Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(21)

Clean Tech(9)

Customer Journey(17)

Design(45)

Solar Industry(8)

User Experience(68)

Edtech(10)

Events(34)

HR Tech(3)

Interviews(10)

Life@mantra(11)

Logistics(5)

Manufacturing(3)

Strategy(18)

Testing(9)

Android(48)

Backend(32)

Dev Ops(11)

Enterprise Solution(33)

Technology Modernization(9)

Frontend(29)

iOS(43)

Javascript(15)

AI in Insurance(38)

Insurtech(66)

Product Innovation(58)

Solutions(22)

E-health(12)

HealthTech(24)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(153)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(8)

Computer Vision(8)

Data Science(23)

FinTech(51)

Banking(7)

Intelligent Automation(27)

Machine Learning(48)

Natural Language Processing(14)

expand Menu Filters

How is technology helping to combat coronavirus pandemic?

5 minutes, 31 seconds read

The deadly outbreak of the pandemic, coronavirus has claimed more than 110,000 lives and infected over 18,30,000 people worldwide. While the government chalks out COVID-19 risk mitigation plans, including social distancing, healthcare advisories, remote working and quarantine the infected; many organizations are taking technology initiatives to provide visualization and real-time situational awareness along with ways to run the lives of daily wagers.

To curb the spread of infection the entire nation has been subjected to rigorous lockdown. Unaccounted migration of daily wagers has made ghost settlements a recurring feature. Business tycoons say it is a daunting task to keep thousands of engineers safe while ensuring business continuity. This situation may affect the global economy because of supply chain, production, oil prices, currency and interest rate fluctuations. According to estimates, the economic cost of the pandemic would be over $4 trillion.

As the world gears up to combat this crisis of unforeseen magnitude, researchers, businesses, and innovators around the world are putting technology to work to mitigate the effects of the global health crisis. From using big data to understand the virus’ genetic tree, to keeping hospitals afloat with telemedicine; countries are trying every tip and trick in the book to contain the disease and provide a pattern amidst pandemonium.

Here is a list of technology-driven initiatives taken worldwide to combat the corona pandemic.

Aarogya Setu App

The Aarogya Setu application is the Government of India initiative to bring essential health services available to people. The most commonly used technology by the government is tracking people’s whereabouts through the location information on their cell phones; which in this crucial time has proven to be a means to restrain the spread of coronavirus. Using this technology this application alerts you when COVID-19 infected people are around. It also gives a detailed view of where the patient was before quarantine and who were in close proximity with them.

Aarogya Setu App

The app aims at amplifying the services of the Department of Health, in proactively reaching out to and informing the users of the app regarding risks, best practices and relevant health advisories related to the confinement of COVID-19 virus.

COVID Symptom Tracker & Corona 100m

C-19 COVID Symptom Tracker, an application developed by a UK startup, helps people self report their symptoms of coronavirus. It also helps to identify high-risk areas. It uses data science and machine learning models to study the data provided by the masses and identify those at risk sooner. 

C-19 COVID Symptom Tracker

The corona 100m, application by South Korea maps the whereabout of a corona positive patient and alerts the user when the infected person is within the reach of 100m.

China is using AI-powered thermal cameras on drones to enable contactless and rapid temperature detection in a crowd. This helps to identify those who have a fever. They have also deployed facial recognition systems to screen out people not wearing masks in public.

WHO Health Alert 

The World Health Organization (WHO) has launched a dedicated messaging service, the WHO Health Alert chatbot to provide information about coronavirus, answers to frequently asked questions about the disease, the current infection rates and preventive measures to be taken against it. 

The service is available in 7 different languages such as English, French, Hindi, Arabic, Italian, Spanish and Portuguese. People can activate conversation related to COVID-19 facts by simply typing a ‘hi’ to +41 79 893 18 92 on WhatsApp.

Video Calling Apps to keep Business as Usual.

With this pandemic taking a toll on the day to day business, companies are trying hard to keep employees safe with options like remote working and using tech tools to collaborate. As the world continues to fight the pandemic, flatten the curve and try to maintain normalcy by working from home. To deal with this containment and yet keeping it business as usual, video calling applications have become the most essential tools.

