A graph homomorphism is a map between two graphs that preserves adjacency relations. We consider the problem of sampling a random graph homomorphism from a graph $F$ into a large network $\mathcal{G}$. When $\mathcal{G}$ is the complete graph with $q$ nodes, this becomes the well-known problem of sampling uniform $q$-colorings of $F$. We propose two complementary MCMC algorithms for sampling a random graph homomorphisms and establish bounds on their mixing times and concentration of their time averages. Based on our sampling algorithms, we propose a novel framework for network data analysis that circumvents some of the drawbacks in methods based on independent and neigborhood sampling. Various time averages of the MCMC trajectory give us real-, function-, and network-valued computable observables, including well-known ones such as homomorphism density and average clustering coefficient. One of the main observable we propose is called the conditional homomorphism density profile, which reveals hierarchical structure of the network. Furthermore, we show that these network observables are stable with respect to a suitably renormalized cut distance between networks. We also provide various examples and simulations demonstrating our framework through synthetic and real-world networks. For instance, we apply our framework to analyze Word Adjacency Networks of a 45 novels data set and propose an authorship attribution scheme using motif sampling and conditional homomorphism density profiles.

Most early adopters face AI skill gaps and are looking for expertise to boost their capabilities. According to Deloitte's global study of AI early adopters, 68 percent report a moderate-to-extreme AI skills gap.1 What are the "most wanted" roles to fill these gaps? According to AI early adopters, the top four most-needed positions are "AI builders" who are involved in creating AI solutions: Beyond these AI builders, adopters are seeking "AI translators" who bridge the divide between the business and technical staff--both at the front and back end of building AI solutions: When we compare companies with relatively little AI experience (they've built five or fewer production systems) with those possessing extensive AI experience (they've built 20 or more production systems), we observe an interesting shift in "most wanted" roles (see chart). Early on, AI researchers are the most sought-after, with about a third of the less-experienced rating them a top-two needed role. Business leaders rank near the bottom.

In the framework of the presentation of what will be ClaroTec 2019, its event focused on the technological world the Claro telecommunications company announced that Sophia, the humanoid robot will come to the Dominican Republic. The android, which utilizes artificial intelligence and has been invited to numerous events in the area of technology in various countries, will be part of the attractions of the activities that are scheduled to take place this October 27 at the Port of Sans Souci. Sophia wears black, blinks and shakes her head when she hears questions. Her expressive light eyes and the artificial skin with which she is covered suggest that the speaker is a human, except for the circuits that are visible on the back of her head. Her body of about 30 kilos in weight is built from the waist up and rests on a table from which she replies that humans "are the most creative creatures on the planet, but also the most destructive and cruel."

For that reason, Square is now letting business owners automate the rescheduling process with a chatbot called Square Assistant. Business owners that are using Square's existing Appointments service can now confirm appointments with customers--or let them cancel or reschedule them--via text message, without any human involvement. It's the first product to come from Square's acquisition of conversational AI startup Eloquent Labs earlier this year. "For some of our customers, SMS is just a more efficient way to interact," says Ellen Blaine, a former Eloquent Labs engineer who is now a product manager at Square. "With Square Assistant, you can reschedule or confirm an appointment just by texting a couple of words."

Verizon and NEC used artificial intelligence (AI)-infused software and sensors as part of a recent proof-of-concept (PoC) trial that allowed already installed fiber infrastructure to monitor traffic and road conditions. The PoC used NEC-developed optical sensor technology with the AI software running alongside existing wavelength division multiplexing (WDM) communication channels on the same fiber lines. The mixture turned the cables into distributed optical sensors that collected information on traffic patterns, road conditions, road capacity, and vehicle classification information. The AI tools used included convolutional neural networks (CNN) and software vector machines that were able to tap into distributed intelligent traffic informatics (DITI). Those tools were plugged into a single integrated monitor that was able to detect back-scattering light traveling through the fiber optic streams to detect static strain, dynamic strain, acoustics, vibrations, and temperatures for each fiber segment.

BELGRADE – When hundreds of video cameras with the power to identify and track individuals started appearing in the streets of Belgrade as part of a major surveillance project, some protesters began having second thoughts about joining anti-government demonstrations in the Serbian capital. Local authorities assert the system, created by Chinese telecommunications company Huawei, helps reduce crime in the city of 2 million. Critics contend it erodes personal freedoms, makes political opponents vulnerable to retribution and even exposes the country's citizens to snooping by the Chinese government. The cameras, equipped with facial recognition technology, are being rolled out across hundreds of cities around the world, particularly in poorer countries with weak track records on human rights where Beijing has increased its influence through big business deals. With the United States claiming that Chinese state authorities can get backdoor access to Huawei data, the aggressive rollout is raising concerns about the privacy of millions of people in countries with little power to stand up to China.

Any organization that wants to deliver targeted, personalized services and experiences needs to understand its customers inside and out: their wants, wishes, behaviors and attitudes. These days, the data to develop that understanding is abundantly available. The challenge is to extract meaningful customer insights from it and convert those insights into actions. By combining the principles of design thinking with the power of artificial intelligence (AI), CIOs have the tools to solve that problem and deliver powerful business results for their organizations. That's definitely true for the CIOs of the service providers we work with at Nokia -- telcos, mobile virtual network operators and the like.

The Inspection2 team will be attending the Total Telecom Congress on October 29-30, 2019 at the Business Design Centre, London. We will be showcasing our Expanse software with the latest Artificial Intelligence technologies for the Telecom industry to automate asset inspection and support 5G network rollout . Come and meet us at stand S31 in the Startup Village and get your hands on our cloud-based software Expanse and learn how it can automate tower condition assessment and deliver engineering and field operations efficiency.

Qualcomm executives this week attempted to draw contrasts and explain how their approach to cloud computing, artificial intelligence (AI), and mobile edge computing is different than other technology companies and operators. "Our focus is different than the rest of the industry," Jim Thompson, CTO and executive vice president at Qualcomm said during a media gathering at the company's headquarters. AI, an area of technology that Qualcomm has been working on for the better part of a decade, plays a big role in Qualcomm's vision for what it calls the "edge cloud," Thompson explained. "Our focus has been deep neural networks, deep learning for low power, for devices that you would have a battery in and have limited thermal capability," he said, adding that Qualcomm's interest is not the cloud essentially. "AI is very good at consuming large amounts of data. It comes from the edge of the network, it comes from what people do, it comes from sensors, and all of that is at the edge of the network," he said.

AI is great at cutting operational costs. For media, entertainment and telecommunications companies, in fact, some of AI's best uses to date have focused on reducing fraud and squeezing inefficiencies from IT infrastructure. Yet the greatest potential for AI lies in its ability to generate growth. By personalizing the customer experience, AI can help companies in high-churn sectors acquire and retain customers. Which content does the customer prefer?