The Internet of Things' killer app might be artificial intelligence. While it may be a stretch to classify artificial intelligence (AI) and its multifaceted offshoot machine learning as true applications, these techs can profoundly change IoT operations. AI makes IoT networks smarter and able to scale as needed without the risk of uncontrollable growth. IoT operations is an ongoing struggle to try to ensure that the thousands or more devices run properly and safely on an enterprise network and that the data that's being collected is both accurate and timely. While the sophisticated back-end analytics engines do the heavy lifting of processing the steady stream of data, ensuring the quality of the data itself is often left to somewhat archaic methodologies.

The Internet of Things' killer app might be artificial intelligence. While it may be a stretch to classify artificial intelligence (AI) and its multifaceted offshoot machine learning (ML) as true applications, these techs can profoundly change IoT operations. AI makes IoT networks smarter and able to scale as needed without the risk of uncontrollable growth. IoT operations is an ongoing struggle to try to ensure that the thousands or more devices run properly and safely on an enterprise network and that the data that's being collected is both accurate and timely. While the sophisticated back-end analytics engines do the heavy lifting of processing the steady stream of data, ensuring the quality of the data itself is often left to somewhat archaic methodologies.

We seem flooded with white papers, summits, meetups, conferences and blogs on Artificial Intelligence (AI) …is all this an indicator that AI has finally reached a maturity stage which supports broader commercialization? The answer is "yes" and the aim of this post is to share some key lessons learned from the front line of implementing AI solutions. The borders between automation, machine learning and AI are sometimes blurred requiring some clarification. AI is the simulation in machines (i.e. AI has also become imbedded in our daily lives from Google Translate to autonomous vehicles to chatbots and there is no turning back.

The industrial sector in the US, driven by high labor costs and the quick time-to-market, has been pushing to enhance production efficiency and lower operation costs, leading to an increase in the use of industrial artificial intelligence (AI) applications, according to a new report from ABI Research. The total installed base of AI-enabled devices in industrial manufacturing will show a compound annual growth rate of nearly 65% through 2024. US manufacturers have been aggressive with the adoption of industrial AI solutions; this has given birth to pure-play AI players in the US and will keep the US as the global leader in industrial AI solutions for some time to come. Over time, however, China will catch up, as investments are poured into AI and related technologies, says Lian Jye Su, principal analyst at ABI Research. Cloud service providers, smart manufacturing platform vendors, pure-play industrial AI platform and service providers, edge industrial AI gateway and server vendors, and chipset vendors are partnering with each other to bring AI into industrial manufacturing.

Summary: Before starting to develop an AI strategy, make sure your team understands the limits of what is reasonable today, as well as incremental improvements that might be overlooked. Focus should be on your LOB leaders who understand the business. Make sure they are also able to recognize AI opportunities. I recently saw this chart from PricewaterhouseCoopers as part of their '2018 AI Predictions Report'. The statement was: 'we effectively utilize all the data we capture to drive business value' (strongly agree - 2200 C-level and IT respondents in large and mid-size companies internationally).

IBM is trying to woo and support new developers as the battle for skilled AI talent ramps up. AI is among the hottest technologies on the horizon, and sub-topics like machine learning have emerged as a must-have for many new applications. IBM and others want to empower developers with tools to simplify the creation of AI-powered apps. Oracle released the long-awaited Java 9, but what will this mean for developers? Uncover how Java 9's improvements aim to simplify the development process.

Internet of Things is no more a science fiction. From smart homes to connected cars to smart healthcare, consumers and vendors are gearing up for the next big thing. There is more to IoT than those fancy wristbands, gadgets, and watches. From chip manufacturers to communication providers to platform vendors to cloud providers, the IoT ecosystem is complex and diverse. Like most of the technology segments, no single player will be able to dominate this market.

Ever since Facebook, the world's largest social networking site made its Messenger mobile texting app available, businesses have begun experimenting with chatbots. In the near future, we should expect businesses to adopt chatbot platforms in the same way they are currently embracing mobile and Internet of Things (IoT) platforms. A chatbot is a software that impersonates a user, a service which allows people to interact through a chat interface using textual or audio means. Chatbots offer brands an opportunity to reach out to an audience and engage them in dialogues that might translate into immediate actions. Functions that depend on interaction and conversations, such as customer service or rapid information access, are good fits for chatbots across different industries.

Ever since Facebook, the world's largest social networking site made its Messenger mobile texting app available, businesses have begun experimenting with chatbots. In the near future, we should expect businesses to adopt chatbot platforms in the same way they are currently embracing mobile and Internet of Things (IoT) platforms. A chatbot is a software that impersonates a user, a service which allows people to interact through a chat interface using textual or audio means. Chatbots offer brands an opportunity to reach out to an audience and engage them in dialogues that might translate into immediate actions. Functions that depend on interaction and conversations, such as customer service or rapid information access, are good fits for chatbots across different industries. For example, you could ask a bot on a travel site to book you a hotel based on your preference.