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Engadget

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The best laptops for college students

A good laptop is a sensible investment for every college student.
The best laptop for college is ideally thin and lightweight, with long battery life.
Consider your major and specific program requirements when choosing your laptop.
Ultraportables generally cost between $1,000 and $1,400, but budget options are available.

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Guardian

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What could Apple’s high court challenge mean for data protection?

Apple to challenge UK government demand for access to encrypted customer data in high court hearing.
UK government wants Apple to provide backdoor access to Apple's Advanced Data Protection service.
Apple objects to the request, citing privacy as a core value and denying building backdoors.
Apple's chances of winning the challenge are hindered by closed-door hearings and past rulings favoring the UK government.

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Digitaltrends

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Nvidia claims RTX 5000 shipped better than 4000 but gamers are still waiting

Nvidia claims that the RTX 5000 series GPUs are selling better than the previous generation, but skeptics question the availability and actual consumer reach.
Media has raised concerns about Nvidia's supply of RTX 5000 series GPUs, with many high-end models seemingly in the hands of reviewers and enthusiasts rather than everyday gamers.
Third-party pricing and supply challenges have plagued the RTX 5000 series, leading some consumers to resort to scalpers for purchasing.
Nvidia VP assures efforts to increase supply of RTX 5000 series GPUs amidst high demand, though critics doubt the extent of the claimed improvement over previous series.
The launch of RTX 5000 series faced supply constraints and multiple model releases within a short timeframe, fueling skepticism around availability.
Media scrutiny highlights limited supply issues and extravagant pricing for RTX 5000 GPUs, hinting at an ongoing struggle to meet consumer demands.
While newer GPU models face challenges, older Nvidia models like the RTX 4060 remain popular among gamers for their availability and affordability.
Steam survey shows RTX 4060 as a favored option due to its reasonable pricing, indicating that gamers are content with existing GPU options.
Nvidia's RTX 5060 and ongoing developments face scrutiny amidst concerns about the brand's management of supply constraints and consumer expectations.
Despite the hype around the latest GPUs, availability and competitive pricing of existing models continue to cater to the needs of most gamers.

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Dev

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[ Solution Library AWS ] Live Chat Content AI on AWS

The Live Chat Content Moderation with generative AI on AWS project aims to create a scalable, real-time chat moderation system for live chat platforms using AWS services and generative AI.
The architecture involves services like Amazon API Gateway, AWS Lambda, Amazon DynamoDB, Amazon SQS, AWS AppSync, Amazon Bedrock, among others, ensuring real-time moderation using generative AI and multiple AI model support.
AWS services costs vary based on usage, such as Amazon API Gateway, AWS Lambda, Amazon DynamoDB, etc., and a monthly cost estimate example is detailed for various services.
The system supports four AI models for chat moderation, each with different capabilities and strengths, allowing users to switch between these models.
Prerequisites for deployment include an AWS Account, AWS CLI, Node.js, Git, and jq installed, with steps outlined for deployment, deployment validation, and usage after installation.
Deployment validation involves checking the status of various resources like CloudFormation stack, DynamoDB tables, Lambda function, SQS queues, AppSync API, and CloudFront distribution to confirm a successful deployment.
Monitoring and observability through CloudWatch dashboard, performance considerations, security measures like encryption at rest and least-privilege IAM roles, and cleanup steps are highlighted for efficient system management.
Next steps for system enhancement include customizing AI prompts, implementing user authentication, and enhancing DDoS attack protection using AWS Shield Advanced.
Readiness notices emphasize the customer's independent assessment responsibility, and the authors of the project are Gabriel Costa and Juliano Baeta.

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Dev

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DevOps with AWS CodePipeline

Integrate GitLab/Github repositories with AWS CodePipeline to automate the CI/CD process.
The integration allows for automatic triggering of pipeline actions when code changes are pushed to GitLab.
The setup provides benefits of automation and scalability for DevOps workflows.
It allows developers to focus on writing code while automation handles building and deploying applications.

