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Engadget

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The best laptop power banks for 2025

The article highlights the importance and benefits of using laptop power banks for travel and work purposes, providing recommendations based on testing and personal experience.
An important update is mentioned regarding Anker's PowerCore 10000 power bank recall due to a fire risk issue, advising affected users to contact Anker for replacements or alternative compensation.
Key considerations for selecting a laptop power bank are explained, such as capacity requirements, airport regulations for portable batteries, and the impact of voltage on actual device charging.
The article discusses the significance of multiple USB ports, including USB-C and USB-A variations, for charging different devices efficiently and the importance of choosing the right wattage for optimal charging speeds.
It also covers the evolution of wireless charging capabilities in power banks, emphasizing improvements in speed but highlighting the efficiency differences compared to wired connections.
Design aspects of laptop power banks are addressed, focusing on portability, weight considerations, display features, and the placement of charging ports and wireless pads for user convenience.
The testing methodology for portable laptop chargers is outlined, detailing the devices used for testing, the criteria evaluated, and the importance of considering capacities when selecting a suitable power bank for laptops.
Frequently asked questions about laptop power banks are answered, covering topics such as differences from phone power banks, fast charging methods, recommended capacities for laptops, and understanding mAh vs. watt-hours for battery comparisons.
Recent updates include testing results from UGreen Power Bank and additional information on airline regulations related to battery banks.

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Microsoft

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Announcing comprehensive sovereign solutions empowering European organizations

Microsoft is expanding efforts with Microsoft Sovereign Cloud to empower European organizations with more control over their data privacy and digital resilience.
They are offering Data Guardian, External Key Management, Regulated Environment Management, and Microsoft 365 Local for European operations.
Sovereign Public Cloud ensures customer data stays in Europe, under European Law, with operations controlled by European personnel.
Sovereign Private Cloud supports critical services workloads using Azure Local and Microsoft 365 Local.
National Partner Clouds in France and Germany provide comprehensive capabilities of Microsoft 365 and Azure in independently operated environments.
Microsoft Sovereign Cloud aims to provide integrated productivity, security, and cloud solutions for European organizations.
Sovereign Public Cloud offers evolving sovereign capabilities without the need for separate duplicate systems or limiting cutting-edge technologies.
The additional features like Data Guardian, External Key Management, and Regulated Environment Management enhance data protection and access control.
Sovereign Private Cloud with Azure Local and Microsoft 365 Local allows organizations to meet specific data residency and sovereignty requirements.
Microsoft is building a sovereign cloud and AI partner ecosystem for Europe to support the implementation and operation of sovereign solutions.
Microsoft Sovereign Cloud is grounded in European Digital Commitments, offering choice, control, and resilience for European customers.

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Silicon

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AstraZeneca In $5.3bn AI Drug Discovery Deal With China’s CSPC

AstraZeneca has entered a $5.3 billion deal with China's CSPC Pharmaceutical to use AI technology for developing oral drugs.
The deal involves an upfront payment of $110 million to CSPC for using AI-driven drug discovery to analyze molecules for clinical success.
The collaboration aims to address chronic health conditions affecting over two billion people globally.
AstraZeneca highlighted the significance of partnerships in enhancing therapeutic molecule discovery for future medicines.
The companies will focus on preclinical candidates targeting diseases across various chronic indications, including immunological diseases.
CSPC stands to receive up to $1.62 billion in development milestone payments and $3.6 billion in sales milestones along with royalties.
AstraZeneca had previously licensed a preclinical cardiovascular drug from CSPC for $100 million upfront.
AstraZeneca is expanding its presence in China with a strategic research and development center in Beijing, part of a $2.5 billion investment in the city.
The company faced challenges in China when its former China head, Leon Wang, was detained in connection with an investigation on illegal drug importation.

