For millennia, we surpassed the other intelligent species with which we share our planet -- dolphins, porpoises, orangutans, and the like -- in almost all skills, bar swimming and tree-climbing. In recent years, though, our species has created new forms of intelligence, able to outperform us in other ways. One of the most famous of these forms of artificial intelligence(A.I.) is AlphaGo, developed by Deepmind. In just a few years, it has learned to play the 4,000-year-old strategy game, Go, beating two of the world's strongest players. Other software developed by Deepmind has learned to play classic eight-bit video games, notably Breakout, in which players must use a bat to hit a ball at a wall, knocking bricks out of it.

The Artificial Intelligence (AI) market is booming, with nearly every major player in the enterprise space vying for a foothold. IBM, Amazon, GE, Microsoft, Google, Cisco, SAP, HPE, Verizon--you name it, anybody and everybody, even folks who used to sell hardware--are actively working on and/or want to stake a claim in a piece of the AI pie. What encompasses the AI market? Machine learning, natural language processing (NLP), voice recognition and image processing, application and geography are what we're looking at, with mobile devices and cloud being the enablers. And just what will the AI market be?

Now if these are not dominant steps toward a world of AI I don't know what is. Front this technology with a robot body and it becomes an intelligent being. They can park themselves, drive themselves, break automatically and navigate based on coordinates. Once they are able to learn and map out routes as well as incorporate traffic reports and weather disturbances to get you quickly and safely from A to B without risk…bingo. Google Assistant, Amazon Echo, Apple Siri and the other personal virtual assistants are bringing all daily rituals, habits and requests together via one central point.

In the not-too-distant future, our fields could be tilled, sown, tended and harvested entirely by fleets of co-operating autonomous machines by land and air. Driverless tractors that can follow pre-programmed routes are already being deployed at large farms around the world. Drones are buzzing over fields assessing crop health and soil conditions. Ground sensors are monitoring the amount of water and nutrients in the soil, triggering irrigation and fertiliser applications. And in Japan, the world's first entirely automated lettuce farm is due for launch next year.

TechCrunch Disrupt in London is on December 5-6. As well as speakers and panels, we'll be featuring some demos by some amazing tech companies. The first will be by Boston Dynamics. Yes, folks, delegates to Disrupt London will get to see one of those amazing BD robots up close and personal, almost literally in the flesh (if they had any flesh, that is). Marc Raibert, CTO and Founder of Boston Dynamics will be demonstrating one of the amazing robots his team has created, but you'll have to come to find out which one… Raibert was Professor of Electrical Engineering and Computer Science at MIT and a member of the Artificial Intelligence Laboratory from 1986 through 1995.

Researchers from Google's AI division DeepMind and the University of Oxford have used artificial intelligence to create the most accurate lip-reading software ever. Using thousands of hours of TV footage from the BBC, scientists trained a neural network to annotate video footage with 46.8 percent accuracy. That might not seem that impressive at first -- especially compared to AI accuracy rates when transcribing audio -- but tested on the same footage, a professional human lip-reader was only able to get the right word 12.4 percent of the time. The research follows similar work published a separate group at the University of Oxford earlier this month. Using related techniques, these scientist were able to create a lip-reading program called LipNet that achieved 93.4 percent accuracy in tests, compared to 52.3 percent human accuracy.

IN THE control room at Ocado's automated warehouse in Hatfield, 50 kilometres north of London, the firm's head of research is wielding something rather odd: an Xbox game controller. But Alex Harvey is not about to zap some aliens. Instead, with a deft twitch of his thumb, he zooms into a 3D computer model that looks, at first glance, like some kind of bizarre, multilayered train set. But this is actually an animated, real-time visualisation of the thicket of over 30 kilometres of conveyor systems in a warehouse the size of eleven football fields. It models the movement of thousands of crates around the conveyor belts to workstations where just a few human workers pack them to fulfil hundreds of thousands of online grocery orders every week.

SAP chief executive Bill McDermott is preparing the German software giant for the next big trend in the world of technology: artificial intelligence. The company is working hard to become the market leader in machine learning for businesses, its CEO told Handelsblatt. CEO Bill McDermott wants SAP to focus heavily on developing intelligent applications for business software and experts say there is enormous potential in artificial intelligence and machine learning. Under the leadership of its American chief executive, the German software group has acquired companies for €20 billion ($21.3 billion) since 2010 so as not to miss out on cloud computing. It's been a successful move as the company's quarterly figures show.

Quantum control is valuable for various quantum technologies such as high-fidelity gates for universal quantum computing, adaptive quantum-enhanced metrology, and ultra-cold atom manipulation. Although supervised machine learning and reinforcement learning are widely used for optimizing control parameters in classical systems, quantum control for parameter optimization is mainly pursued via gradient-based greedy algorithms. Although the quantum fitness landscape is often compatible with greedy algorithms, sometimes greedy algorithms yield poor results, especially for large-dimensional quantum systems. We employ differential evolution algorithms to circumvent the stagnation problem of non-convex optimization. We improve quantum control fidelity for noisy system by averaging over the objective function. To reduce computational cost, we introduce heuristics for early termination of runs and for adaptive selection of search subspaces. Our implementation is massively parallel and vectorized to reduce run time even further. We demonstrate our methods with two examples, namely quantum phase estimation and quantum gate design, for which we achieve superior fidelity and scalability than obtained using greedy algorithms.

Companies like Google, IBM and SAP are making massive investments in artificial intelligence. German software maker SAP is investing heavily in artificial intelligence, or AI, especially for business software. AI is expected to fundamentally change our lives in the near future. Cars that navigate autonomously through traffic. Digital assistants that provide doctors with key information needed to make a diagnosis.