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Digitaltrends

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Apple CEO should do a Steve Jobs on Siri delay, analyst says

Apple CEO Tim Cook should go public to explain the delay in integrating advanced Siri capabilities across its ecosystem.
Prominent Apple analyst Ming-Chi Kuo suggests that Apple should handle the delay in a similar manner that Steve Jobs dealt with the 'antennagate' crisis.
Kuo believes that the recent announcement of the Siri delay through an unofficial channel is not how the world's most valuable company should handle a PR crisis.
Apple is intentionally avoiding an Apple Maps-type error and won't release the enhanced Siri tool until it's sure it's ready.

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Dev

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TiDB Serverless vs Amazon RDS: The Ultimate Cloud Database Showdown

TiDB Serverless and Amazon RDS are compared to determine the best cloud database service.
Scalability: Amazon RDS requires selecting an instance size and lacks the ability to scale down to zero, while TiDB Serverless offers autonomous capacity ramp-up and scales both reads and writes without single node bottlenecks.
Reliability: TiDB Serverless provides automated failover and strong ACID guarantees, while Amazon RDS requires manual setups and has higher costs for redundancy.
Developer-Friendly Features: TiDB Serverless offers built-in AI features and greater flexibility as an open-source solution, while Amazon RDS simplifies database management within AWS.

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Dev

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Azure Logic Apps & AWS Step Functions

Azure Logic Apps and AWS Step Functions offer graphical approaches to deploying workflows, suitable for teams lacking programming expertise or seeking simplicity in workflow implementation.
These tools aim to reduce complexity and allow engineers to create complex workflows without extensive coding, serving as No-Code solutions.
Logic Apps and Step Functions help visualize workflows with cause-and-effect relationships, simplifying the process and directing actions from start to completion.
AWS Step Functions provide a straightforward way to set up no-code solutions, guiding users through template selection and customization.
Within Step Functions, tasks can be edited and configured according to requirements, with options for exporting configurations and generating diagrams.
In contrast, Azure Logic Apps, while offering similar functionalities, caters to specific actions like those in Buffer, a social media service.
AWS Step Functions are considered more developer-friendly, while Azure Logic Apps are perceived as more suitable for specific actions outside engineering.
Overall, AWS Step Functions are perceived as better suited for engineers looking for a simpler way to handle workloads, while Azure Logic Apps are more tailored to non-engineering tasks.

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Dev

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AI Agents For Cloud & DevOps Engineers: RAG Operations

AI is not taking away jobs in engineering fields like cloud and DevOps; instead, it can create new job opportunities.
AI Agents are specialized in performing specific tasks effectively, such as writing code or generating responses.
RAG (Retrieval Augmented System) enhances a Large Language Model by providing access to real-time external data sources.
Fine-tuning a model involves retraining it on specific data sets, while RAG allows feeding external information to the model.
Weights in AI models determine the importance of words and ideas in responses, affecting the output.
Using base models like GPT and implementing RAG operations with tools like Serper and WebsiteSearchTool can optimize task performance.
Local model deployment with Ollama and leveraging the langchain_openai library enable using AI models locally for specific tasks.
Creating RAGs involves specifying websites for information retrieval and using them in AI Agent tools for enhanced functionality.
Code generation with AI Agents involves setting allow_code_execution to create and execute code for specific tasks like deploying clusters.
DevOps professionals can enhance their skills by learning to create and deploy AI Agents for performing engineering tasks effectively.

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Siliconangle

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PagerDuty delivers strong earnings and revenue beat, boosting its stock

PagerDuty Inc. reported Q4 earnings that beat expectations.
The company's revenue for the quarter rose 9% to $121.4 million from a year earlier.
PagerDuty's stock gained more than 5% in after-hours trading.
The company also reported annual recurring revenue of $494 million, up 9% from the previous year.

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Siliconangle

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Docusign shares rise on earnings and revenue beat

Docusign Inc. shares rose over 10% in late trading after reporting earnings and revenue beats in its fiscal 2025 fourth quarter.
For the quarter, adjusted earnings per share were 86 cents, exceeding analysts' expectations of 84 cents.
Quarterly revenue increased to $776.3 million, up 9% year-over-year. Subscription revenue rose 9% to $757.8 million.
Docusign's full fiscal year 2025 showed adjusted earnings per share of $3.55, with revenue of $2.98 billion, up 8% from the previous year.

