Lego's next release is a digital brick loaded with sensors that add new layers of interactivity to its play sets. WIRED got exclusive access to the Lego labs where the Smart Brick was born. The secretive division of 237 staff based here and in London, Boston, and Singapore is dedicated to thinking up what comes next for the world's largest toy brand. In front of me, on a plain white table, is a batch of prototypes of Lego's new Smart Brick, the final version of which is a small, sensor-laden 2-by-4 black brick with a big brain. No outsider has seen these prototypes, all of which represent stages of a journey Lego has been charting over the past eight years. Lego hopes this innovation, which lands in stores March 1, will safeguard the future of its plastic empire. The diminutive proportions of the finished Smart Brick belie the fact that the thing is exceedingly clever. Inside is a tiny custom chip running bespoke software that can communicate with onboard sensors to monitor and react to motion, orientation, and magnetic fields. It's also likely no exaggeration that the Smart Brick could represent the most radical product Lego has produced since Jens Nygaard Knudsen, the company's former longtime chief designer, created the minifigure nearly 50 years ago.

AI is approaching the next level of maturity, coming out of the hype cycle, says Gartner. Its adoption is expanding across industries beyond automation to building new-generation intelligent products and services for business growth. However, half of them acknowledge that they don't have skilled talent to make the most of AI advances. This is where experienced AI consulting firms come in to help. The market of AI consulting is vast, ranging from tech giants like IBM and Accenture to Big 4 firms and smaller-scale innovators.

Google CEO Sundar Pichai has described the advent of artificial intelligence (AI) as more revolutionary than the discovery of fire or electricity. According to PwC, it has the potential to contribute $15 trillion to the global industry by 2030. I have worked with countless organizations on their AI strategies; however, companies wanting to capitalize on AI face significant barriers regarding the skills and resources needed to put it to use. To bridge this gap, many businesses turn to AI consultancies. These experts have the specialized knowledge and experience required to help companies deploy AI to create more intelligent products and services, improve their internal processes, and ultimately make better use of the data available to them. One of the most frequently asked questions I get from clients is: can you recommend an AI consulting firm to help us turn our AI ambitions into practice?

The clamour of anticipation around new applications for artificial intelligence is as fevered as ever. The problem for me is that expectations are not informed by a robust appreciation of the practical requirements for innovating with AI. As an adviser to businesses on bringing such innovation to market, my advice is simple: to scale rapidly, large-scale AI-enabled projects must be built on firm foundations to allow multidisciplinary development teams to thrive. Chief among the reasons is that, in engineering terms, developing AI is a complex, non-linear process. Frankly, you can expend a great deal of time and effort with very little progress to show for it.

Watching a child learn is an extraordinary experience. As a proud dad, it delights and inspires me, and as an artificial intelligence (AI) professional, it reminds me that our journey into machine learning (ML) has only just begun. What is particularly incredible about babies and young children, of course, is that they learn incredibly quickly – drawing on building blocks of information and astounding us by picking things up naturally and incrementally. Is that too much to ask of machines? For now, the answer is yes.

Plans to beam 5G signals to the public via drones that stay airborne for nine days at a time have been announced by two UK firms. They want to use antenna-equipped aircraft powered by hydrogen to deliver high-speed connectivity to wide areas. Stratospheric Platforms and Cambridge Consultants say they could cover the whole of the UK with about 60 drones. But telecoms analysts question whether the economic case for this scheme is quite as simple as it sounds. The Cambridge-based companies say they would run the service in partnership with existing mobile operators. They are already backed by Deutsche Telekom, which hopes to trial the technology in rural southern Germany in 2024.

Despite the rapid advances it has made it over the past decade, deep learning presents many industrial users with problems when they try to implement the technology, issues that the Internet giants have worked around through brute force. "The challenge that today's systems face is the amount of data they need for training," says Tim Ensor, head of artificial intelligence (AI) at U.K.-based technology company Cambridge Consultants. "On top of that, it needs to be structured data." Most of the commercial applications and algorithm benchmarks used to test deep neural networks (DNNs) consume copious quantities of labeled data; for example, images or pieces of text that have already been tagged in some way by a human to indicate what the sample represents. The Internet giants, who have collected the most data for use in training deep learning systems, have often resorted to crowdsourcing measures such as asking people to prove they are human during logins by identifying objects in a collection of images, or simply buying manual labor through services such as Amazon's Mechanical Turk.

Picking up someone else's drink at the bar could soon become a thing of the past thanks to an immersive new app that identifies drinks with beams of light. The BEAM app, which is currently in development by Cambridge Consultants, lets customers order and pay for drinks on their phone while still sitting at their table. The BEAM app uses near-field communications and machine vision to link customers' phones with their drinks, helping bartenders to give the right orders to the right people The innovation is the brainchild of Cambridge Consultants, which offers tech-based product and development services. The firm says that the customer experience should be'elevated, not just automated'. Rosie Parrish, User Experience Designer at Cambridge Consultants, said: 'To stand out from the crowd, brands in many different sectors are striving to provide more than just a product or service.' 'They want to create a memorable and meaningful experience for the customer.'

"I say this to everyone in the media world who I talk to," says Darren Atkins, wrapping up our phone interview: "Please, absolutely do not portray this as a hidden agenda to get rid of staff." Atkins is the Chief Technology Office for AI automation at East Suffolk and North Essex NHS Foundation Trust – group of hospitals employing more than 10,000 staff, who serve a quarter of a million people in the South East of England. "If this technology is applied in the wrong way, it can be very threatening," Atkins says. "Our main priority is to free up time for staff to do the work that they should be doing, rather than the work that has no value." Just over a year ago, Atkins led the deployment of virtual workers across his group of NHS hospitals – and according to him, it's been an unqualified success. Patients are missing fewer appointments and staff are happier.

Artificial intelligence (AI) has been a hot topic among IT and business leaders as it promises to be the biggest driver of change in human history. The way we work, live, learn and play will never be the same once AI is infused into all of our devices, cars, appliances and everything else we interact with. CIOs are well aware of this and are looking to use AI as part of their digital transformation strategy. One of the challenges is that people often overestimate what an AI can do and they expect perfection. If there are any mistakes at all, it's back to the drawing board to refine the algorithms or spend more time in the learning phase.