Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services. CEO Sundar Pichai and other top executives brought Google's audacious ambition into sharper focus Wednesday at an annual conference attended by more than 7,000 developers who design apps to work with its wide array of digital services. Among other things, Google unveiled new ways for its massive network of computers to identify images, as well as recommend, share, and organize photos. It also is launching an attempt to make its voice-controlled digital assistant more proactive and visual while expanding its audience to Apple's iPhone, where it will try to outwit an older peer, Siri. The push marks another step toward infusing nearly all of Google's products with some semblance of artificial intelligence – the concept of writing software that enables computers to gradually learn to think more like humans.

Google will make it harder for that friend in your group to make excuses when chipping in for food. The tech titan's voice assistant will be able send personal payments for you in the coming months, just like its rival Siri can, so long you're in the US. Simply tell it to "Send John $10 for pizza" or something similar and authenticate the transaction with your fingerprint or password to send cash. Your recipient will then receive an email about your payment. The big G recently tweaked its API to make any card associated with your account available on all its apps and on third-party applications that use Google Payments.

A future driven by AI technology has just been outlined by the CEO of Google, Sundar Pichai, during his keynote address at Google IO 2017. Pichai stated "the more we democratise access to AI, the sooner everyone will benefit". This vision was backed up by announcing a number of AI driven technologies including improvements to Google Home, Google Assistant and the all new Google Lens -- an object recognition system that uses a smartphone camera and machine learning to interpret the world around you. This is another major step toward a machine driven future -- a movement that has garnered a lot of attention in recent years. AI isn't a new technology and has been applied to plenty of digital systems for decades.

Food delivery company DoorDash says personalized restaurant recommendations based on AI are seeing a significant lift in orders, compared to regular recommendations based on popularity. In an interview with VentureBeat, DoorDash product manager Jimmy Liu said customers who saw personalized recommendations on average "were over 25 percent more likely" to place an order versus people who saw the most popular restaurants in their area. We talked with Liu on the eve of the company's announcement today that it's rolling out these machine-learning based recommendations to all of its users, after testing it on increasing percentages of its customer base. Millions of users have already seen the recommendations, the company said. Liu said the 25 percent lift from recommendations came specifically from email campaigns.

Machine Learning is the buzzword of the moment. In recent years, news stories raving about its possibilities have soared, Google searches for the term have quadrupled, and companies across the globe have been scrambling to figure out how to capitalize on the excitement by bringing it into their product mix. While that can be a great thing, claims made by some businesses about what Machine Learning can do are wildly exaggerated. That makes it crucial to cut through the noise and get to grips with its potential, limitations, and what you can realistically achieve with your resources so that any investment makes solid business sense -- so say Philip Lima, CEO of Mashey, and Boaz Farkash, Head of Product Management at Sisense. The pair joined forces to deliver an in-depth webinar on Machine Learning and business intelligence, which you can view in full here.

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MOUNTAIN VIEW, Calif.--If you own an iPhone, there's yet another way to talk with an artificial intelligence trained on the whole internet and beamed down to your handset from a cluster of computers somewhere in the world. Tuesday, Google made its artificial-intelligence powered Assistant available for the iPhone. The service, which uses a conversational interface to do things and provide information for users, has been available on Android phones since spring of last year. The move brings the company's voice interface into direct competition with Apple's own Siri. For the first time, you can now have both assistants on the same phone in your palm.

As PSD2 is set to open data sharing between banks and third parties, banking and fintech professionals should heed this warning: Don't confuse digitization with digital strategy. You need to build mobile apps and digital experiences for your customers. They expect it, so you should deliver. But a series of mobile experience projects doesn't constitute a digital strategy. To appreciate the difference, we'll look at a topic outside of banking and fintech--AI (artificial intelligence) assistants.

Over the last several decades, the evolution of artificial intelligence has followed an uncertain path – reaching incredible highs and new levels of innovation, often followed by years of stagnation and disillusionment as the technology fails to deliver on its promises. Today we are once again experiencing growing interest in the future possibilities for AI. From voice powered personal assistants like Google Home and Alexa, to Netflix's predictive recommendations, Nest learning thermostats and chatbots used by banks and retailers, there are countless examples of AI seeping into everyday life and the potential of future applications seem limitless . . . Despite the mounting interest and the proliferation of new technologies, is this current wave that much different than what we have seen in the past? Do the techniques of the modern AI movement – machine learning, data mining, deep learning, natural language processing and neural nets – deserve to be captured under the AI moniker, or is it just more of the same?

Music streaming service Spotify on Wednesday disclosed it has acquired the team and technology behind Niland, a French start-up with a service for delivering music recommendations. The move signals that Spotify wants to incorporate more artificial intelligence (AI) into its system as it fights off competition from alternatives like Apple Music. Niland is not well-known in the field of AI. But for years its CEO, Damien Tardieu, has done research on ways to extract meaningful information from raw music content in order to form connections with other music. This approach differs from collaborative filtering, one of the techniques that Spotify and others use.