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Silicon

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Apple ‘Eyes Spring 2026’ For Delayed Siri AI Upgrade

Apple aims to release its delayed Siri upgrade in spring 2026 to boost its AI efforts.
The Siri upgrade is targeted to be part of the planned iOS 26.4 software release in March.
No exact date has been set, but a spring release timeframe is expected.
The major Siri revamp might be previewed during the autumn iPhone release if development progresses well.
Apple faced delays in releasing the Siri AI features due to technical challenges, pushing the release indefinitely.
The delays have impacted Apple's AI strategy, affecting the sales pitch for new iPhones.
Apple reorganized its AI development teams earlier, relocating Siri responsibilities to Mike Rockwell and Craig Federighi.
Apple is aiming to develop a more complex 'LLM Siri' powered by a large language model for advanced AI tasks.
Initial attempts to combine the new features with the basic software led to errors and necessitated rebuilding Siri from scratch.
Apple is debating internally on the extent of developing AI technology in-house versus relying on external partners like OpenAI.
The company has also considered acquiring AI start-ups to enhance its AI capabilities.
Tech firms, including Meta Platforms, have shifted between internal AI development and external investments to boost AI capabilities.

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Fintechnews

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Amazon to Invest AU$20 Billion in Australia to Expand Cloud, AI Infrastructure

Amazon plans to invest AU$20 billion in Australia between 2025 and 2029 to expand its cloud infrastructure through AWS, the largest tech investment in Australia to date.
The investment aims to meet growing demand for cloud computing and AI services and support national efforts to strengthen AI capability.
It will enhance AWS infrastructure in Australia, building on previous expansions and partnerships including a high-security cloud agreement with the Australian Government.
AWS also introduced AWS AI Spring Australia to accelerate generative AI use across various sectors.
Initiatives like AWS Generative AI Accelerator and AWS AI Launchpad will aid startups and enterprises in adopting AI technologies.
AWS has trained over 400,000 individuals in Australia since 2017 and plans to continue supporting workforce development through programs like the Work-Based Learning Program.
Prime Minister Anthony Albanese praised the investment, highlighting the economic opportunities and innovation it will bring to Australia, including creating skilled jobs and infrastructure for advanced AI and supercomputing applications.
Matt Garman, CEO of AWS, emphasized the expansion of data center infrastructure, renewable energy projects, and support for Australia's aspiration to become a global AI leader.

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Medium

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An AI-Powered Framework for Scalable Cloud Migration in Financial Services and Critical…

Legacy IT systems in financial services and critical infrastructure sectors pose challenges for cloud migration due to complex architectures, regulations, and risks.
An AI-driven framework is introduced to automate and optimize cloud migration in mission-critical environments.
The framework utilizes transformer-based code analysis, graph neural network dependency mapping, and NLP for compliance simulation.
It reduces migration time, downtime, and compliance violations, improving operational resilience and modernization.
Evaluations with JPMorgan Chase, Bank of America, Capital One, and Citi show positive results in legacy modernization.
AI-assisted migration enables secure, compliant, and efficient modernization aligned with business demands.
Financial institutions and critical infrastructure are undergoing digital transformation using cloud computing for scalability and cost efficiency.
Legacy IT systems consist of millions of lines of COBOL, PL/SQL, or proprietary code, making migration challenging.

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Dev

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A Simple ECS + ECR Project for Beginners

This article provides a simple walkthrough for beginners on deploying applications using Amazon ECS and ECR with Terraform.
Services used include Amazon ECR, Amazon ECS with Fargate, Amazon VPC, Application Load Balancer, CloudFront, Amazon S3, CloudWatch, Amazon SNS, and Terraform.
Deployment steps involved initializing Terraform, formatting the Terraform code, preparing Docker images, and pushing them to ECR.
After deployment, accessing the application involves utilizing URLs generated by Terraform.
The article also covers cleaning up resources after deployment to avoid costs and provides solutions for errors during resource deletion.
The flow summary includes steps from user request to response, along with design choices and customization options.
Tips are included for handling re-creation issues, resource order, and considerations for real-world applications.
GitHub repository link for the project is provided for readers to try out the deployment process.

