Google Home update could finally fix common Nest camera issue – inkl

The Google Home app just got an update which could fix a common Nest camera issue.
Users who have reported ‘no video available’ errors in the Home app should now see this less frequently.
It’s safe to say that users of Google Home and Nest devices haven’t had the best few months. But now, a new Google Home app update could finally fix a common Nest camera issue – but there’s still no news on what Google plans to do about its other bugs and glitches.
Over the past month, Google Home users have reported many issues with their devices. These glitches have included Google Assistant misunderstanding commands, delayed responses and complete ignoring of questions.
Other issues have also arisen that Google Assistant voice controls no longer work to control smart lights. Many smart home users are fed up with these glitches, and near radio silence regarding any fixes, and there’s even been reports about Google facing a lawsuit.
Amidst the numerous problems that many users are currently experiencing with their Google Home smart devices, there seems to be some light at the end of the tunnel for those who have a Google Nest security camera.
For some time, Nest camera users have stated that they often see ‘no video available’ errors in the Google Home app. This error message is something that has been reported to regularly show in the app when users have tried to open a notification or access a recording.
But thanks to a recent Google Home v3.36 update, Google has said that it’s made improvements to the app, and Nest camera users should see this error message less frequently. As reported by 9to5Google, Google has said “camera users will see fewer cases where a recent video is not yet available for streaming.”
Another fix that’s been reported in the recent app update is camera stream reliability, where Google has “fixed an issue where turning a camera off and on during a live stream would result in a ‘Camera Unavailable’ error, ensuring the stream recovers properly.”
There’s still little news regarding any fixes on other Google Home devices and Google Assistant, but we’re happy to see some improvements being made for Nest users.

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Amazon Bedrock Powers AI for Personalized Education Content Creation – WebProNews

In the rapidly evolving world of educational technology, Amazon Web Services is pushing boundaries with tools like Amazon Bedrock, enabling developers to create sophisticated AI systems for generating course content. A recent AWS Machine Learning Blog post details how engineers can build an end-to-end system that automates the creation of personalized learning materials, from lesson plans to quizzes, using foundation models hosted on Bedrock. This approach leverages models like Anthropic’s Claude to process inputs such as course outlines and generate coherent, tailored content, addressing the growing demand for scalable education solutions amid a surge in online learning.
The system’s architecture, as outlined in the blog, integrates Amazon Bedrock’s serverless capabilities with AWS Lambda for orchestration and Amazon S3 for storage, ensuring seamless scalability without managing infrastructure. Developers input parameters like subject matter, difficulty level, and target audience, and the AI iteratively refines outputs through prompt engineering techniques, producing everything from interactive modules to assessment questions.
Unlocking Efficiency in Content Creation