Read to know more about how Enterprises investing in Workplace Mobility Can Survive Pandemics.

The popular video calling applications like Skype, WhatsApp, Google Hangouts, Duo, Webex and Zoom, received approximately 600,000 downloads in one day. There has been a 70% increase in activity in Facebook Messenger’s video call functionality since the beginning of the outbreak.

Relief Fund for Daily Wagers

Due to this lockdown, as the economic activities of the country grind to a halt; millions of underdeveloped regions face penury and deprivation. With the lockdown suspending all kinds of work, daily wage workers are the ones to suffer the most. However to provide some relief to this horrifying situation, tech companies like Swiggy, Zomato and Ola have reached out to help.

Ola’s Drive the Driver’s Fund is to offer relief to the driver community. It provides financial assistance for essential supplies and emergency support.

Ola Cabs Drive the Driver’s Fund

Whereas Swiggy and Zomato are taking donations on their app and feeding India without involving a middle man. The financial help directly reaches the labours.

MyGov Corona Helpdesk

To mitigate the spread of fake news and offer immediate information related to coronavirus, the government of India has launched an official helpdesk, called MyGov Corona Helpdesk. One can initiate the conversation by simply texting a ‘hi’ to 9013151515 on Whatsapp.

Government of India initiative to create awareness and support individuals against coronavirus crisis

The government has also taken to other social media platforms such as Youtube, Facebook messenger, Linked In, Twitter, Instagram, Facebook Page and Telegram App to spread awareness and prevent the spreading of coronavirus.

Corporate technology-driven initiatives

Coronavirus Helpline India

ACKO, an Indian general insurance firm has created a portal – Coronavirus Helpline India to connect the government and common mass. It has listed all state wise essential helpline numbers, FAQs and important news related to coronavirus outbreak in India.

Lockdown Helping Hands

MantraLabs has taken the initiative to create a platform for people all over India to share their problems. The platform Lockdown Helping Hands is an effort to give voice to those who need help at this crucial hour of need. Others can directly share their, or other person’s problem on the portal. Using the share option, one can post the issue on various social sites to amplify the voices to reach the ears of the respective authority. The platform also provides state-wise helpful links, essential contact numbers and list of shops that are providing home delivery.

Lockdown Helping Hands - a technology-driven initiative to spread the word of those in need during nationwide lockdown

Due to the lockdown, there are several people far away from their loved ones, and struggling for help and information. There are many groups of people volunteering and ready to assist senior citizens, new mothers, physically challenged and people with medical conditions get access to basic daily essentials & medicines. Let us also do our bit and help lend a hand of help at this hour of need.

#StayHome #StaySafe

Cancel

Knowledge thats worth delivered in your inbox

AI Code Assistants: Revolution Unveiled

AI code assistants are revolutionizing software development, with Gartner predicting that 75% of enterprise software engineers will use these tools by 2028, up from less than 10% in early 2023. This rapid adoption reflects the potential of AI to enhance coding efficiency and productivity, but also raises important questions about the maturity, benefits, and challenges of these emerging technologies.

Code Assistance Evolution

The evolution of code assistance has been rapid and transformative, progressing from simple autocomplete features to sophisticated AI-powered tools. GitHub Copilot, launched in 2021, marked a significant milestone by leveraging OpenAI’s Codex to generate entire code snippets 1. Amazon Q, introduced in 2023, further advanced the field with its deep integration into AWS services and impressive code acceptance rates of up to 50%. GPT (Generative Pre-trained Transformer) models have been instrumental in this evolution, with GPT-3 and its successors enabling more context-aware and nuanced code suggestions.

Image Source

  • Adoption rates: By 2023, over 40% of developers reported using AI code assistants.
  • Productivity gains: Tools like Amazon Q have demonstrated up to 80% acceleration in coding tasks.
  • Language support: Modern AI assistants support dozens of programming languages, with GitHub Copilot covering over 20 languages and frameworks.
  • Error reduction: AI-powered code assistants have shown potential to reduce bugs by up to 30% in some studies.

These advancements have not only increased coding efficiency but also democratized software development, making it more accessible to novice programmers and non-professionals alike.

