Throughout my career as an unwavering advocate of AI and AI for good, I've had the pleasure of meeting, connecting with, and absorbing wisdom from a variety of individuals. As part of my 10-Part Series of The 9 Inspirational Women Leaders In AI Shaping The 21st Century, I was honored to converse with Linda Avery. Linda is the strategic voice, and visionary for data and analytics at Verizon, focused on using the power of data and AI across the enterprise. Linda joined Verizon in September 2019 and has grown the AI & Data organization to approaching 1,000 contributors by the end of 2021, including teams dedicated to Data Governance, Data Architecture and Engineering, and an AI Center, covering a broad range of disciplines from AI Ethics to Industrialization and Digital Twins. NEW YORK, UNITED STATES - 2020/10/15: Verizon store front displays the 5G network near Grand Central ... [ ] Terminal.

Governments and humanitarian groups can use machine learning algorithms and mobile phone data to get aid to those who need it most during a humanitarian crisis, we found in new research. The simple idea behind this approach, as we explained in the journal Nature on March 16, 2022, is that wealthy people use phones differently from poor people. Their phone calls and text messages follow different patterns, and they use different data plans, for example. Machine learning algorithms--which are fancy tools for pattern recognition--can be trained to recognize those differences and infer whether a given mobile subscriber is wealthy or poor. As the COVID-19 pandemic spread in early 2020, our research team helped Togo's Ministry of Digital Economy and GiveDirectly, a nonprofit that sends cash to people living in poverty, turn this insight into a new type of aid program. First, we collected recent, reliable and representative data.

The telecommunications industry is so many enterprises wrapped into one--they have to get every aspect of customer experience right. It's a challenge every organization can learn from. AI solutions offer the exciting potential to transform the customer experience and bend the value curve for enterprises. Everywhere you look, there's another business attempting to harness data, analytics, and artificial intelligence to help them increase sales and crack the code to provide higher-quality, lower-cost goods and services. Travel and hospitality companies want to make persuasive, personalized offers at just the right moment to drive bookings.

General Motors is acquiring SoftBank's stake in Cruise and pouring even more money into the self-driving unit it purchased in 2016. The auto giant has announced that it's buying out SoftBank Vision Fund 1's equity ownership into the company that's worth $2.1 billion. In addition, it has committed to investing an extra $1.35 billion in Cruise to replace the funding SoftBank promised in February after the self-driving car company started offering robotaxi rides in San Francisco. The automaker didn't say why it's buying SoftBank's equity ownership, but GM chief executive Mary Barra said: "Our increased investment position not only simplifies Cruise's shareholder structure, but also provides GM and Cruise maximum flexibility to pursue the most value-accretive path to commercializing and unlocking the full potential of AV technology." SoftBank, meanwhile, has recently struggled with debt and the plummeting value of its properties.

An international tech blockade threatens to deprive Russia of sophisticated semiconductors needed to power advanced weaponry and cutting-edge technologies like 5G, artificial intelligence and robotics, experts say. In late February, the U.S. imposed a ban on selling high-tech products including semiconductors and telecommunications systems used by the defense, aerospace and maritime industries to Russia and its ally Belarus, days after Russia invaded Ukraine. The ban also extended to certain foreign items produced with U.S. equipment, software or blueprints.

General Motors Co. bought out the SoftBank Vision Fund 1's stake in self-driving startup Cruise LLC for $2.1 billion, ending the Japanese investment firm's involvement in the business and giving the Detroit automaker 80% ownership. GM also said Friday it will invest another $1.35 billion in Cruise, which makes up for the amount that SoftBank had pledged to invest in the startup once the company deploys vehicles in a ride-sharing business, something it is preparing to do. The deal consolidates GM's ownership and control over Cruise, and reverses a capital diversification play by former Chief Executive Officer Dan Ammann, who was fired in December after pushing for an initial public offering. GM CEO Mary Barra and Cruise founder Kyle Vogt, who replaced Ammann as CEO, have said an IPO isn't in the offing at this time and likely won't be anytime soon. "Why not just go public? It's a major distraction, especially right now," Vogt said on Twitter after GM announced the deal.

A: The number of devices that are being built for virtual reality, augmented reality, mixed reality is not a small number by any metric. Tech is not far away from being able to have [smart] glasses. You'll be able to walk into a room and capture the image, and it will immediately go to the Internet and say these are the connections you have with people, here's information from this person's social network. You can get trained on things that you don't know. You get step-by-step instructions in your glasses.

The Research Brief is a short take about interesting academic work. Governments and humanitarian groups can use machine learning algorithms and mobile phone data to get aid to those who need it most during a humanitarian crisis, we found in newly published research. The simple idea behind this approach is that wealthy people use phones differently from poor people. Their phone calls and text messages follow different patterns, and they use different data plans, for example. Machine learning algorithms – which are fancy tools for pattern recognition – can be trained to recognize those differences and infer whether a given mobile subscriber is wealthy or poor.

When we hear about AI in the contact center, it's usually about chatbots and augmented agent. But in this conversation, we hear at how contact center AI can help with sales and marketing. Invoca is doing some fascinating stuff with its conversational intelligence engine. The company's technology has analyzed over 1.5B conversational minutes. Its customers analyze their call center interactions to optimize marketing, improve digital conversion rates, automate contact center QA, and enable agent coaching. Invoca just announced it saw 70% revenue growth during the past 12 months. Invoca's customer base now includes over 2,300 of the leading B2C brands across a number of industries. The common theme, according to Gregg, is they tend to have complex interactions. The small company seems to be doing a few things right. It was named a Leader in The Forrester Wave: Conversation Intelligence: Sales And Marketing, Q4 2021 report. Just this week it was selected for the Innovation Showcase at Enterprise Connect. Invoca was also recognized in the Inc. Best Workplaces of 2019 list and achieved the difficult Great Place to Work certification. Dave Michels 0:12 Welcome to talking here today, Evan and I will be talking with Brent Johnson of invoca. But before that Evon must be the pandemic is over, because it's time for Enterprise Connect. I know I'm gonna be there. Evan Kirstel 0:24 You know, after a two year hiatus, I will be there in person at Enterprise Connect in Orlando, and at the Innovation Showcase which you are spearheading I really actually looking forward to it to seeing, well, you not so much, but a lot of other people that I haven't seen in person for a while. You mentioned the Innovation Showcase, because that is without doubt the most valuable session.

Artificial Intelligence has applications in all fields including telecommunications. Mobile data analytics, total network optimization, enhancing security, improvement of network operations, control of operational cost and network design are some of the areas where AI can be deployed. Prediction of consumer behaviour, introduction of such services which will be appreciated by him/her, launching of customised services, reduction of power consumption, improving resilience of the network, predictive maintenance, optimum utilisation of network elements, seamless provision of services and real time fraud detection and fraud prevention are other interesting applications of AI. As operators move from 4G to 5G implementation, network complexity and cost sharply increase because of implementation of Customer Experience Management (CEM), IOT, SDN (Software Defined Network), NFV (Network Function Virtualisation), 5G Radio access equipment and core infrastructure, 5G for private networks etc. But the average revenue per user is stagnating.