Improving the efficiency of your helpdesk with serverless machine learning Google Cloud Big Data and Machine Learning Blog Google Cloud Platform


Great customer service builds trust, inspires brand loyalty, and earns repeat business. So it's no surprise that, according to Deloitte, close to 90 percent of organizations name improving the quality of their customer service as a strategic focus. Customer service helpdesks know this all too well. They often deal with an ongoing flow of tickets that sometimes have little information or context, which can slow down agents and impact service quality. What if you could use historical data to predict key KPI or fields of a support ticket to handle it in the most efficient way?

Enterprises Challenged By The Many Guises Of AI


Artificial intelligence and machine learning, which found solid footing among the hyperscalers and is now expanding into the HPC community, are at the top of the list of new technologies that enterprises want to embrace for all kinds of reasons. But it all boils down to the same problem: Sorting through the increasing amounts of data coming into their environments and finding patterns that will help them to run their businesses more efficiently, to make better businesses decisions, and ultimately to make more money. Enterprises are increasingly experimenting with the various frameworks and tools that are on the market and available as open source software, in both small scale experiments run by a growing number of data scientists who have the expertise to find the valuable information the growing lakes of data and in full blown production deployments that are, conceptually, every bit as sophisticated as what the hyperscalers are deploying. The top cloud service providers and hyperscalers have for several years embrace data-driven AI and machine learning techniques and built their own internal frameworks and platforms that enable them to quickly take advantage of them. But as the technologies begin to cascade into more mainstream enterprises, the complexity of software and systems are throwing roadblocks in front of initiatives aimed at leveraging AI and machine learning for the good of the business.

What Amazon's Machine Learning Tools Could Hold for Businesses - Market Realist


Amazon (AMZN) subsidiary Amazon Web Services (or AWS) has rolled out a new set of machine learning services and the world's first deep learning camera to allow companies to take advantage of AI (artificial intelligence) in their businesses. Amazon's five machine learning services include Amazon SageMaker, Amazon Transcribe, Amazon Translate, Amazon Comprehend, and Amazon Rekognition Video. These services allow developers to build applications that easily understand human instructions. Another critical product launched was AI-powered camera DeepLens, which is similar to Alphabet's (GOOGL) Google Clips. However, the clips are targeted at consumers and not developers like DeepLens.

AI's impact on network engineering now and in the future


If nothing else, AI continues to climb the technology hype curve. It was impossible to read the news, browse the web, attend a conference, or even watch television without seeing a reference to how AI is making our lives better. Since Alan Turing declared "what we want is a machine that can learn from experience" in a 1947 lecture to the London Mathematical Society, the imaginations of computer scientists and engineers have run wild with visions of a computer that can answer questions on par with a human. Today, almost everyone in business is looking at how to leverage AI, and there is no shortage of vendors looking to capitalize on the trend. Venture Scanner currently tracks more than 2,000 AI startups that have received more than $26 billion in funding.

7 Things to Know About AI and Customer Care


Artificial intelligence for customer care is a hot subject. One industry analyst recently shared that, starting a few months ago, more than 75% of the firm's customer inquiries were to discuss just one topic: Using AI to improve customer care. What are some key insights regarding customer care and AI? AI can help further address self-service outcomes by helping you deepen offers through more natural and intuitive interfaces. "How may we help you?" will become the most common question companies ask in their self-service offers compared to today's largely static interfaces. The nature of AI is such that you can infuse it into existing business processes.

14 jokes about net neutrality while they're still free


In a brave motion, the Federal Communications Commission voted to repeal a nasty net neutrality protection on Thursday that was put in place by the evil Obama administration in 2015. Finally, the internet will be able to serve its true and real purpose: make untold billions of dollars for faceless corporations, which nearly everyone in the United States hates. Finally, the people who make the internet a weird place for new opportunities, creation, innovation, and social interaction will be forced to pay for that privilege. Finally, the poor corporate CEOs of major telecom companies will be able to afford a new jet to replace their old and outdated planes. But before the new regime takes hold of the invisible force that bonds the modern world together as we know it, bringing new life to underprivileged areas and creating a global conversation and marketplace, we can wallow in the mediocre humor of those sarcastic shits who define the culture of the internet.

Big Data and Analytics – What's Ahead? @ThingsExpo #IoT #M2M #BigData


Recently I read somewhere this statement – As we end 2017 and look ahead to 2018, topics that are top of mind for data professionals are the growing range of data management mandates, including the EU's new General Data Protection Regulation that is directed at personal data and privacy, the growing role of artificial intelligence (AI) and machine learning in enterprise applications, the need for better security in light of the onslaught of hacking cases, and the ability to leverage the expanding Internet of Things. In the area of big data, a combination of new and long-established technologies are being put to work. Hadoop and Spark are expanding their roles within organizations. NoSQL and NewSQL databases bring their own unique attributes to the enterprise, while in-memory capabilities (such as Redis) are increasingly being utilized to deliver insights to decision makers faster. And through it all, tried-and-true relational databases continue to support many of the most critical enterprise data environments.

Business Models of #WebRTC @CloudExpo @Twilio #IoT #RTC #AI #ML


WebRTC services have already permeated corporate communications in the form of videoconferencing solutions. However, WebRTC has the potential of going beyond and catalyzing a new class of services providing more than calls with capabilities such as mass-scale real-time media broadcasting, enriched and augmented video, person-to-machine and machine-to-machine communications. In his session at @ThingsExpo, Luis Lopez, CEO of Kurento, introduced the technologies required for implementing these ideas and some early experiments performed in the Kurento open source software community in areas such as entertainment, video surveillance, interactive media broadcasting, gaming or advertising. He concluded with a discussion of their potential business applications beyond plain call models. Speaker Bio Dr. Luis Lopez is associate professor at Universidad Rey Juan Carlos in Madrid, where he works in the creation of advanced multimedia communication technologies.

Google's return to China foretells a global race to deliver AI


When Google abandoned the Chinese search market over government censorship in 2010, it seemed a remarkably principled act of self-sabotage. The company's decision to return to China today, by establishing a new AI research center in Beijing, is all about safeguarding its future. The center was announced at an event in Shanghai today by Fei-Fei Li, a prominent AI researcher and the chief scientist at Google Cloud. With the announcement, Google is acknowledging the growing importance of China for the future of AI. It is also setting the stage for a battle over who gets to deliver AI to the rest of the world.

How Artificial Intelligence Will Personalize How We Work


Artificial intelligence in the workplace is here to stay. However, as enterprise technologies continue to develop and evolve, we must understand how AI will affect our roles and responsibilities at work. The unknowns about the impact of AI has led to the fear that this emerging technology could be a substitute for – or entirely eradicate – existing jobs. Depending on which stats you refer to, AI will replace over 40% of jobs by 2030, or that 165 million Americans could be out of work before 2025. Yet it is not all doom and gloom.