We provide tools that help teams make the complex simple, personalization possible, and agility achievable. We enable new forms of acquisition, engagement, and retention across the global sports media and gaming industry. As video platforms, media and gaming companies strive to improve and differentiate their sports experiences, they have come to recognize that personalization is a necessity for success. The ability to better understand the customer, deliver recommendations and connect the users to the content they desire is no longer an option, but a requirement for success and growth. With Audience Cloud your team now has access to the best in class AI driven customer analysis platform.

Metal fabrication simply means the creation of metal structures for use in other industries. Are there intelligent solutions possible in this sector? It turns out that yes! At least three important aspects of AI in metal fabrication are mentioned. We will be looking at all three of these important aspects in this article.

Today, Daily AI, the provider of intelligent solutions for the future of mortgage lending, announced that it has acquired Whiteboard CRM. Whiteboard provides a mortgage CRM built to accelerate lead management, partner relationships, team production, and revenue growth. This acquisition will enable Daily AI to continue its significant expansion of market share since its founding in 2019 and continue fulfilling its mission of empowering mortgage professionals to increase their performance with its suite of automation tools. "All of us at Daily AI are looking forward to partnering with Whiteboard," said Spencer Dusebout, co-founder and CEO of Daily AI. "With the combined power of our sales, development, product, marketing, and customer success teams, we believe we will be an unstoppable force in the mortgage lending industry to create automation and AI-driven products and services of significant value to our customers."

On 17th May, L&T Technology Services announced the development of a smart parking solution working in collaboration with the Intel Corporation. The solution leverages the efficient capabilities of AI and has four key components according to the company. They are an operator portal that hosts user information; a mobile application for end-user interface; a digital signage module to ensure safe and secured access; and a digital camera. All these components are connected through the AWS cloud platform, hence making it easily available and accessible to people. The smart parking solution is powered by the Intel Distribution of the OpenVINO toolkit to run the AI inference model on Intel Xeon scalable processors and Intel Movidius VPUs.

If the adage that the customer is king is still true, it is especially true in government where customers are often citizens as well. Accenture's own research shows that 85 percent of Americans believe that government digital services should match or exceed commercial service levels. The ability to have seamless experiences across channels (even across competitor platforms) defines what we expect to see everywhere – if Facebook can target ads based on your recent Google search history, shouldn't the DMV be able to figure out that you've moved to a new address? Previously, citizens expected a three to five-year lag in CX standards between government and the commercial sectors. Now, that divide is shrinking to a matter of months, which is why the White House released guidance on customer experience standards for Federal agencies.

Artificial Intelligence is considered the modern era of innovation that has transformed the digital age. Smartphones are already an example of how our mobile devices have become more intelligent and how AI is powering the future intelligence of mobile devices is yet to be explored. Today, businesses and mobile manufacturers are collaborating to build hardware capabilities of mobile devices to accommodate the machine learning applications for the devices. But, many enterprises and researchers are looking to develop an intelligent architecture for mobile devices and applications to be more intelligent than ever. Mobile Intelligence is the power of mobile systems to learn, analyze, understand and resolve user queries through intelligent solutions.

It is a truism that artificial intelligence (AI) is set to change the world in unimaginable ways. The giants of the tech industry have realised it and are investing heavily in it, as can be seen, for instance, from Microsoft's $1 billion investment in OpenAI, which in turn was founded by Tesla's Elon Musk, and seeks to use AI to benefit all of mankind. Again, Twitter has acquired four AI companies - the biggest of them being Magic Pony for $150 million in 2016 - in its bid to improve its system of recommending specific tweets in users' timelines. Even traditional businesses are using AI to improve their services, such as UK-based grocer Nisa Retail employing Amazon Web Services to meet its business challenges. India too has plunged headlong into AI and machine learning (ML) with numerous start-ups offering AI solutions in areas such as banking, logistics and transportation.

In my previous post, I outlined a key problem facing insurers today: many are investing a significant amount in innovative technologies, yet are struggling to unlock their true potential and release trapped value in their business. In this post, I'll discuss how insurers can use advanced technology such as artificial intelligence (AI) and intelligent automation to reduce costs, enhance operations and improve efficiency to future-proof their organizations. In our research on "The New, New Normal: Exponential Growth", 56 percent of executives agreed that AI deployment will drive new growth and revenue opportunities by accelerating new products and services. Fifty-eight percent said that AI-enabled revenue growth will come from increased customer satisfaction and engagement; while nearly 50 percent believe it will spur a change in their business models. In the 2017 Technology Vision for Insurance survey, 76 percent of executives said AI would significantly or completely change the industry in the next three years, while 72 percent believed it would have a similar impact on their organization.

In my previous blog, we have seen how the off-the-shelf Object Detection is applied in Enterprise context in conjunction with SAP Leonardo Machine Learning Foundation. Now we will have a close look at how to implement custom object detection with tensorflow for serving intelligent solutions, especially how to train a custom object detector with custom dataset, and provision as RESTful API running on SAP Cloud Platform, Cloud Foundry, which can be consumed by your intelligent solution through loosely-coupled HTTP(s). The TensorFlow Object Detection API is an open source framework built on top of TensorFlow that makes it easy to construct, train and deploy object detection models. For more detail, you may refer to its official document. In order to train your own object detector, you need to prepare the dataset for training, including the images with the target objects, and labelling the object in the images.

US Insurers Could Boost Profits by $20 Billion Through Intelligent Solutions, According to Accenture Report More than half of insurers currently use intelligent solutions in one or more business process NEW YORK; July 25, 2018 – By embedding intelligent solutions such as artificial intelligence (AI), machine learning and analytics into every business process, insurers in the U.S. could increase annual profitability by as much as US$20 billion, according to new research by Accenture (NYSE: ACN). The report, called "Reimagining Insurance Processes with Intelligent Solutions," is based on an analysis of the potential profit impact of intelligent solutions on U.S. tier 1 insurers, as well as a survey of 185 insurance process professionals. The research found that insurers that use intelligent solutions to reinvent the customer experience and drive human-machine collaboration are achieving returns in excess of 10 times their investment and could increase industry-wide profitability by between US$10.4 billion and US$20.8 billion. "As insurers face heightened customer expectations and cost pressures, now is the time for them to move from experimenting with AI in the laboratory to deploying it at scale across several business processes," said Michael Costonis, who leads Accenture's Insurance practice globally. Encouragingly, the report notes that more than half (53 percent) of insurers surveyed are already using intelligent solutions in one or more business process, and 46 percent are investing in or piloting them to streamline selected business processes and customer experiences.