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Siliconangle

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Ali Ghodsi’s data intelligence playbook: Turning data into agentic advantage

Databricks aims to shift from an analytic to an intelligent application platform with the System of Intelligence and System of Agency.
They focus on data intelligence, aiming to transition from managing data to defining end-to-end business operations.
Databricks introduced Genie AI, Databricks One, and Lakebase to enhance data intelligence and user experiences.
They are evolving towards a 4D enterprise map for agents to understand business operations and make autonomous decisions.
References to Snowflake competition, Unity Catalog for semantic control, and Lakeflow for no-code pipeline generation are noted.
Databricks positions itself to operationalize decisions and lead in enterprise AI with Agent Bricks for AI-driven pipelines.
They aim to converge engagement and agency in applications, focusing on interoperability and vendor resistance challenges.
The future goal is to achieve 'enterprise AGI' by translating intelligence into actionable decisions within enterprise boundaries.
Key milestones to watch include Unity Catalog depth, Agent Bricks capabilities, ecosystem commitment, and regulatory certifications.
The competition is shifting towards semantic control for enterprise AI, with Databricks, Snowflake, SAP, Salesforce, and others vying for dominance.

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Dev

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Why your ECS tasks aren’t scaling

Many teams face scaling issues despite having auto scaling, alarms, and metrics set up for their ECS tasks.
The problem often lies in the mismatch between task scaling and available cluster capacity.
Tasks can remain stuck in PENDING if there is not enough CPU or memory available on the cluster.
ECS Cluster Auto Scaling (CAS) becomes crucial to address this capacity constraint.
Understanding API behavior and estimating task size are essential for proper ECS scaling.
Monitoring key metrics like CPUReservation and MemoryReservation is vital for effective scaling policies.
ECS CAS utilizes a formula to calculate the needed EC2 capacity based on task resource demand.
Daemon and Non-Daemon tasks play a significant role in determining EC2 scaling in ECS.
ECS checks task placement every 15 seconds and can have up to 100 tasks in provisioning per cluster.
By implementing CAS, linking services to capacity providers, and enabling managed scaling, tasks can scale efficiently without 502 errors.
Estimating concurrency, understanding app behavior, and wisely choosing EC2 instances are key factors for early capacity planning.

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Tech Radar

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NYT Strands hints and answers for Monday, June 16 (game #470)

The theme of NYT Strands for game #470 is Key notes.
Clue words for the game include REPEAT, NEEDS, LICE, SAUCE, PLATE, CLUE.
Today's spangram has 11 letters.
The spangram for game #470 touches the top of the 3rd column as the first side and the bottom of the 3rd column as the last side.
The answers for game #470 are ETUDE, SUITE, MINUET, NOCTURNE, SONATA, PRELUDE, with the spangram being PIANO PIECES.
The difficulty level for game #470 is rated as Moderate.
One hint was used by the player in game #470 to start.
ETUDE is a musical piece used for practice, while MINUET is a slow, stately dance in triple time, as found in the answers.
Yesterday's game #469 answers included words like CHALUPA, CRAWDAD, POPCORN, and POPSICLE, with the spangram being FATHERS DAY.
Strands is a word game by the NYT, now established alongside Wordle and Connections, playable on the NYT Games site.
Players can access guides with tips on how to play NYT Strands effectively for daily challenges.

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Dev

128

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A Complete Guide to EKS Upgrades: Zero Downtime, Full Automation, and Enterprise-Scale Strategies

Amazon EKS upgrades are complex engineering efforts touching infrastructure, application reliability, and organization readiness.
The guide divides the upgrade lifecycle into Pre-Upgrade Planning, High Availability Execution, and Post-Upgrade Validation phases.
Pre-Upgrade involves backups, compatibility audits, staging, and change management.
High Availability & Zero Downtime Upgrade focuses on control plane and node group upgrades with best practices for Node Drain and add-ons.
Security hardening and observability are crucial during upgrades using tools like Prometheus, Grafana, and CloudWatch.
Post-Upgrade includes validation, rollback strategies via Helm or GitOps, cleanup, and automation suggestions.
Key takeaways highlight treating upgrades as lifecycle workflows, continuous observation, and smart engineering practices.
The article emphasizes automation and best practices, featuring bonus resources and a conclusion on EKS upgrade mastery.