This innovation comes at a time when generative AI is transforming industries, including education. Recent updates to Amazon Bedrock, as reported in an About Amazon article from last year, include expanded model choices and enhanced security features, making it easier for enterprises to deploy such systems securely. For instance, the ability to customize models with proprietary data allows educators to infuse institution-specific knowledge, reducing the time to create courses from weeks to hours.
Posts on X (formerly Twitter) highlight growing excitement around Bedrock’s applications in machine learning education, with users sharing examples of AI-generated curricula that adapt to learner progress. One thread discussed integrating Bedrock with tools like AWS’s Machine Learning University resources, which have been publicly available since 2020, to automate content for topics like natural language processing.
Technical Deep Dive: From Prompts to Outputs
Diving deeper, the AWS blog explains the use of multi-agent workflows where specialized agents handle tasks like content outlining, drafting, and reviewing for accuracy. This is powered by Bedrock’s agent framework, recently bolstered by the introduction of AgentCore in a preview announced on the AWS News Blog three weeks ago, offering memory management and tool integration for complex operations. In practice, this means an AI agent can cross-reference educational standards while generating material, minimizing hallucinations through grounded responses.
Integration with multimodal capabilities, such as those from Amazon Nova models mentioned in a recent AWS Industries Blog, extends this to visual content like diagrams or videos, enriching courses beyond text. A Coursera course on getting started with Bedrock, available via Coursera, provides hands-on tutorials that align with these workflows, emphasizing best practices for prompt chaining to achieve high-quality outputs.
Real-World Applications and Challenges
Industry insiders are already experimenting with these systems. A WebProNews report from five days ago detailed how Bedrock automates note generation from slides and videos, a feature that could revolutionize corporate training by summarizing lectures into digestible modules. Similarly, another WebProNews piece highlighted its use in drafting reports, underscoring efficiency gains that translate to education, where instructors save time on repetitive tasks.
However, challenges remain, including ensuring content accuracy and ethical AI use. The AWS blog stresses human-in-the-loop reviews to mitigate biases, while updates like comprehensive content protection in Bedrock, as per About Amazon, add safeguards against harmful outputs. Costs are another consideration; Bedrock’s pay-as-you-go model, detailed in a DataCamp tutorial from January, helps manage expenses, but scaling for large institutions requires careful optimization.
Future Prospects and Industry Impact
Looking ahead, Bedrock’s asynchronous agent capabilities, explored in an AWS Machine Learning Blog post from March, promise even more dynamic systems that handle long-running tasks like adaptive learning paths. X posts from educators praise this for democratizing access to customized education, with one recent share linking to a Spanish-language guide on building similar systems, indicating global interest.
As AI-driven tools mature, they could reshape how knowledge is disseminated, making education more inclusive. Yet, as AWS CEO Adam Selipsky noted in a 2023 X post announcing Bedrock, the key is providing choice in foundation models to foster innovation. For industry players, mastering these systems isn’t just about technology—it’s about reimagining learning in an AI-augmented era, with Bedrock positioning AWS as a leader in this shift.
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Lucid Leverage LLC: Leading SEO Agency in Phoenix Expands Digital Marketing Services for Business Growth – The Palm Beach Post

