The robot apocalypse has been tentatively scheduled for late 2019. Boston Dynamics, the SoftBank-owned robotics firm (that was once Alphabet's headache), will begin to commercialize its research next year. Marc Raibert, the company's founder, announced onstage at a TechCrunch robotics conference May 11 that Boston Dynamics will begin selling its dog-shaped robot, SpotMini, in 2019. It'll build about 100 robots over the next year, and is currently in the process of contracting manufacturers. The robot, which the company has been developing for the last couple years, is the smaller brother of Spot, a robot Boston Dynamics' researchers have been kicking since 2015. SpotMini weighs about 66 pounds and has a battery life of about 90 minutes, according to the company's website.

Enterprise machine learning within business organizations is all set to double by this year while smartphone usage is set to grow with sales reaching 1.85 billion per year by 2023, a new study has found. According to Deloitte Global's Technology, Media and Telecommunications Predictions, business organizations will likely double their use of machine learning technology by the end of 2018 as they seek to ramp up productivity. The report noted that the growth in new semiconductor chips will increase the use of machine learning, enabling applications to use less power, and at the same time become more responsive, flexible and capable. "We see governments in the GCC playing an active role in promoting the adoption of AI and Machine Learning," said Emmanuel Durou, Partner and Technology, Media and Telecommunications Leader, Deloitte, Middle East. Deloitte Global also predicted that live broadcast and events will generate over $545 billion in direct revenues in 2018.

The world is evolving around us. Chris Reece, who recently spoke about AI and network evolution to a packed house at Mobile World Congress in Barcelona, will be presenting an AI discussion focusing on use cases in the telecommunications industry. Learn how and why service providers are investing in AI to solve their toughest challenges. They are using AI to solve everything from infrastructure challenges to implementing automation. New technologies are fueling AI applications and accelerating adaptive, "self-everything" networks.

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?