Google Next 2019

I attended Google Next 2019 in SF!

The conference featured tracks encompassing application development, architecture, collaboration and productivity, cost management, data analytics, databases, hybrid cloud, ML and AI, mobility and devices, security, serverless and much more. There were customers, partners, developers, influencers and the greater global cloud community together to get inspired and learn about Google Cloud Platform, G Suite, Maps, Devices and more great technology and solutions from across Google. I was able to learn from customers and partners, and dive deep through breakout sessions, code labs, demos and hands-on training. It was great getting to meet lots of other cloud developers and practitioners to share stories and ideas.

Tuesday - Thursday, April 9-11th 2019

Here are some of the sessions I attended:

The Road to Intelligent Transportation (Cloud Next ‘19)

Mobility is a way of life for active and thriving communities. Residents place their trust in the government to manage roadways and traffic, reduce congestion, and keep them out of harm’s way when traveling to their destination. Yet with cities growing in population, mobility suffers and traffic is worse than ever before. Transportation leaders need a way to unlock the power of their ever-increasing data to make our roadways more efficient and safer for everyone.

The Colorado Department of Transportation (CDOT) is on a mission to prepare for the roadways of the future by transforming their view of roadways from carriers of vehicles to producers of valuable digital information which can be leveraged for intelligence and predictive analytics to optimize how they operate and maintain more than 23,000 lane miles of roadway smarter today. As part of our project, we consolidated disparate data sources from across CDOT’s data ecosystem, migrating from batch to streaming ingest. Unlocking new insights around road sensor failures and data anomalies, enriched by crash data from third party data sources, to get maintenance crews to broken devices faster.

Join Google and CDOT to see how Colorado is taking advantage of Google Cloud to innovate, accelerate, modernize, and leverage data to optimize traffic and help save lives and modernize Colorado highways.

Speaker(s): Christopher Haas, Zef Delgadillo, Andrew Schwartz

Hardware root of trust with Google Cloud IoT Core and Microchip secure elements

Check out how to improve IoT security by securing the authentication between Google Cloud IoT core and IoT devices using a secure element (ATECC608A) from Microchip.

Connected Vehicles as Air Quality Sensors: Powered by BigQuery GIS (Cloud Next ‘19)

Air pollution costs the global economy $225 billion every year in lost labor income. Measuring air pollution from stationary instruments located miles apart is insufficient, as dangerous air pollution can be eight times higher from one end of a block to another, and living in the vicinity of elevated air pollution increases the risk of serious conditions such as asthma, heart disease, COPD, and ultimately, premature death. There is a better way. Geotab manages data and services for over 1.4 million connected vehicles and over 30 billion data points per day. Aclima is a leader in hyper-local environmental sensing and analytics, deploying both mobile and stationary sensor networks to gather billions of data points related to both human health and global climate change. Together, these two Google partners will tell the story of how they have partnered to leverage BigQuery, BigQuery GIS, and Google Cloud Platform to enable hyper local air quality sensing on municipal vehicles and deliver this insight to the community in real-time.

Speaker(s): Mike Branch, Davida Herzl, Chad Jennings, Jon Walton

Making Planet Scale Geospatial Processing Possible with BigQuery GIS (Cloud Next ‘19)

Joining big data with planet scale image analysis stretches the frontier of impossibly big GIS. In this session, Descartes Labs will first explain how they’re usingBigQuery GIS to perform analyses with data volumes and speeds that could only be handled efficiently on Google Cloud infrastructure. Then, Global Fishing Watch will present their method for combining radar image processing in Earth Engine and vessel telemetry data in BigQuery to detect and identify illicit activities at sea. Finally, you’ll peek under the hood with an esteemed BigQuery engineer and learn the fundamental mathematical mechanics underlying BigQuery GIS, Earth Engine, and all of Google’s mapping products.

Speaker(s): Tim Kelton, David Kroodsma, Mosha Pasumansky

Automating Visual Inspections in Energy and Manufacturing with AI (Cloud Next ‘19)

AES is a Fortune 500 global power company, generating and distributing sustainable energy in 15 countries, owning and managing $33 billion in assets. To optimally serve their mission of accelerating a safer, greener, energy future, AES has rigorously scaled the use of drone technologies and machine learning in their wind farm operations. Using Google’s AutoML Vision, they can help automate the detection of defects, and prioritize maintenance of their high-value assets.