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Lucid Leverage LLC is expanding its services, offering new opportunities for businesses that want to strengthen their digital presence. Based in Tempe, Arizona, Lucid Leverage is known for improving online visibility with a wide range of services. As an SEO agency in Phoenix, the company is dedicated to delivering results that matter for companies across different industries. More information about their services can be found on their website, lucidleverage.com.
The main services offered by Lucid Leverage include Search Engine Optimization (SEO), Social Media Management, and Online Reputation Management. These services are designed to boost brand visibility and maintain a positive public image. What’s important is that they tailor these services to meet the unique needs of each business. This means clients get the focused attention and expertise they need to stand out in today’s competitive market.
Local SEO is a critical part of Lucid Leverage’s strategy. It helps businesses appear more prominently in search engine results, which is crucial for attracting relevant customers and generating new leads. Chris Quintela, the founder of Lucid Leverage, explains, “Our goal is to make sure our clients dominate their local search results. By doing so, we help them build trust and credibility with their target audience.”
Managing online reputation is another key service. It’s vital for businesses to handle negative reviews and false claims to keep a positive image. Lucid Leverage takes pride in offering solutions that highlight good feedback and manage any negative content that might mislead the audience. This is part of their broader mission to help businesses control their public image.
In the realm of Social Media Management, Lucid Leverage develops strategies to boost online engagement, making social networks a key part of their clients’ marketing plans. Their social media services, starting at $299.00 a month, are designed to increase visibility and drive growth by reaching more people.
They also offer Web Design Services for companies aiming to create a strong online presence. Lucid Leverage designs websites that are visually appealing and user-friendly, aligning with modern digital interaction standards. These sites are built to turn visitors into loyal clients, supporting the business’s marketing objectives.
Recognizing the power of multimedia, Lucid Leverage provides YouTube Marketing Services to improve the accessibility and search ranking of business videos. They don’t just distribute content; they also offer production services for those who need high-quality videos to reach their audiences.
Lucid Leverage’s thorough approach is based on a deep understanding of both the opportunities and challenges in digital marketing today. This insight is key to staying ahead of trends and competitors. Quintela noted, “We equip businesses with the tools they need to protect against negative SEO tactics. Our approach is holistic, addressing all aspects of digital content and engagement.”
The company’s ability to diversify its SEO strategies is notable, as it uses not only traditional SEO methods but also social media strategies to guard against harmful SEO threats from rivals. Lucid Leverage’s advertising and content strategies are about not just protecting businesses but also helping them grow.
Lucid Leverage stays committed to adapting to the needs of the businesses they serve, particularly as digital environments continue to shift. The company is ready for future growth, strengthening its role as a leading SEO agency in Phoenix, with proven successes in brand and reputation management.
As the need for effective online marketing solutions increases, Lucid Leverage is prepared to help businesses build durable and engaging digital presences. Each strategy is customized to ensure the greatest impact, setting clients up for success in an increasingly connected world.
Chris Quintela concluded, “We see ourselves not just as service providers but as partners in our clients’ growth. We’re excited to continue this journey and look forward to achieving even greater results through our expanded services.”
The post Lucid Leverage LLC: Leading SEO Agency in Phoenix Expands Digital Marketing Services for Business Growth appeared first on DA80 Hub.
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Google Patches Vulnerability That Let Anyone Hide Search Results – TechRepublic

