Are you ready for the robot invasion? Or are you just plain worried that your job will be automated away? The age of artificial intelligence is not simply here but has permeated through our very existence already. From forecasting market trends to reordering your groceries that were going low to being delivered by drones, artificial intelligence is all around our lives and the way we do business. When we talk about artificial intelligence, its focus centers around adding and, more importantly, enhancing our current capabilities.
AR and thermal imaging in the Qwake C-Thru mask could help firefighters better navigate burning buildings. With smoke, flames and a claustrophobic mask on, running into a burning building is a leap of faith. Firefighters are taught never to leave the wall, because they could become disoriented, run out of air and die. "The way we used to look for people was almost as if you were blind," said Harold Schapelhouman, fire chief of the Menlo Park Fire Protection District. That could change with technology like Qwake's C-Thru.
Disease Diagnosis & Medication: Data privacy and regulatory barriers will cause a delay in disrupting this segment. If the patient is able to access their own data, they should be able to use AI for diagnosis of their X-rays or MRI scans as a second opinion. A soldier in war zones can get the AR/VR experience with instructions to help treat themselves and remove a bullet. DNA based personalized medicine to extend the life of humans. Robots to remind you to take medicine pills (e.g.
The race to fully autonomous vehicles is on. In April, Elon Musk declared that Tesla should have over a million level 5 autonomous vehicles manufactured by 2020. To clarify, that means over a million cars equipped with the necessary hardware capable of driving with no help from a driver. In addition, government approvals will be necessary (read: mandatory) long before self-driving Teslas will be commonplace. In addition, Musk also sparked some lively debate when he commented that Tesla will not be relying on lidar, the laser sensor technology that self-driving cars from many other companies (most notably Google's Waymo) currently depend on for "seeing" lines on the road, pedestrians, and more.
There is no better way to learn coding and AI than getting some hands-on practice. You can teach the robot to follow objects, avoid collisions, and a whole lot more with simple tutorials available. It is compatible with TensorFlow, PyTorch, Caffe, and MXNet frameworks. The kit includes a Leopard Imaging 145FOV wide angle camera, EDIMAX WiFi Adapter, SparkFun Micro OLED Breakout, and all the parts you need to get started.
Scale AI Inc., a three-year-old startup run by a 22-year-old, is teaching machines how to see. For that, it just joined Silicon Valley's list of unicorns with a fresh $100 million investment that puts its valuation above the coveted $1 billion mark, and its artificial intelligence (AI) technology has already attracted big-name customers in the field for autonomous vehicles, according to Bloomberg. Alphabet Inc.'s (GOOGL) Waymo, General Motor Co.'s (GM) Cruise, and Uber Technologies Inc. (UBER) are all buying what Scale has to offer, because well, self-driving cars are machines that need to be able to see. Scale stands out because it has built a set of software tools that are significantly reducing the time it takes to train a machine how to process and interpret visual imagery. And less time means lower costs.
We are a Ukraine-based company which means that our parents and grandparents lived in the era of infamous Soviet collective farms, where tractors were considered to be an ultimate technology. For them, a smart farm will sound like a fairy tale. So let it be, a fairy tale of a smart farm. First of all, what is a smart farm? Smart Farming is a concept of farming management using modern Information and Communication Technologies to increase the quantity and quality of products.
AI computing needs high levels of data processing and conventional AI systems function by transmitting data to a cloud server to be processed. Insights about the data and the decisions to be taken by the system are then transmitted back to connected devices. This approach works fine but for the rapidly increasing number of IoT devices, this is not ideal. There are issues both with the processing power, cloud connectivity and battery capacities in the mobile devices. While connected devices are not ideal to support large data crunching, sometimes they are designed for purposes that need insights in real-time, such as in self-driving cars or in anomaly detection systems.
Should Elon Musk's robot-surgeon start inserting electrodes into human brains to connect humans and computers via a high-bandwidth brain-machine? What exactly are the implications for medical insurance? Should a self-driving flying taxi crash and kill civilians? These are the questions our CEO, Lizé Lambrechts, is asking. The insurance industry is developing new ways to assess and underwrite risk as artificial intelligence (AI) and automation advance.
Nvidia CEO Jensen Huang proudly proclaimed on an analyst earnings call this week that artificial intelligence is the "single most powerful force of our time." Nvidia reported Q2 earnings and revenues that beat analysts' expectations as demand for graphics and artificial intelligence chips picked up. After the earnings call, I interviewed Huang about the company's progress. During the analyst call, he said there are more than 4,000 AI startups working with the company -- as compared to 2,000 AI startups in April 2017. In our interview, Huang said the actual number of AI startups Nvidia is tracking is closer to 4,500.