LG CNS is a global IT services company with USD$2.7 billion in annual sales. They supply IT solutions for the LG Group’s affiliates and other companies, and apply big data and AI to improve manufacturing processes at scale. Originally, many inspectors were required to detect defects in everything from LCD and OLED panels, to optical films and automotive fabrics. But the monotony of visual inspections led to many errors, so LG CNS built their own in-house AI solution to visually inspect products on the assembly line. This required lots of time and effort to achieve high performing machine learning models, and they experienced a shortage of highly skilled AI experts. They turned to Google’s AutoML Vision Edge to design and distribute models to the edge, and centrally control the performance of their deployed models in one integrated system. This improved accuracy and performance, and reduced the time it takes to build high quality models.

Speaker(s): Mandeep Waraich (Google), Nicholas Osborn (AES), Sungwook Lee (LG CNS)

Building IoT Applications With Cloud IoT and Firebase (Cloud Next ‘19)

IoT solutions are complex because the data needs to proceed through different systems and layers, from ingest to application and presentation layers. This is especially true when you involve many role types, from system designers and OEMs to corporate or consumer end users. Learn how Google provides a complete set of fully managed serverless components to build such a solution by combining IoT Core for device identity and data ingest, with Firebase Authentication for user identity and Firestore for real-time application data.

Customer Story: Target - 70 days to PCI Compliance

Building Blocks for the Digital and IoT Ecosystem in Manufacturing (Cloud Next ‘19)

An array of building blocks is part of every digital and IoT project. Some of these building blocks include: the machines, people and things being connected; the sensors collecting data from all those elements; the devices that connect those sensors; the networks that carry the data; the data itself and how it is stored, managed and analyzed; the applications that inform and automate; and the people who play a role at every touch point. Google Cloud provides a complete set of tools to connect, process, store, and analyze data both at the edge and in the cloud. By bringing together Google Cloud’s leading data analytics and machine learning capabilities with Hitachi’s ground-breaking work in operational technology and IoT, we are driving innovation in Manufacturing.

Speaker(s): Ellen Dowd, Robert Lively

Honeywell and Foghorn Leverage Android for Smart Industrial Devices (Cloud Next ‘19)

This session will share how FogHorn, Google Cloud IoT, and Honeywell have worked together to apply traditional and adaptive machine learning models to improve operational efficiencies on the shop floor. Honeywell will demonstrate how they were able to improve barcode image reconstruction system and device battery lifespan prediction using Android, Google Cloud, and Foghorn technologies.

Speaker(s): Antony Passemard, Sastry Malladi, Scott Bracken, Ramya Ravichandar

Medical Imaging 2.0 (Cloud Next ‘19)

Medical imaging is one of the largest sources of healthcare data. Join us in this talk to learn how cloud technologies and artificial intelligence enable new applications in the medical imaging domain, improving patient care and reducing physician burnout.

Speaker(s): Arie Meir, Patrick Kling, Omer Khawar, Alexander Sicular

NASA FDL + Google Cloud: Identifying Exoplanets — Finding Life (Cloud Next ‘19)

A presentation that will explain NASA FDL’s four step plan to finding extertierital life and their partnership with Google Cloud.

The talk will go over, the four steps:

Step 1: Finding Exoplanets
Step 2: Measure the atmospheric qualities of exoplanets
Step 3: Reverse engineer all possible planetary atmospheres
Step 4: Determine which planets could support life

Both speakers will be sure to highlight the fact that even though there are not technically trained on machine learning they were able to use Google Cloud tools to combine their expertise with AI and greatly push their fields forward.

Speaker(s): Megan Ansdell, Molly O’beirne

Building Smarter Software Robots with Robotic Process Automation & Google Cloud AI (Cloud Next ‘19)

Business Process Automation is driving seismic business change across the workplace with both routine and non-routine based tasks already being transformed by automation. To keep pace with this, Robotic Process Automation vendors are partnering with Google Cloud to drive a shift from rule based decision-making automation to a more advanced judgment and self learning-based intelligent automation. This evolution means more intelligent, digital workers with new skills that include knowledge and insight, planning and sequencing, visual perception, collaboration, learning and problem solving.

In this session, we’ll showcase how top RPA partners UiPath and Automation Anywhere have equipped their bots with the best of Google Cloud technologies from GSuite to Google Cloud AI to increase the capabilities of these automated implementations. We’ll highlight customer use-cases and demonstrate available RPA solutions.

Speaker(s): Abhijit Kakhandiki, Mark Benyovszky, Ganapathy Subramanian, Francisco Uribe, Ravi Boggaram