create machine learning rules.

The team’s white paper explains how 20 different cognitive biases could potentially alter the development of machine learning rules and proposes methods for “debiasing” them.

Continue reading “Human bias is a huge problem for AI. Here’s how we’re going to fix it” »

We created the first working AI using the theory of practopoiesis. We are still far away from biological intelligence, but still we have something much better than classical machine learning. You can play with a live demo here:

next is an advanced smart transportation system based on swarms of modular self-driving vehicles, refined by italian designers and engineers. the modules can drive autonomously on regular roads, joining themselves and detach even when in motion. when joined, the doors between modules fold, creating a walkable open space among modules. founded by tommaso gecchelin, the concept would greatly outperform conventional transportation when used in conjunction with other modules. the collection of next modules would improve traffic fluidity, commute time, running costs and pollution prevention by optimizing each module occupancy rate.

once linked, passengers would be able to walk between modules the modules would be individualized shipping and goods transportation could be adapted companies would offer specific modules to the system piotr boruslawski I designboom.