Google Patches Vulnerability That Let Anyone Hide Search Results  TechRepublic
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Apple Patches Zero-Day Exploit Targeting Google Chrome Users – TechRepublic

Apple Patches Zero-Day Exploit Targeting Google Chrome Users  TechRepublic
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AI-powered ad testing—How Delta and other brands are determining the precise impact of their marketing – Ad Age

Brands explored everything from absurdist humor to AI storytelling, from Super Bowl spectacles to low-fi stunts, in the first seven months of the year.

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Proving SEO Value in AI Era: Strategies for ROI and Growth – WebProNews

In the rapidly evolving world of digital marketing, where artificial intelligence is reshaping search behaviors, proving the tangible value of search engine optimization (SEO) has become a critical challenge for marketers and executives alike. As AI-driven tools like Google’s AI Overviews and ChatGPT dominate user queries, traditional metrics such as click-through rates are plummeting, forcing a reevaluation of how SEO contributes to business growth. According to a recent analysis in Search Engine Journal, the key to securing buy-in lies in demonstrating SEO’s worth through innovative tracking and forecasting methods that align with stakeholder priorities.
This shift is not just theoretical; it’s grounded in real-time data showing that AI is siphoning off organic traffic. For instance, impressions may rise as content appears in AI summaries, but actual site visits often drop, creating a disconnect between visibility and revenue. Marketers must now pivot to metrics that capture AI-era dynamics, such as share of voice in AI responses or the quality of referral traffic from diverse platforms.
Tracking AI Visibility as a Core Metric
One effective strategy highlighted by industry experts involves monitoring AI visibility to quantify SEO’s impact beyond traditional search results. By using tools that track how often a brand’s content is cited in AI-generated answers, companies can demonstrate sustained relevance. A post on X from SEO veteran Matt Diggity emphasizes that entity optimization—focusing on building a brand’s knowledge graph presence—is crucial for dominating AI platforms like Gemini and ChatGPT, turning potential traffic losses into opportunities.
Complementing this, competitive benchmarking provides a clearer picture of SEO’s ROI. Instead of isolated performance data, comparing a site’s AI visibility against rivals reveals market share gains. For example, if a competitor’s content appears in 40% of AI overviews for key queries while yours lags at 15%, this gap becomes a compelling argument for increased SEO investment, as noted in recent insights from Backlinko.
Forecast Modeling for Predictive ROI
Forecasting models are another powerful tool, allowing teams to project future traffic and revenue based on current SEO efforts. By integrating historical data with AI trends, these models can predict outcomes like a 20% uplift in qualified leads if E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) guidelines are fully implemented. A detailed guide in Fast Frigate stresses that incorporating real-world proof, such as case studies, bolsters these forecasts, making them more persuasive to C-suite executives skeptical of intangible digital strategies.
Real-world applications underscore this approach’s effectiveness. Take Zapier’s rise, documented in Glorywebs, where targeted content optimization led to a 300% traffic increase by aligning with user intent across AI-influenced searches. Such examples illustrate how forecasting isn’t guesswork but a data-driven narrative that ties SEO to bottom-line results.
Leveraging Case Studies for Credible Proof
To further solidify SEO’s value, integrating case studies from successful campaigns provides empirical evidence. A compilation of 19 SEO success stories in AIOSEO reveals patterns like Airbnb’s use of localized content to capture high-intent searches, resulting in millions in additional bookings. These narratives counter doubts by showing compounded ROI over time, especially in an AI context where trust signals like backlinks and author expertise amplify visibility.
Industry insiders on X, including Neil Patel, point to a broader trend: optimizing for all platforms, not just Google, with daily searches totaling 45.1 billion across ecosystems. This multi-platform strategy ensures diversified traffic, reducing reliance on any single source and proving SEO’s resilience.
Addressing Stakeholder Concerns with Diversified Metrics
Stakeholders often question SEO’s cost-effectiveness amid AI disruptions, but diversified metrics offer a robust defense. By measuring not only traffic but also user engagement and conversion paths influenced by AI referrals, marketers can highlight holistic value. A recent X thread from SA News Channel on SEO copywriting pillars reinforces that people-first content, blended with SERP strategy, yields measurable trust and authority gains.
Moreover, as Bruce Clay Inc. detailed in a Semrush collaboration, emerging trends like voice search and personalized AI experiences demand adaptive strategies. Proving value here involves showing how SEO fosters long-term brand authority, turning one-time visitors into loyal customers through consistent, high-quality interactions.
Building a Compelling Narrative for Investment
Ultimately, the narrative around SEO must evolve to emphasize its role as a foundational growth driver in the AI age. By combining AI visibility tracking, predictive modeling, and competitive insights with real case studies, professionals can craft arguments that resonate with decision-makers. Insights from Jolt Collective affirm that SEO remains essential for relevance and competitiveness, transforming skepticism into strategic commitment.
As 2025 unfolds, those who master these proof strategies will not only secure budgets but also position their brands to thrive amid ongoing innovations. The evidence is clear: SEO’s real value lies in its adaptability, delivering sustained visibility and revenue in an increasingly AI-dominated digital ecosystem.
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Grok Imagine, xAI’s new AI image and video generator, lets you make NSFW content – TechCrunch

