Subject matter experts are hard to come by when looking to hire in specialized areas. However, many companies do not realize that the specialties they are seeking already exist in their organization – using data connection. With proper data connection powered by artificial intelligence and machine learning, subject matter experts can be identified internally, which helps to – reduce costs and get the most out of your existing workforce. In addition, data connection and a holistic approach to knowledge management give other employees the ability to know what the experts know with just a few clicks. Valuable data sits all around your company in different data sources.

Data integration is one of the most crucial resources within every business. As a matter of fact, data is one of the most expansive and complex resources that's difficult to process and manage. As a business expands, the amount of exact data it needs to integrate, analyze, and load will also grow. Organizations continue to add new, disparate systems as well as applications at a fast pace. Which ultimately increases data volume.

Ever wanted to build a chatbot and encountered some blockers along the way relating to data privacy or supported languages? Do you wish to reduce chatbot response time or run them without an active data connection? If that's the case or if you're just curious and want to learn more, give NLP.js a try. Natural Language Processing or NLP is a field combining linguistics and computing, as well as artificial intelligence. Correctly understanding natural language is critical for virtual assistants, chatbots, voice assistants, and a wide range of applications based on a voice or text interface with a machine.

Outer space is unfriendly to humans. We can only exist in a contained environment with its own air supply, so that means working in very close quarters. Zero gravity means things don't stay where you put them. Despite these constraints, astronauts on the International Space Station (ISS) must be highly productive on a very tight time schedule. They conduct hundreds of experiments they've memorized and trained for on the ground, but now in zero-gravity.

Google's Pixel phones are the company's preferred way of showcasing its AI chops to consumers. Pixel phones consistently set the phone camera bar thanks to Google's AI prowess. But many of the AI features have nothing to do with the camera. The Pixel 4 and Pixel 4 XL unveiled this week at the Made by Google hardware event in New York City continue this tradition. Camera improvements aside, the Pixel 4 makes a play for a new arena that Google clearly wants to rule: offline natural language processing.

Accessing the data is one of the biggest struggles that I encountered in my career as Data Scientist which I never expected after my academic training. It might sound ridiculous and slightly naive, but I graduated believing that my stakeholders would stand ready with a data connection established to have their data sets analyzed by me, The Data Scientist. I quickly learnt how wrong I was. Issues about data accessibility or data extraction happen commonly in large companies full of complex processes and compliance regulations. Nonetheless, smaller organizations can undeniably experience similar issues.

Globe Telecom is the leading full service telecommunications company in the Philippines, serving the needs of consumers and businesses across an entire suite of products and services including mobile, fixed, broadband, data connections, internet and managed services. Accounting for more than 50% of the Philippines' mobile revenues, Globe Telecom leads the mobile market, while also generating one-third of the country's fixed broadband revenues and enterprise data connections. To enhance customer experience for its 60 million customers, Globe Telecom looked into the use of machine learning to deliver real-time targeted marketing and optimised products and services, while maintaining compliance with the latest industry data regulations in the country. According to Chief Technology and Information Officer and Chief Strategy Officer of Globe Telecom Mr Gil Genio, the company strives to enable its customers to live a digital lifestyle that is supported by its robust and pervasive mobile network. Given the increasing number of Internet of Things (IoT) devices, Globe Telecom's mobile data volumes grew by 66% in 2017, reaching 600 petabytes (PB).

Dirty money and money laundering have been around since the existence of currency itself. On a global level, as much as $2 trillion is washed annually, estimates the United Nations. Today's criminals are sophisticated, using ever-adapting tactics to bypass traditional anti-fraud solutions. Even in cases where enterprises do have enough data to reveal illicit activity, more often than not they are unable to conduct analysis to uncover it. As the fight against money laundering continues, AML (anti money laundering) compliance has become big business. Global spending in AML alone weighs in at more than $8 trillion, says WealthInsight.

Think the name "Google," and for most, the first thing that comes to mind is the company's founding, eponymous product: Google Search. But it soon might be A.I. Google's first, and still most profitable venture has become so popular for web searches that its name is now the verb to search, and yet in a call to investors Thursday, reporting the company's Q1 2017 earnings, Google CEO Sundar Pichai said the company's in translation. "We continue to set the pace in machine learning and A.I. research," Pichai said on the Thursday call. But just what does it actually mean to transition to an A.I.-first company, and why would Google be willing to upset the system that made it 2017's most highly valued company in the world? For Google, becoming "A.I-first" means putting machine learning at the heart of every one of its platforms.

Prompted by an activation phrase, Dragon Drive recognizes a driver named Lior by his voice. Voice command in cars shows so much potential to help drivers keep their eyes on the road, but since its implementation, the technology largely resulted in frustration. Sure, placing a call to a specific contact usually works, but just try finding a destination in the navigation system. It becomes worse when the car doesn't show what commands it understands. Nuance, the company behind the majority of voice systems in cars, thinks it has the problem licked through the use of machine learning and the cloud, essentially equipping cars with a virtual assistant.