Current Adoption and Maturity: Metrics Defining the Landscape

The landscape of AI code assistants is rapidly evolving, with adoption rates and performance metrics showcasing their growing maturity. Here’s a tabular comparison of some popular AI coding tools, including Amazon Q:

Amazon Q stands out with its specialized capabilities for software developers and deep integration with AWS services. It offers a range of features designed to streamline development processes:

  • Highest reported code acceptance rates: Up to 50% for multi-line code suggestions
  • Built-in security: Secure and private by design, with robust data security measures
  • Extensive connectivity: Over 50 built-in, managed, and secure data connectors
  • Task automation: Amazon Q Apps allow users to create generative AI-powered apps for streamlining tasks

The tool’s impact is evident in its adoption and performance metrics. For instance, Amazon Q has helped save over 450,000 hours from manual technical investigations. Its integration with CloudWatch provides valuable insights into developer usage patterns and areas for improvement.

As these AI assistants continue to mature, they are increasingly becoming integral to modern software development workflows. However, it’s important to note that while these tools offer significant benefits, they should be used judiciously, with developers maintaining a critical eye on the generated code and understanding its implications for overall project architecture and security.

AI-Powered Collaborative Coding: Enhancing Team Productivity

AI code assistants are revolutionizing collaborative coding practices, offering real-time suggestions, conflict resolution, and personalized assistance to development teams. These tools integrate seamlessly with popular IDEs and version control systems, facilitating smoother teamwork and code quality improvements.

Key features of AI-enhanced collaborative coding:

  • Real-time code suggestions and auto-completion across team members
  • Automated conflict detection and resolution in merge requests
  • Personalized coding assistance based on individual developer styles
  • AI-driven code reviews and quality checks

Benefits for development teams:

  • Increased productivity: Teams report up to 30-50% faster code completion
  • Improved code consistency: AI ensures adherence to team coding standards
  • Reduced onboarding time: New team members can quickly adapt to project codebases
  • Enhanced knowledge sharing: AI suggestions expose developers to diverse coding patterns

While AI code assistants offer significant advantages, it’s crucial to maintain a balance between AI assistance and human expertise. Teams should establish guidelines for AI tool usage to ensure code quality, security, and maintainability.

Emerging trends in AI-powered collaborative coding:

  • Integration of natural language processing for code explanations and documentation
  • Advanced code refactoring suggestions based on team-wide code patterns
  • AI-assisted pair programming and mob programming sessions
  • Predictive analytics for project timelines and resource allocation

As AI continues to evolve, collaborative coding tools are expected to become more sophisticated, further streamlining team workflows and fostering innovation in software development practices.

Benefits and Risks Analyzed

AI code assistants offer significant benefits but also present notable challenges. Here’s an overview of the advantages driving adoption and the critical downsides:

Core Advantages Driving Adoption:

  1. Enhanced Productivity: AI coding tools can boost developer productivity by 30-50%1. Google AI researchers estimate that these tools could save developers up to 30% of their coding time.
IndustryPotential Annual Value
Banking$200 billion – $340 billion
Retail and CPG$400 billion – $660 billion
  1. Economic Impact: Generative AI, including code assistants, could potentially add $2.6 trillion to $4.4 trillion annually to the global economy across various use cases. In the software engineering sector alone, this technology could deliver substantial value.
  1. Democratization of Software Development: AI assistants enable individuals with less coding experience to build complex applications, potentially broadening the talent pool and fostering innovation.
  2. Instant Coding Support: AI provides real-time suggestions and generates code snippets, aiding developers in their coding journey.

Critical Downsides and Risks:

  1. Cognitive and Skill-Related Concerns:
    • Over-reliance on AI tools may lead to skill atrophy, especially for junior developers.
    • There’s a risk of developers losing the ability to write or deeply understand code independently.
  2. Technical and Ethical Limitations:
    • Quality of Results: AI-generated code may contain hidden issues, leading to bugs or security vulnerabilities.
    • Security Risks: AI tools might introduce insecure libraries or out-of-date dependencies.
    • Ethical Concerns: AI algorithms lack accountability for errors and may reinforce harmful stereotypes or promote misinformation.
  3. Copyright and Licensing Issues:
    • AI tools heavily rely on open-source code, which may lead to unintentional use of copyrighted material or introduction of insecure libraries.
  4. Limited Contextual Understanding:
    • AI-generated code may not always integrate seamlessly with the broader project context, potentially leading to fragmented code.
  5. Bias in Training Data:
    • AI outputs can reflect biases present in their training data, potentially leading to non-inclusive code practices.

