Google Duplex will call salons, restaurants, and pretend to be your personal human. Google has its robot work cut out for it. Janell Goplen automatically hangs up the phone when she receives automated calls to her Clearwater restaurant in Newport, Oregon. In the summer, Google will begin testing its controversial new plan to have the Google Assistant smartphone app make human-sounding calls for restaurant reservations and hair-cut appointments. If Goplen were to get the call and she sensed that it was robotic, "I'd hang up," she says.

Google started its annual I/O conference yesterday. It was packed full of AI applications showing that Google really is going'AI First.' It even changed its research arm name from Google Research to Google AI. But perhaps the most draw dropping demonstration was when Google used an AI to make calls and book appointments. I strongly recommend you spend 5 minutes and watch this.

The roughly €19 billion deal would face a possibly lengthy European Union antitrust review, but if completed, would create one of the continent's biggest telecommunications operators, selling the industry's holy grail "quad-play" package: cable, internet, wireless and landline-phone service on a single bill. The Financial Times reported earlier Tuesday the two companies were nearing a deal. The deal would represent the latest in a global trend of wireless carriers acquiring cable operations, or vice versa, to offer quad-play packages. Wireless carriers need high-speed cable networks to quickly transmit data to cellular towers for 5G, the coming generation of mobile networks that promise to be fast enough to enable near-instantaneous movie downloads and innovations such as self-driving cars. Both companies have said they have engaged in various forms of merger talks with each other in recent years.

One of the those AI skills is computer vision, which allows tiny cameras to recognize objects and then, armed with that knowledge, to take relevant action--for example, if a camera on a drone sees and recognizes a broken drainage pipe, it sends a fix-it ticket to the maintenance server. Microsoft and Qualcomm said today they'll co-create a developer kit containing the hardware and software needed to build such computer vision chops into small devices. Such devices will leverage Microsoft's cloud-based machine learning service. Qualcomm will provide chips specially designed to support the millions of computations needed for computer vision tasks. Separately, Microsoft announced that its Custom Vision computer vision service can now run on devices at the edge of the network (such as on IoT devices with cameras), allowing them to recognize objects and take actions without having to connect with the cloud.

The age of Artificial Intelligence (AI) is almost upon us. Rapid developments in machine learning have allowed us to build better, smarter machines that are capable of making decisions and handling tasks similar to humans. Some of these developments are also being implemented in mobiles to create the next generation of smarter phones. I attended the recent Huawei Global Analyst Summit in Shenzhen to speak with the heads of Huawei's development teams and find out more about the future of AI in mobiles. Huawei is a leading brand in mobile phone technology.

Software-defined cognitive networks: machine learning from comprehensive network data for self-organizing, self-optimizing management Software-defined networking: automated, multi-layer control with open interfaces for better resource utilization Legacy NMS: manual processes with tight control and potential for higher resource utilization Short-term improvements – long-term objectives Intelligently managing and operating networks 4. 2018 ADVA Optical Networking. Intent-based service activation Real-time, intent-based provisioning of secure connections Multi-layer network optimization and self-healing for highest availability Seamless integration with open, standardized interfaces Open network automation - multi-partner demonstration NETCONF RESTCONF/ TAPIOPENFLOW Secure photonic layer Secure CE layer Secure vSwitch layer Intent-driven API Network orchestrator Source: Intent-Based In-flight Service Encryption in Multi-Layer Transport Networks, OFC 2017 5. 2018 ADVA Optical Networking. Security is key ZTP is flexible and can be adapted to operational needs and stakeholder scenarios Zero touch provisioning in action Configuration steps Yang models 1. Device connects to bootstrap server and authenticates itself and the bootstrap server Zero touch information data model; procedure: get- bootstrapping data 2. Device uploads the boot-image and configuration scripts and verifies integrity and authenticity Ownership certificate, ownership voucher 3. Device installs and executes boot image and scripts Procedure: report-progress; device: "bootstrap complete" NB: There is also a need for securely connecting with NMS systems and there might be several boot and configuration servers … Service provider (owner) Bootstrapping server 6. 2018 ADVA Optical Networking. Intelligence emerges from complexity and scale Intelligence substituting human capabilities Insight extending human capabilities Explain affirming human capabilities • Machine learning: prediction • Deep learning: automated machines • AI: behaves and reasons • Data analysis: individual problem • Data analytics: general problem • Big data: beyond traditional data • Statistics: quantification • Data mining: pattern identification 7. 2018 ADVA Optical Networking. AI business value expectations (suppliers) Optimization of network resources Fraud detection and security Personalization Predicting congestion ChatbotsSituation-aware assuranceCall center Natural language machine control Source: AI – the time is now; TM Forum, Dec 2017 8. 2018 ADVA Optical Networking.

Drones may be best known for taking impressive aerial videos and inspecting buildings, infrastructure and crops, but they also promise to improve mobile and internet connectivity for emergency services and consumers. Poor mobile signal in rural areas is frustrating, but it can also be life-threatening in emergency situations. Slow emergency response times mean higher mortality rates. Mobile signals are usually sent via base stations, attached to buildings or special masts. These are tough to put up in a hurry - so why not attach a base station to a drone?

Apache Spark is a leading platform for large-scale data mining, batch processing and stream processing. Touted as a "lightning-fast unified analytics engine," Spark modernizes data analytics with machine learning to help businesses uncover patterns at new levels. Best of all, Spark is included within many other software solutions, so this powerful tool may already be part of your modern data analytics infrastructure. From its inception at the AMPLab at U.C. Berkeley in 2009, Spark has become one of the key big data distributed processing frameworks in the world. It's used by banks, telecommunications companies, games companies, governments, and nearly all major tech giants, including Apple, Facebook, and Microsoft.

A typical way in which network data is recorded is to measure all the interactions among a specified set of core nodes; this produces a graph containing this core together with a potentially larger set of fringe nodes that have links to the core. Interactions between pairs of nodes in the fringe, however, are not recorded by this process, and hence not present in the resulting graph data. For example, a phone service provider may only have records of calls in which at least one of the participants is a customer; this can include calls between a customer and a non-customer, but not between pairs of non-customers. Knowledge of which nodes belong to the core is an important piece of metadata that is crucial for interpreting the network dataset. But in many cases, this metadata is not available, either because it has been lost due to difficulties in data provenance, or because the network consists of found data obtained in settings such as counter-surveillance. This leads to a natural algorithmic problem, namely the recovery of the core set. Since the core set forms a vertex cover of the graph, we essentially have a planted vertex cover problem, but with an arbitrary underlying graph. We develop a theoretical framework for analyzing this planted vertex cover problem, based on results in the theory of fixed-parameter tractability, together with algorithms for recovering the core. Our algorithms are fast, simple to implement, and out-perform several methods based on network core-periphery structure on various real-world datasets.

Why bother with a human docent when a robot could give you a guided tour? Last week, the Smithsonian Institution in Washington, DC, revealed its new employee -- an interactive robot named Pepper. The 4-foot-tall humanoid robot was created by Softbank, which donated 30 robots to the museum last year. This friendly Pepper robot wants to show you around the Smithsonian museum. "By interacting with museum visitors and providing insight on different exhibits, Pepper will help guide their educational experience through the Smithsonian that they otherwise might have missed out on," Steve Carlin, chief strategy officer of Softbank Robotics, said in a statement.