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Guardian

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UK government rollout of Humphrey AI tool raises fears about reliance on big tech

The UK government's AI tool called Humphrey is based on models from OpenAI, Anthropic, and Google.
The government is rolling out AI across the public sector in England and Wales to enhance efficiency.
Critics raise concerns about the government's reliance on big tech for AI and the potential conflict with copyright concerns.
There is a public debate over the use of AI trained on copyrighted material.
Creative sector backlash against AI use without proper credit or compensation.
The government uses a pay-as-you-go model for AI tools through existing cloud contracts.
Humphrey's tools, including Consult, Lex, Parlex, and Redbox, utilize base models from OpenAI, Anthropic, and Google.
Criticism from Fairly Trained CEO on AI being trained on copyrighted material.
Shami Chakrabarti urges caution regarding biases and inaccuracies in AI implementation.
Whitehall sources emphasize the need for transparency and evaluation of AI tools' accuracy.
Costs of using AI in government are expected to increase as Humphrey is further implemented.
Government's AI playbook provides guidance for officials on using AI effectively.
Government states AI can make public services more efficient by handling basic admin tasks.
The Department for Science, Innovation, and Technology highlights the potential of AI to enhance public services.
ChatGPT responded that information about base models for Humphrey AI toolkit was not available when asked.
The government aims to alter its strategy for technology contracts to support smaller tech startups.

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Dev

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🚀 Getting Started with AWS CodeBuild: A Beginner-Friendly Guide

AWS CodeBuild is a fully managed build service in the cloud and part of the AWS Developer Tools suite.
Benefits of using CodeBuild include serverless operation, scalability, cost-effectiveness, and CI/CD pipeline integration.
CodeBuild uses Docker containers for running build environments and supports Ubuntu, Amazon Linux 2, and Windows Server Core.
A buildspec is a YAML file that instructs CodeBuild on how to run the build, defining phases like install, pre_build, build, and post_build.
Managing build projects with CodeBuild includes adding projects to CI/CD pipelines, creating standalone projects, and scheduling builds using AWS EventBridge or CloudWatch.
CodeBuild maintains security by encrypting data in transit with SSL, data at rest in Amazon S3 with Customer Managed Keys via AWS KMS, and controlling access using AWS IAM.
CodeBuild is a valuable build tool when used with other AWS Developer Tools like CodePipeline, suitable for both beginners and developers scaling their build processes.

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Dev

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💬 Building BankerBot: A Conversational Banking Assistant Using Amazon Lex, Lambda & CloudFormation

BankerBot is a cloud-native chatbot created to provide seamless banking services through natural conversation.
It was developed using Amazon Lex for voice/text interaction, AWS Lambda for backend logic, and CloudFormation for automated deployment.
BankerBot assists users in checking account balances, transferring funds, and handling general inquiries.
The project involved implementing Welcome & Fallback Intents, CheckBalance Intent, Lambda integration, Context Carryover, and Fund Transfer Flow.
Challenges included permissions issues between Amazon Lex and Lambda, which were resolved through proper policy statements.
BankerBot showcases the synergy of AI and cloud services, enabling rapid development of scalable applications.
AI-driven chatbot development offers enhanced customer experience and efficiency in various industries.

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Dev

344

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Automate EC2 Start/Stop with AWS Lambda and CloudWatch — Step-by-Step Guide with Alerts

Automating EC2 instance start/stop with AWS Lambda, CloudWatch, and SNS to prevent unnecessary billing due to idle instances.
AWS Lambda allows serverless code execution, triggered by events/alerts, without server management.
Amazon EC2 provides resizable cloud computing capacity for running applications and websites.
Amazon SNS is a managed messaging service for sending notifications via email, SMS, or push notifications.
Prerequisites include an AWS Account and Gmail Account for notifications.
Step 1 involves creating an IAM role and policy for EC2 and SNS permissions.
Step 2 entails creating Lambda functions 'Stopec2' and 'Startec2' for stopping and starting instances.
Step 3 involves creating SNS topics for start and stop instance notifications.
Step 4 includes creating rules using EventBridge Scheduler for starting and stopping EC2 instances.
By scheduling actions and utilizing SNS notifications, the project aims to optimize costs and efficiency in cloud operations.

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