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Elon Musk’s AI company has officially rolled out Grok Imagine, xAI’s image and video generator, to all SuperGrok and Premium+ X subscribers on its iOS app. And true to form for Musk, who positions Grok as an unfiltered, boundary-pushing AI, the generator allows users to make NSFW content. 
Grok Imagine, which promises to turn text or image prompts into a 15-second video featuring native audio, has a “spicy mode” that allows users to generate sexually explicit content, including partial female nudity . There are limits to how explicit one can get. Many of our spicier prompts — made in the name of Journalism! — generate blurred-out images that are “moderated” and therefore inaccessible. We were, however, able to generate semi-nude imagery. 
Imagine with @Grok pic.twitter.com/UIay5yNp97
The NSFW content is unsurprising for xAI, given the release last month of a raunchy, hyper-sexualized anime AI companion. But just as Grok’s unrestrained nature was entertaining until it started spewing hateful, antisemitic, misogynistic content, Grok Imagine could be poised to bring its own set of unintended consequences. 
CNBC first reported the existence of a “spicy mode” last week after xAI employee Mati Roy said in a now-deleted post on X: “Grok Imagine videos have a spicy mode that can do nudity.” 
TechCrunch has reached out to xAI for more information. 
The existing limitations with Grok Imagine are somewhat heartening given the model also lets you create content of celebrities — anyone from Donald Trump to Taylor Swift — and there appear to be additional restrictions on those. For example, TechCrunch tried, and failed, to generate an image of Trump pregnant. Grok Imagine only generated images of Trump holding a baby or next to a pregnant woman. 
While it’s still early days for Grok Imagine, which aims to compete with incumbents like Google DeepMind, OpenAI, Runway, and Chinese rivals, the images and videos generated of humans are still a bit lost in the uncanny valley, with waxy-looking skin that verges on cartoonish at times. 
Still, the generator is impressive. It produces images in seconds from a text prompt, and continues to auto-generate new images as you scroll. Those images can then be animated into stylized videos. The user interface is also seamless and intuitive. 
Musk said on X that the model would “get better every day.”
Testing out Grok Imagine 👀 pic.twitter.com/G943K0soNJ
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Rebecca Bellan is a senior reporter at TechCrunch, where she covers Tesla and Elon Musk’s broader empire, autonomy, AI, electrification, gig work platforms, Big Tech regulatory scrutiny, and more. She’s one of the co-hosts of the Equity podcast and writes the TechCrunch Daily morning newsletter. Previously, she covered social media for Forbes.com, and her work has appeared in Bloomberg CityLab, The Atlantic, The Daily Beast, Mother Jones, i-D (Vice) and more. Rebecca has invested in Ethereum.
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Google Merchant Knowledge Panel Deals Section Update – Search Engine Roundtable

Google Sale Sign
Google has replaced the promotions section in the merchant local knowledge panel with a deals section. There are still clipable coupons but it is renamed “Deals” instead of it saying “Promotions.” There is also a new green percentage icon next to each deal.
This was spotted by both Sachin Patel on X and later by Brodie Clark on X/SERP Alerts. Here is the new version:
Google Deals Promotions Coupon
Here is the old version:
Google Local Knowledge Panel Promotions
Here is another version:
Google Deals Promotions Coupon 2
Brodie wrote:

Google is now showing a new treatment for promotions within merchant knowledge panels.
The section is now showing underneath a ‘deals’ heading that displays a green % badge alongside each individual promotion.
After clicking the ‘view all deals’ tab, all deals are then featured at top of the page within the same knowledge panel experience.
This makes promotions that are loaded into GMC Next more prominent for branded queries with a more engaging treatment compared to previously.

Then there is also this:

Noticed a similar 'deals' section showing for a client of mine today. The treatment is similar to what was originally described within a brand profile that's managed in GMC: https://t.co/pIps85tcFL. Is this another sign of a broader rollout of this feature? https://t.co/e2YeDQkN4f pic.twitter.com/Odnk6a4PpT
These deals do stand out more with these green icons and the word “Deals” doesn’t hurt.
Forum discussion at X.
The content at the Search Engine Roundtable are the sole opinion of the authors and in no way reflect views of RustyBrick ®, Inc
Copyright © 1994-2025 RustyBrick ®, Inc. Web Development All Rights Reserved.
This work by Search Engine Roundtable is licensed under a Creative Commons Attribution 3.0 United States License. Creative Commons License and YouTube videos under YouTube’s ToS.