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Siliconangle

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Docusign shares jump on earnings and revenue beat

Shares in Docusign Inc. rose almost 16% after reporting earnings and revenue beats in its Q4 FY2025.
Docusign reported adjusted earnings of 86 cents per share and revenue of $776.3 million, both beating analysts' expectations.
Subscription revenue rose 9% and professional services and other revenue rose 11% in the quarter.
For FY2025, Docusign reported adjusted earnings per share of $3.55 and revenue of $2.98 billion.

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AWS Blogs

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Collaborate and build faster with Amazon SageMaker Unified Studio, now generally available

Amazon SageMaker Unified Studio is now generally available, providing a unified data and AI development environment for users to access and act on data across various use cases.
The platform integrates tools from Amazon Athena, EMR, Glue, Redshift, Managed Workflows for Apache Airflow, and SageMaker Studio.
New capabilities for Amazon Bedrock include support for new foundation models and Amazon Q Developer, a generative AI assistant, is now generally available in SageMaker Unified Studio.
Developers can create and customize generative AI applications using Amazon Bedrock within the SageMaker Unified Studio.
Amazon Q Developer offers assistance with data processing, SQL analytics, ML model development, and generative AI application development.
It simplifies tasks like writing SQL queries, troubleshooting, and generating real-time code suggestions through natural language interactions.
Amazon SageMaker Unified Studio is available in various AWS Regions and Amazon Q Developer subscription is offered in free and Pro Tiers.
The platform enhances collaboration and streamlines generative AI setup with user-friendly interfaces for model governance across multiple AWS accounts.
Users can leverage powerful generative AI capabilities of Amazon Bedrock for building data products and AI applications within a unified workspace.
To get started, create a SageMaker Unified Studio domain via the Amazon SageMaker console and access new features for enhanced collaborative development.

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Tech Radar

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I tried Gemini's new AI image generation tool - here are 5 ways to get the best art from Google's Flash 2.0

Gemini Flash 2.0 by Google offers a fast image creation tool with notable speed and quality improvements compared to others like DALL-E 3.
To get the best results from Gemini Flash, telling a story and instructing it to generate a series of related images can be engaging and effective.
Being super specific in your instructions to Gemini Flash can lead to more accurate and detailed image outputs.
Engaging in a conversational style with Gemini Flash allows you to make edits and adjustments to the generated images, enhancing customization.
Gemini Flash's ability to match ChatGPT in terms of real-world knowledge enables users to request historically accurate and culturally detailed imagery.
Utilizing Gemini Flash's efficient text integration feature, users can quickly and clearly incorporate text into generated images.
By following these tips, users can maximize the potential of Google's Gemini Flash 2.0 for creating high-quality and personalized AI-generated art.
Interacting with Gemini Flash through detailed and specific commands can result in images that closely match the envisioned concepts.
Gemini Flash's features like quick text rendering and conversational adjustments make it a versatile tool for creating diverse and customized AI art.
The advancements in AI art generation tools like Gemini Flash showcase the evolving capabilities and possibilities in the field of artificial intelligence and creative applications.

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AWS Blogs

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Amazon S3 Tables integration with Amazon SageMaker Lakehouse is now generally available

Amazon S3 Tables, integrated with Apache Iceberg, and Amazon SageMaker Lakehouse were launched to simplify tabular data storage and analytics collaboration.
S3 Tables integration with AWS analytics services like Amazon Athena, EMR, Redshift, and others allows for streamlined querying and visualization of data.
Customers can leverage S3 Tables and SageMaker Lakehouse for unified access to multiple data sources, enhancing analytics and machine learning workflows.
The general availability of Amazon S3 Tables integration with Amazon SageMaker Lakehouse enables unified data access across various analytics engines.
Users can centrally manage access permissions on S3 Tables data, Redshift, and other sources within SageMaker Lakehouse for secure analytic workflows.
To get started with S3 Tables integration, users can create table buckets and access them from AWS analytics services like Amazon Athena.
Integration with Amazon SageMaker Unified Studio enables querying S3 data lakes, Redshift, and other sources directly within SageMaker Lakehouse.
Data engineers can join S3 Tables data with data from various sources, such as DynamoDB and Redshift, to gain deeper insights without ETL scripts.
The availability of S3 Tables integration with SageMaker Lakehouse in all AWS Regions offers users a unified data access experience.
Users are encouraged to try out S3 Tables in SageMaker Unified Studio and provide feedback for further enhancements.

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