Personalisation today is a must, not longer a maybe. Research from BCG suggests that brands which create personalised experiences by integrating advanced digital technologies and proprietary data for customers are seeing revenues increase by 6% to 10% – two to three times faster than those that don't. The need for personalisation has infiltrated a wide variety of industries. Why do you think you can personalise your Coke with your own name, or get the perfect song recommended on Spotify? The travel industry has slowly started to go in the same direction.

Martin Welker is the chief executive of Axonic. Even with the support of AI frameworks like TensorFlow or OpenAI, artificial intelligence still requires deep knowledge and understanding compared to a mainstream web developer. If you have built a working prototype, you are probably the smartest guy in the room. Congratulations, you are a member of a very exclusive club. With Kaggle, you can even earn decent money by solving real-world projects. All in all, it is an excellent position to be in, but is it enough to build a business?

Egyptian company AvidBeam won the award for best emerging company in the field of artificial intelligence in the world during the CES Exhibition and Conference held in Las Vegas, USA. During the first day of the exhibition, the Egyptian company won a competition organised by Trend Forward Capital, one of the world's largest financiers of start-ups. AvidBeam is partaking in CES Conference as part of the Egyptian delegation of eight companies. Founding Partner of AvidBeam, Hossam Samy, said that the company is working in the field of innovative solutions, analysing video to automatically find the important commercial and security information they contain. It also outputs simple reports on commercial and security operations to achieve maximum efficiency.

Chris Manson, 50, is chief executive of Newable, a provider of advice and loans controlled by the 33 London boroughs and the City of London Corporation. Newable, which bought the London Business Angels network last year, invests in funding rounds of up to £2m, focusing on space, digital healthcare and artificial intelligence. It has backed medical device business Oxtex and Advizzo, a developer of machine learning software. Professional angels Angel investing has been a bit of a cottage industry. It sprang up from clubs and networks of like-minded people. To get scale, it needs to become a professional service.

We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition. MILABOT is capable of conversing with humans on popular small talk topics through both speech and text. The system consists of an ensemble of natural language generation and retrieval models, including neural network and template-based models. By applying reinforcement learning to crowdsourced data and real-world user interactions, the system has been trained to select an appropriate response from the models in its ensemble. The system has been evaluated through A/B testing with real-world users, where it performed significantly better than other systems. The results highlight the potential of coupling ensemble systems with deep reinforcement learning as a fruitful path for developing real-world, open-domain conversational agents.

Google just announced significant enhancements to its machine learning services (MLaaS), attempting to close the significant competitive gap that Microsoft has enjoyed, in my opinion, for the last year or so. Not to be left out, Amazon.com AWS announced the company's own new MLaaS tools and services at AWS Re:Invent last November, trying to court AI application developers to build their smart apps on the AWS cloud. MLaaS is still in its infancy today, but it may become a dominant AI platform for enterprises who would prefer to leave all the messy details to someone else, and rent AI services by the click. This article summarizes each company's strategies and tactics and tries to size up the winners and losers.

For a species that's conquered Earth and traveled through space and invented the Slapchop, we humans sure are insecure when it comes to technology. Our greatest fear: the singularity, when the abilities of AI and robots surpass those of humans, growing so advanced that civilization is forced to reboot as humanity spirals into existential dread. Or worse, the machines turn us into batteries, à la The Matrix. As fun as that all sounds, UC Berkeley roboticist Ken Goldberg thinks the singularity is bunk. "I think it's counterproductive," he says.

Google just announced significant enhancements to its machine learning services (MLaaS), attempting to close the significant competitive gap that Microsoft has enjoyed, in my opinion, for the last year or so. Not to be left out, Amazon.com AWS announced the company's own new MLaaS tools and services at AWS Re:Invent last November, trying to court AI application developers to build their smart apps on the AWS cloud. MLaaS is still in its infancy today, but it may become a dominant AI platform for enterprises who would prefer to leave all the messy details to someone else, and rent AI services by the click. This article summarizes each company's strategies and tactics, and tries to size up the winners and losers.

MeetAI London and NeurotechX want to join efforts and bring together a selected panel of experts in diverse aspects of machine learning and neuroscience. An open discussion centred around how this two fields work together, the current achievements, and the future goals and limitations. Neuroscience and artificial intelligence are heavily related and both are living a golden age. Machine learning has been inspired by the nervous systems since its first steps. Terms such as neural networks or reinforcement learning have been borrowed from natural sciences and translated into silicon.

The Future is Quantum with Dr. Krysta Svore If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you're in good company: some of the world's smartest people admit they don't really understand it either. Fortunately, some of the world's other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC – group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality. Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world's biggest problems, explains why Microsoft's topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer's equivalent of Schroedinger's Cat. Krysta Svore: The problems we're looking at solving with a quantum computer are the problems that, today, require age-of-the-universe time scales. I'm not going to be around for that solution. Some of these problems literally require billions and billions and billions of years to solve. And on a quantum computer, what we've shown in some recent research, is that you can solve some of these problems in a matter of say, weeks, days, hours, seconds. I'll be around for those solutions. A show that brings you closer to the cutting edge of technology research and the scientists behind it. If someone mentions quantum computing and you find yourself outwardly nodding your head but secretly shaking it, you're in good company. Some of the world's smartest people admit they don't really understand it either. Fortunately, some of the world's other smartest people, like Dr. Krysta Svore, Principle Research Manager of the Microsoft Quantum, or QuArC, Group at Microsoft Research in Redmond, actually do understand quantum computing and are working hard to make it a reality. Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world's biggest problems, explains why Microsoft's topological quantum bit – or qubit – is a game-changer for quantum computing and assures us that although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmers equivalent of Schrödinger's Cat. Your research revolves around quantum algorithms.