Amazon Web Services (AWS) has connected the Middle East to its global network with the launch of its Bahrain AWS region. The cloud supplier already has infrastructure in the region, but the launch of the Bahrain AWS region, with three datacentres, will connect to its global network. This will bring the Middle East region up to par with its other global AWS regions as the Middle East accelerates its digital transformation. Andy Jassy, CEO at AWS, said the cloud could unlock digital transformation in the Middle East. "Today, we are launching advanced and secure technology infrastructure that matches the scale of our other AWS regions around the world and are already seeing strong demand in the Middle East for AWS technologies like artificial intelligence (AI) and machine learning, data analytics, IoT [internet of things] and much more," he said.
The government's announcement of a £250 million investment into artificial intelligence (AI) is very exciting and will solve some of the healthcare systems most difficult challenges. Although the UK is making leeway in the battle against cancer, the breakthroughs are only significant if early disease detection is made sooner rather than later, helping the treatments work more efficiently. Early detection of various diseases is crucial, and in cases like ovarian cancer, a woman has no symptoms in the early stages. AI and genomics can possibly help detect this cancer early, which means treatments can start sooner and more lives can be saved. AI is already making practical improvements in the healthcare system.
Artificial intelligence is redefining the nature of customer service. According to one analysis by Maruri Tech Labs, 85% of all customer service communications will be handled by an AI system by the end of next year. This is even true in call centers, which are surprisingly being disrupted by AI technology. Although artificial intelligence is going to be extremely important in the future of customer service, it is still too early to determine the degree to which it will be utilized. The question ultimately boils down to the effectiveness of these new systems.
Once a general understanding of true AI is established, the only skepticism remaining typically stems from the fact that businesses looking to implement some type of AI may not trust providers to be honest about their products' capabilities. It's easy to say that a product has AI capabilities, but it's much harder to put true AI into practice. Since true AI will learn and become smarter over time, it's important to ask providers leading questions to determine if their technology has this capability.
The automotive industry isn't just being driven by people -- it's also driven by data, particularly as automobile manufacturers move toward autonomous, self-driving vehicles. Last year, Waymo cars drove 1.2 million miles in California. Meanwhile, Tesla, with its Autopilot program, is actively collecting data from hundreds of thousands of vehicles to predict how its cars might perform autonomously. So far the company has collected hundreds of millions of miles worth of data. What are these autonomous vehicle manufacturers doing with all of that data?
DeepMind's Demis Hassabis once pointed to the human brain as a paramount inspiration for building AI with human-like intelligence. The meteoric success of deep learning showcases how insights from neuroscience--memory, learning, decision-making, vision--can be distilled into algorithms that bestow silicon minds with a shadow of our cognitive prowess. This month, the prestigious journal Nature published an entire series highlighting the symbiotic growth between neuroscience and AI. It's been a long time coming. At their core, both disciplines are solving the same central problem--intelligence--but coming from different angles, and at different levels of abstraction.
The'AI Apocalypse' might kill humanity before any actual robot uprising Education Images/Universal Images Group via Getty Images You can think of artificial intelligence (AI) in the same way you think about cloud computing, if you think about either of them through an environmental lens: an enormous and growing source of carbon emissions, with the very real potential to choke out humans' ability to breathe clean air long before a sentient and ornery AI goes all Skynet on us. At the moment, data centers--the enormous rooms full of stacks and stacks of servers that juggle dank memes, fire tweets, your vitally important Google docs and all the other data that is stored somewhere other than on your phone and in your home computer--use about 2% of the world's electricity. SEE ALSO: Can Giant Snow-Blowing Cannons Save Earth From Climate Change? Of that, servers that run AI--processing all the data and making the decisions and computations that a machine mimicking a human brain must handle in order to achieve "deep learning"--use about 0.1% of the world's electricity, according to a recent MIT Technology Review article. The likelihood that figure will grow, it turns out, is quite good.