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Google I/O 2018, Day 3 : Announcements and new kits for developers to build amazing products

The final day of Google I/O 18 consisted of a few talks including Node.js, Server less deployment, Tensorflow, Android Security, etc. It’s been an amazing three days of awesomeness with a lot of announcements and new kits for developers to build amazing products.  Let’s get to the highlights from Day 3 at Google I/O 2018.

Deploying Serverless Node.js Microservices

Myles Borins and Steren Giannini gave a talk on Deploying Serverless Node.js microservices.

They announced that in a couple of weeks, Node.js will start running on Google App Engine. Developers would be able to deploy a Node.js app easily to Google Cloud. The Node.js app would simply have an app.yaml file that specifies the runtime. And then the developer can run gcloud app deploy. That’s it!

TensorFlow without a PhD

This talk gave techniques about deep reinforcement learning with TensorFlow. There was a demo of a pong game driven by a neural network. There was also a demo of an animation character that learned how to move and jump via machine learning exposed by TensorFlow.

The tools for the demo included were :

  • TensorFlow for the models
  • Google ML engine for the training
  • Tensorboard Visualization Kit

Search Friendly JavaScript-powered Websites

Several tips for building search-friendly JavaScript-powered websites were given in this talk. Tools such as Puppeteer and Rendertron were recommended for dynamic rendering. The rendering of JavaScript-powered websites in Google search is deferred until Googlebot has resources available to process that content.

The Key Tips

  • Add a robot.txt to the top level domain of the site which specifies the URLs to crawl and not to.
  • Use good URLs such as example.com/about rather than fragmented URLs such as example.com/#home.
  • Use consistent URLs for the same page.
  • Add the critical metadata such as canonical links, viewport, title and description of each page, etc.
  • Use href elements when linking between pages. Don’t use non-semantic elements such as <div onclick=goTo(‘/contact’)></div> if you don’t have to!

With Google I/O 2018 coming to an end we are stoked for all the great things that will be rolled out in the coming months.

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Conversational UI in Healthcare: Enhancing Patient Interaction with Chatbots

As healthcare becomes more patient-centric, the demand for efficient and personalized care continues to grow. One of the key technologies that have gained traction in this domain is Conversational UI (CUI) — a user interface where interactions occur through natural language, often with the help of chatbots. For developers, building a robust CUI in healthcare requires a balance of technical proficiency, understanding of the healthcare landscape, and empathy toward patient needs. Let’s explore how CUI can improve patient interactions through chatbots and what developers should consider during implementation.

Why Conversational UI is Gaining Popularity in Healthcare

From scheduling appointments to answering medical queries, healthcare chatbots have become vital tools for enhancing patient engagement and streamlining healthcare workflows. Conversational UIs enable these chatbots to interact with patients naturally, making them accessible even to non-tech-savvy users. By incorporating AI and NLP (Natural Language Processing), chatbots can now simulate human-like conversations, ensuring patients receive timely, relevant responses. 

Image credit: https://www.analytixlabs.co.in/blog/ai-chatbots-in-healthcare/ 

Key Areas Where Chatbots Are Revolutionizing Healthcare

  1. Appointment Scheduling and Reminders – Chatbots can automatically schedule appointments based on patient availability and send reminders before the visit, reducing no-show rates. For developers, this feature requires integration with hospital management systems (HMS) and calendar APIs. The challenge lies in ensuring secure and real-time data transfer while adhering to healthcare compliance standards like HIPAA.
  1. Medical Query Resolution– Chatbots equipped with NLP can answer common patient questions related to symptoms, medications, and treatment plans. This reduces the burden on healthcare providers, allowing them to focus on more critical tasks. Developers working on this feature need to consider integrating medical databases, such as SNOMED CT or ICD-10, for accurate and up-to-date information.
  1. Patient Monitoring and Follow-ups – Post-discharge, chatbots can monit