There is a definition of a Fourth Industrial Revolution (4IR) as the age of digitalization. This is making smart cities, vastly improved factories and a lot of automation of tasks and services in our homes and at work. Industry 4.0 enables real-time data gathering, analysis, and decision- and prediction-making capabilities. Nextbigfuture would indicate that this 4IR is just an extension of the third industrial revolution of computers and robotic automation. The adoption levels of computers and robots are too low and the impact on factory and production levels has not reached the level of improvements reached by the Ford factories and oil machinery over the steam age.

Autonomous vehicles make use of sensors and complex algorithms to detect and respond to their surroundings. Thanks to these technologies, autonomous vehicles don't necessitate a driver to complete even complex journeys. Additionally, multiple autonomous vehicles can communicate with each other to improve traffic and obstacle avoidance. The evolution in automation levels of cars is summarised in Figure 1. Many companies such as Waymo and Tesla are now hugely investing in a future lead by Autonomous vehicles (self-driving cars).

Glowing stickers are able to confuse deep learning systems. Deep Learning expert Geoffrey Hinton believes simple adversarial attacks show that Deep Learning has flaws. Deep Learning flaws * The systems needs 10,000 examples to learn a concept like cows. Humans only need a handful of examples * Deep Learning cannot explain how the systems got an answer * Deep Learning lacks common sense. This makes the systems fragile and when errors are made, the errors can be very large.

Roborace is the world's first competition for human AI teams, using both self-driving and manually-controlled cars. Race formats will feature new forms of immersive entertainment to engage the next generation of racing fans. Through sport, innovations in machine-driven technologies will be accelerated. A self-driving car has set a speed record of 175 mph. In November 2017, Musk said the next Tesla Roadster would have three motors and be able to travel a whopping 0 to 60 miles per hour in 1.9 seconds with a top speed of 250 mph or even more.

Tesla bought Deepscale, an artificial intelligence vision company. In January, 2019, DeepScale introduced Carver21 which is AI building blocks for intelligent cars. Carver21 offers a portfolio of perception software modules that give Tier-1s and OEMs the flexibility they need to create modular, scalable ADAS. Carver21 can be used in small SoCs that would be embedded in edge ECUs, which typically require less than 5W power consumption and are still the status quo for the distributed electrical architectures used in today's ADAS. DeepScale's full-stack deep learning methodology enables cohesive integration of AI software with various processors and sensors for customizable automated driving features.

Influencer marketing might seem like a recent invention, but it has always existed. In the past influencers existed as celebrities who promoted products in ads and writers who wrote about products in articles both offline and online. Slowly influencer marketing crept onto social media. Social media influencers have been active for several years on networks like Twitter, Myspace, Facebook, etc. Influencer marketing seems like a recent invention because of the sudden growth on Instagram. Anyone can become an influencer on this network.

Frequently reported advances in artificial intelligence make some people curious, and others nervous. While some people picture their next smart appliance purchase being an AI robot, others wonder if an AI robot will take their job. The truth is, neither of those scenarios will be a reality anytime soon. True AI doesn't exist yet, and it's not a likely near future, either. People get excited when new breakthroughs in machine learning are publicized, like the CNBC interview with a robot named Sophia.

There is a lot of hype for the accomplishments of Artificial Intelligence. Nextbigfuture keeps you up to date about the achievements made in AI. Two hours ago Nextbigfuture published what IBM has done with AI. We marveled at our own magnificence…. Waze and Google Maps use a lot of Artificial Intelligence and real-time updates to provide the best driving instructions.

I believe it is likely that we will have 10,000 qubit quantum computers within 5 to 10 years. There is rapidly advancing work by IonQ with trapped ion quantum computers and a range of superconducting quantum computer systems by Google, IBM, Intel, Rigetti and 2000-5000 qubit quantum annealing computers by D-Wave Systems. They will be beyond not just any regular computer today but any non-quantum computer ever for those kinds of problems. Those quantum computers will help improve artificial intelligence systems. How certain is this development? What will it mean for humans and our world?

Deep Learning and Machine Learning has made breakthroughs in recent years. There is tens of billions of dollars going into development of the new AI. Google and Deep Mind are recognizing that Deep Learning is not going to reach human cognition. They propose using models of networks to find relations between things to enable computers to generalize more broadly about the world. Deep learning faces challenges in complex language and scene understanding, reasoning about structured data, transferring learning beyond the training conditions, and learning from small amounts of experience.