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Building an AI-driven course content generation system using Amazon Bedrock – Amazon Web Services


AWS Blogs
The education sector needs efficient, high-quality course material development that can keep pace with rapidly evolving knowledge domains. Faculty invest days to create content and quizzes for topics to be taught in weeks. Increased faculty engagement in manual content creation creates a time deficit for innovation in teaching, inconsistent course material, and a poor experience for both faculty and students.
Generative AI–powered systems can significantly reduce the time and effort faculty spend on course material development while improving educational quality. Automating content creation tasks gives educators more time for interactive teaching and creative classroom strategies.
The solution in this post addresses this challenge by using large language models (LLMs), specifically Anthropic’s Claude 3.5 through Amazon Bedrock, for educational content creation. This AI-powered approach supports the automated generation of structured course outlines and detailed content, reducing development cycles from days to hours while ensuring materials remain current and comprehensive. This technical exploration demonstrates how institutions can use advanced AI capabilities to transform their educational content development process, making it more efficient, scalable, and responsive to modern learning needs.
The solution uses Amazon Simple Queue Service (Amazon SQS), AWS Lambda, Amazon Bedrock, Amazon API Gateway WebSocket APIs, Amazon Simple Storage Service (Amazon S3), Amazon CloudFront, Amazon DynamoDB, Amazon Cognito and AWS WAF. The architecture is designed following the AWS Well-Architected Framework, facilitating robustness, scalability, cost-optimization, high performance, and enhanced security.
In this post, we explore each component in detail, along with the technical implementation of the two core modules: course outline generation and course content generation. Course outline generates course structure for a subject with module and submodules by week. Primary and secondary outcomes are generated in a hierarchical structure by week and by semester. Content generation is content generated for the module and submodule generated in content outline. Content generated includes text and video scripts with corresponding multiple-choice questions.
The solution architecture integrates the two core modules through WebSocket APIs. This design is underpinned by using AWS Lambda function for serverless compute, Amazon Bedrock for AI model integration, and Amazon SQS for reliable message queuing.
The system’s security uses multilayered approach, combining Amazon Cognito for user authentication, AWS WAF for threat mitigation, and a Lambda authorizers function for fine-grained access control. To optimize performance and enhance user experience, AWS WAF is deployed to filter out malicious traffic and help protect against common web vulnerabilities. Furthermore, Amazon CloudFront is implemented as a WebSocket distribution layer, to significantly improve content delivery speeds and reduce latency for end users. This comprehensive architecture creates a secure, scalable, and high-performance system for generating and delivering educational content.
Comprehensive AWS architecture diagram for course design system utilizing Lambda, API Gateway, SNS, DynamoDB, and Bedrock LLM for processing and storing course content
Course WebSocket API manages real-time interactions for course outline and content generation. WebSockets enable streaming AI responses and real-time interactions, reducing latency and improving user responsiveness compared to traditional REST APIs. They also support scalable concurrency, allowing parallel processing of multiple requests without overwhelming system resources. AWS WAF provides rule-based filtering to help protect against web-based threats before traffic reaches API Gateway. Amazon CloudFront enhances performance and security by distributing WebSocket traffic globally. Amazon Cognito and JWT Lambda authorizer function handles authentication, validation of user identity before allowing access.
Each WebSocket implements three primary routes:
The WebSocket API integrates Amazon Cognito for authentication and uses a JWT-based Lambda authorizer function for token validation. The authentication flow follows these steps:
The following is a sample AWS CDK code to set up the WebSocket API with Amazon Cognito. AWS CDK is an open source software development framework to define cloud infrastructure in code and provision it through AWS CloudFormation. The following code is written in Python. For more information, refer to Working with the AWS CDK in Python:
The course outline generation module helps course designers create a structured course outline. For this proof of concept, the default structure spans 4 weeks, with each week containing three main learning outcomes and supporting secondary outcomes, but it can be changed according to each course or institution’s reality. The module follows this workflow:
The following code sample is a sample payload for the courseOutline route, which can be customized to meet institutional requirements. The fields are defined as follows:
When interacting with the courseOutline route of the WebSocket API, the response follows a structured format that details the course outline and structure. The following is an example of a WebSocket response for a course. This format is designed for straightforward parsing and seamless integration into your applications:
Here’s a snippet of the Lambda function for processing the outline request:
The course content generation module creates detailed week-by-week content based on the course outline. Although the default configuration generates the following for each main learning outcome, these outputs are fully customizable to meet specific course needs and institutional preferences:
The module follows this workflow:
The following is a sample payload for the courseContent route, which can be customized to align with institutional requirements. The fields are defined as follows:
When interacting with the courseContent route of the WebSocket API, the response follows a structured format that details the course content. The following is an example of a WebSocket response for a course content. This format is designed for easy parsing and seamless integration into your applications:
Here’s a Lambda function code snippet for content generation:
To implement the solution provided in this post, you should have the following:
When the prerequisite steps are complete, you’re ready to set up the solution:
The activation of the virtual environment differs based on the operating system; refer to the AWS CDK workshop for activating in other environments.
export AWS_REGION=”<region>” # Same region as ACCOUNT_REGION above
export AWS_ACCESS_KEY_ID=”<access-key>” # Set to the access key of your role/user
export AWS_SECRET_ACCESS_KEY=”<secret-key>” # Set to the secret key of your role/user
Note the CloudFront endpoints, WebSocket API endpoints, and Amazon Cognito user pool details from deployment outputs.
The solution is designed with scalability and security as core principles. Because Amazon API Gateway for WebSockets doesn’t inherently support AWS WAF, we’ve integrated Amazon CloudFront as a distribution layer and applied AWS WAF to enhance security.
By using Amazon SQS and AWS Lambda, the system enables asynchronous processing, supports high concurrency, and dynamically scales to handle varying workloads. AWS WAF helps to protects against malicious traffic and common web-based threats. Amazon CloudFront can improve global performance, reduce latency, and provide built-in DDoS protection. Amazon Cognito handles authentication so that only authorized users can access the WebSocket API. AWS IAM policies enforce strict access control to secure resources such as Amazon Bedrock, Amazon S3, AWS Lambda, and Amazon DynamoDB.
To avoid incurring future charges on the AWS account, invoke the following command in the terminal to delete the CloudFormation stack provisioned using the AWS CDK:
This innovative solution represents a significant leap forward in educational technology, demonstrating how AWS services can be used in course development. By integrating Amazon Bedrock, AWS Lambda, WebSockets, and a robust suite of AWS services, we’ve built a system that streamlines content creation, enhances real-time interactivity, and facilitates secure, scalable, and high-quality learning experiences.
By developing comprehensive course materials rapidly, course designers can focus more on personalized instruction and student mentoring. AI-assisted generation facilitates high-quality, standardized content across courses. The event-driven architecture scales effortlessly to meet institutional demands, and CloudFront, AWS WAF, and Amazon Cognito support secure and optimized content delivery. Institutions adopting this technology position themselves at the forefront of educational innovation, redefining modern learning environments.
This solution goes beyond simple automation—it means teachers and professors can shift their focus from manual content creation to high-impact teaching and mentoring. By using AWS AI and cloud technologies, institutions can enhance student engagement, optimize content quality, and scale seamlessly.
We invite you to explore how this solution can transform your institution’s approach to course creation and student engagement. To learn more about implementing this system or to discuss custom solutions for your specific needs, contact your AWS account team or an AWS education specialist.
Together, let’s build the future of education on the cloud.
Dinesh Mane is a Senior ML Prototype Architect at AWS, specializing in machine learning, generative AI, and MLOps. In his current role, he helps customers address real-world, complex business problems by developing machine learning and generative AI solutions through rapid prototyping.
Tasneem Fathima is Senior Solutions Architect at AWS. She supports Higher Education and Research customers in the United Arab Emirates to adopt cloud technologies, improve their time to science, and innovate on AWS.
Amir Majlesi leads the EMEA prototyping team within AWS Worldwide Specialist Organization. Amir has extensive experiences in helping customers accelerate adoption of cloud technologies, expedite path to production and catalyze a culture of innovation. He enables customer teams to build cloud native applications using agile methodologies, with a focus on emerging technologies such as Generative AI, Machine Learning, Analytics, Serverless and IoT.
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