Almost a year ago, I wrote these words, "Technology has reached the tipping point for me, it moved from a help to a hindrance." The plethora of adrenaline- and endorphin-inducing mobile apps, 24x7 news, notifications, alerts and updates, drip fed my brain and hindered my "deep work and deep thoughts." In Cal Newport's new book titled, Deep Work he posits that most knowledge workers need concentration and substantial time, dedicated and uninterrupted, to produce their best work. He argues that a lot of technologies and open office layouts today inhibit creativity, "deep work" and "deep thoughts," and are the very things that are most highly valued, and one of the key differentiators between humans and robots. Newport argues that we must understand and optimize the conditions that enable our brains to work best. To sum up his argument, constant drip feeding technologies serve to prevent deep thoughts and deep work, our most valuable assets.

Businesses that use artificial intelligence (AI), big data and the Internet of Things (IoT) technologies to uncover new business insights "will steal $1.2 trillion per annum from their less informed peers by 2020." So says Forrester in a new report, "Predictions 2017: Artificial Intelligence Will Drive The Insights Revolution." Across all businesses, there will be a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. Through the use of cognitive interfaces into complex systems, advanced analytics, and machine learning technology, AI will provide business users access to powerful insights never before available to them. It will help, says Forrester, "drive faster business decisions in marketing, ecommerce, product management and other areas of the business by helping close the gap from insights to action."

With the advent of photography, a tiny fraction of 19th-century scientists believed they could develop methods of accurately identifying criminals by their facial features. While their hypotheses were eventually discredited, new artificial intelligence technology suggests their claims might've been valid after all. Xiaolin Wu and Xi Zhang from Shanghai Jiao Tong University in China have resurrected this facial recognition tradition and built a neural network that can supposedly pick out criminals by simply looking at their faces. TNW Conference is back for it's 12th year. To accomplish this, the researchers used an array of machine-vision algorithms to examine a series of facial juxtapositions between photos of criminals and non-criminals with the goal of finding out whether a neural network can reliably tell them apart.

As tech giants make bigger leaps into artificial intelligence, they see marketers as key customers for a variety of services and are promising more nuance and layers than the technology's early days might suggest. Companies such as IBM, Salesforce and others believe AI has the potential to transform marketing as much as the digital revolution has over the past several years. IBM, which first made an AI media splash in 1997 when its Deep Blue supercomputer beat chess champion Garry Kasparov, has emerged as an early market leader with newer, smarter Watson software. Google is also ramping up R&D spend on AI; Microsoft is integrating AI across its enterprise; Facebook is building out facial recognition AI for basic user experiences and Salesforce is championing a new platform called Einstein to help optimize for individual customer data. In late September, all of these companies and others banded together to create the Partnership on Artificial Intelligence to Benefit People and Society, a group with the objective of addressing opportunities and challenges, along with standards and best practices, for AI developers.

Artificial Intelligence (AI) is changing everything from marketing to healthcare. And this holiday season is the beginning of the future for how marketers will leverage AI to better understand, connect with, and create superior experiences for consumers. To better appreciate the impact that AI is having on retailers, I connected with IBM's first CMO, Michelle Peluso. Peluso has a strong background in retail, having served at the CEO of Gilt as well as the Global Consumer Chief Marketing and Internet Officer at Citigroup. Peluso provides her thoughts below on how Watson's AI capability is changing the way retailers impact the consumer shopping experience.

AWS has announced three new features for its artificial intelligence portfolio at re:Invent 2016 in Las Vegas this week. Artificial intelligence is a development which could have wide ranging impacts on businesses throughout the world, and while many have been sceptical about its effectiveness the technology is starting to make waves. Google recently announced a few changes to the way its translation tool works with AI, IBM's Watson seems to be making progress constantly and Salesforce's Einstein is paying off with the company growing year-on-year. Considering the normalization of artificial intelligence and growing acceptance in the technology world, it wasn't going to be long before the public cloud leader started making itself known. And sure enough just in time for Christmas, the AWS team has put forward three new features for developers to play with.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

It's one thing to create computers that behave like brains, but it's something else to make them perform as well as brains. Conventional circuitry can only operate so quickly as part of a neural network, even if it's sometimes much more powerful than standard computers. However, Princeton researchers might have smashed that barrier: they've built what they say is the first photonic neural network. The system mimics the brain with "neurons" that are really light waveguides cut into silicon substrates. As each of those nodes operates in a specific wavelength, you can make calculations by summing up the total power of the light as it's fed into a laser -- and the laser completes the circuit by sending light back to the nodes.

For a long time, hiring in India (or for that matter anywhere in the world) meant candidates would have to be active on job portals and scout through the various jobs listed. It would then be up to the recruiter of a company to go through all the CVs and schedule interviews with potential candidates and the entire process took around four to five months. As companies run into increasingly competitive talent markets, recruiting costs and cycles are escalating. To overcome these challenges and help businesses meet their goals, recruiting teams need radically new capabilities and technologies, something Bengaluru-based startup Belong is helping companies to achieve. Basically, the premise is simple: for an employer and potential employee to connect with each other they must connect on something beyond skills and experience.