Chip maker Intel Corporation has acquired Itseez, a company specializing in computer learning and machine learning. Itseez is said to bring its expertise in advanced driver assistance systems (ADAS) for automobiles to Intel. The move is likely a part of Intel's growing IoT-related ambitions. The firm recently acquired Yogitech, an Italian company manufacturing safety measures for semiconductors. The value of the deal it's not been disclosed.

Remember those little six-wheeled robots we told you about in April? They're now set for a commercial rollout in London and three other European cities. The robots, from Starship Technologies, will be deployed this month to make deliveries for food-ordering services Just Eat and Pronto, and carry packages for courier service Hermes and supermarket Metro Group. The Starship delivery bots will be stationed at kitchens, delivery hubs, and supermarkets in London, Düsseldorf, Bern, and Hamburg. When an order comes in, the bots will drive themselves to collect their cargo, store it in their holds (which can take about two shopping bags' worth of stuff), then trundle on to their destinations.

Philippines' outsourcing industry races to expand higher-end services as hedge against automation, which is shaking up India

This has been the year of the chatbot. Siri opened up to developers recently. The Facebook Messenger bots arrived. The Slack App Store continues to evolve quickly with hundreds of bots. Chatbots have been in many ways disappointing to me, but they are an important step in the evolution of conversational technology.

Self-driving robots will soon start delivering food and groceries. This month Starship Technologies is rolling out its six-wheeled delivery robots in London, Dusseldorf, Bern, and Hamburg, Quartz reports. The robots will be used by two food delivery services in those areas, Just Eat and Pronto, as well as courier service Hermes and grocery store Metro Group. Starship hopes that this new technology will help cut both the time and costs associated with delivery. The self-driving robots won't exactly be self-driving at first.

Moodstocks, a Parisian startup that develops image recognition tools for smartphones, is joining Google. The companies announced the acquisition today, sans financials. Around since 2008, Moodstocks hasn't had considerable traction. But the company has tech and engineers working on machine learning, something Google cannot get enough of as it competes with rivals like Apple and Facebook for talent. And Moodstocks' core service -- "to give eyes to machines by turning cameras into smart sensors," as its parting note described -- fits with Google's vision for image search and augmented reality, where a phone (or something else) knows your physical surroundings. Also, the acquisition price may have been low thanks to wobbling global markets.

Few environmental limits are as obvious to people today as water availability. Particularly in drier climates, availability can be a pretty unforgiving equation. Even there, a family might pay less for water than for cell phones, but there is often a pretty complex system behind your tap that keeps it running. The challenge of water availability rises beyond engineering. It becomes a delicate dance managing demand, forecasting supply, and sustaining ecosystems. Decisions have to be made based on information that is never complete, so any opportunity to obtain more useful information is liable to get a thirsty look from water managers.

More than 1.5 billion people use Facebook. And only half speak English. The rest speak so many dozens of other languages, effectively silo'd off from the English speakers and, in many cases, from each other. If you stumble onto a Facebook post in a foreign language, Facebook lets you instantly translate it--in a semi-effective way. And beginning today, millions of people will have the option of instantly translating their own posts into any one of 44 other languages, so that they will automatically show up in your News Feed in your native tongue.

Enterprises today are finding it exceedingly meaningful and resourceful in the massive amounts of data they generate and save every day. The required algorithms, applications and frameworks to bring greater predictive accuracy and value to enterprises' data sets are available; therefore, businesses need to make sure they have data sets of sufficient size and quality. It is due to the excessive need to do a better job in capturing and utilizing data. The rise of deep learning and neural networks has spread in everyday lives. It took about six years for neural nets to show impressive results, first in speech recognition, then computer vision, images, image detection and diagnostics, and more recently, in natural language processing.

Studies suggest that relying on your smartphone heart monitor may not be the wisest move. The widespread use of smartphones to collect healthcare data has been thrown into doubt by a couple of recent studies. In some fields -- such as the management of chronic diseases and mental health monitoring smartphones have enabled a greater level of patient self-control, and personalised clinical intervention. Success in one area, however, does not imply success in all – especially as smartphone health apps are often rolled out before evidence of their effectiveness has been rigorously analysed. A major study into the use of mobile phone data as a tool for predicting clinical decisions, released in June, came to a scathing conclusion, characterising the practice as "voodoo machine learning".