While AI code assistants offer significant productivity gains and economic benefits, they also present challenges that need careful consideration. Developers and organizations must balance the advantages with the potential risks, ensuring responsible use of these powerful tools.

Future of Code Automation

The future of AI code assistants is poised for significant growth and evolution, with technological advancements and changing developer attitudes shaping their trajectory towards potential ubiquity or obsolescence.

Technological Advancements on the Horizon:

  1. Enhanced Contextual Understanding: Future AI assistants are expected to gain deeper comprehension of project structures, coding patterns, and business logic. This will enable more accurate and context-aware code suggestions, reducing the need for extensive human review.
  2. Multi-Modal AI: Integration of natural language processing, computer vision, and code analysis will allow AI assistants to understand and generate code based on diverse inputs, including voice commands, sketches, and high-level descriptions.
  3. Autonomous Code Generation: By 2027, we may see AI agents capable of handling entire segments of a project with minimal oversight, potentially scaffolding entire applications from natural language descriptions.
  4. Self-Improving AI: Machine learning models that continuously learn from developer interactions and feedback will lead to increasingly accurate and personalized code suggestions over time.

Adoption Barriers and Enablers:

Barriers:

  1. Data Privacy Concerns: Organizations remain cautious about sharing proprietary code with cloud-based AI services.
  2. Integration Challenges: Seamless integration with existing development workflows and tools is crucial for widespread adoption.
  3. Skill Erosion Fears: Concerns about over-reliance on AI leading to a decline in fundamental coding skills among developers.

Enablers:

  1. Open-Source Models: The development of powerful open-source AI models may address privacy concerns and increase accessibility.
  2. IDE Integration: Deeper integration with popular integrated development environments will streamline adoption.
  3. Demonstrable ROI: Clear evidence of productivity gains and cost savings will drive enterprise adoption.
  1. AI-Driven Architecture Design: AI assistants may evolve to suggest optimal system architectures based on project requirements and best practices.
  2. Automated Code Refactoring: AI tools will increasingly offer intelligent refactoring suggestions to improve code quality and maintainability.
  3. Predictive Bug Detection: Advanced AI models will predict potential bugs and security vulnerabilities before they manifest in production environments.
  4. Cross-Language Translation: AI assistants will facilitate seamless translation between programming languages, enabling easier migration and interoperability.
  5. AI-Human Pair Programming: More sophisticated AI agents may act as virtual pair programming partners, offering real-time guidance and code reviews.
  6. Ethical AI Coding: Future AI assistants will incorporate ethical considerations, suggesting inclusive and bias-free code practices.

As these trends unfold, the role of human developers is likely to shift towards higher-level problem-solving, creative design, and AI oversight. By 2025, it’s projected that over 70% of professional software developers will regularly collaborate with AI agents in their coding workflows1. However, the path to ubiquity will depend on addressing key challenges such as reliability, security, and maintaining a balance between AI assistance and human expertise.

The future outlook for AI code assistants is one of transformative potential, with the technology poised to become an integral part of the software development landscape. As these tools continue to evolve, they will likely reshape team structures, development methodologies, and the very nature of coding itself.

Conclusion: A Tool, Not a Panacea

AI code assistants have irrevocably altered software development, delivering measurable productivity gains but introducing new technical and societal challenges. Current metrics suggest they are transitioning from novel aids to essential utilities—63% of enterprises now mandate their use. However, their ascendancy as the de facto standard hinges on addressing security flaws, mitigating cognitive erosion, and fostering equitable upskilling. For organizations, the optimal path lies in balanced integration: harnessing AI’s speed while preserving human ingenuity. As generative models evolve, developers who master this symbiosis will define the next epoch of software engineering.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot