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How to cancel Amazon Music Unlimited

To cancel Amazon Music Unlimited, you can follow these steps:
On the website: Navigate to Amazon.com, open your account, select memberships & subscriptions, find your Amazon Music Unlimited subscription, and click on the cancel membership button.
On Android: Open the Amazon Music app, go to settings, select Amazon Music Unlimited Member, and cancel your subscription.
On iPhone and iPad: Open the Settings app, select subscriptions, find the Amazon Music subscription, and cancel it.
Via iTunes: Visit Apple's support site, log in to your account, go to billing and subscriptions, find Amazon Music Unlimited, and follow the on-screen prompts to cancel.

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Dev

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[Mini Project] Serverless URL Shortener Using AWS Lambda, Api Gateway and DynamoDB

In this tutorial, we will walk through building a Serverless URL Shortener using AWS services like Lambda, API Gateway, and DynamoDB.
The project is designed to be beginner-friendly and will guide you step-by-step.
Before we start, ensure that you have the following prerequisites: AWS Account, AWS CLI, Python 3.x, and Postman.
The first step is to create a DynamoDB table where the shortened URLs and their corresponding long URLs will be stored.
Next, we need to create an AWS Lambda function that will generate short codes and handle the URL redirection.
Lambda is a serverless compute service that lets you run code without provisioning or managing servers.
After creating the Lambda function, we need to add the Python code that will perform the main logic of the URL shortener including generating a short code for a given long URL and redirecting users when they visit the short code.
Once you have set up the Lambda function and API Gateway, it’s time to test the URL shortener functionality using Postman or Command Prompt or PowerShell.
To clean up AWS resources, delete DynamoDB Table, Lambda Function, and API Gateway.
In conclusion, we’ve built a simple yet scalable serverless URL shortener using AWS Lambda, API Gateway, and DynamoDB.

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Guardian

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Was this the week DeepSeek started the slow unwinding of the AI bet?

Chinese chatbot DeepSeek, developed by the millennial mathematician Liang Wenfeng, has been hailed as AI’s Sputnik moment as it appears to rival top US-based models at a fraction of the cost. DeepSeek's achievement shook the market, causing shares in major global companies such as chip maker Nvidia to plummet. China's AI lab claimed that the cost for training one of its models had only been $5.6 million. In the biggest week for AI since the launch of ChatGPT in November 2022, DeepSeek's app became the most downloaded on Apple's app stores in the US and UK.
DeepSeek's announcement prompted fears about control of AI, particularly given the technology's capacity for being weaponized. Furthermore, it is now one of the principal battlegrounds in global geopolitics, posing a question about whether DeepSeek’s success presents a greater threat to US hopes of maintaining supremacy in AI. While some suggest that DeepSeek's accessible technology could open AI up to more startups, DeepSeek's main users are China's leading technology companies.
DeepSeek said its model is comparable to OpenAI's 01 model and is even better in some areas, with a more efficient design intended to activate only the relevant part of the system to answer the query. DeepSeek inspired OpenAI to announce the launch of o3-Mini reasoning model on Friday. The model was free to use, and its design could potentially redefine the benchmarks of AI performance and offer more equality among AI researchers.
Experts generally agreed that Big Tech companies like Google and Facebook, with much larger computational processing power, could still rapidly experiment and use emerging techniques, such as those used in DeepSeek’s technology. In the UK, minister of state for digital and culture expressed excitement about DeepSeek’s breakthrough. But, as a minister tasked with using AI to deliver economic growth, he also acknowledged the security risks implicit in downloading the Chinese app.
However, as more information about the chatbot came to light, it was clear that the government had the ability to censor its responses for politically sensitive issues. The Irish Data Protection Commission demanded explanations from DeepSeek about its information processing. It was discovered that DeepSeek would censor itself in real time when its answers might be politically sensitive or challenging for the government.
David Sacks, a White House AI adviser, claimed there was substantial evidence that DeepSeek had distilled knowledge from OpenAI models, and that OpenAI was unhappy about the move. OpenAI's founder, Sam Altman, initially welcomed DeepSeek as a new competitor. Yet, the next day, OpenAI claimed it was “reviewing indications that DeepSeek may have inappropriately distilled our models”.
DeepSeek’s success led to numerous discussions about the ramifications of AI innovation and the security risks involved. Governments and companies need to prioritize AI security to check the threat of weaponized AI. Further discussions also ensued regarding the control of AI and the fair sharing of technology, particularly as AI becomes more accessible to small companies.
DeepSeek's success will only perpetuate the competition for AI supremacy. As AI remains a prime concern for global security, it is important for governments to safeguard against potential misuse of AI technology.
Although DeepSeek has ruffled feathers, it is important to remember that AI is an evolving technology that is still open to many possibilities. DeepSeek’s success does not necessarily equate to the downfall of US or European AI progress, and could in hindsight act as a wake-up call for further research and development into AI technology.
Overall, DeepSeek has opened up discussions for improved AI sharing and security. Governments should prioritise security risks to put a check on weaponised AI. As AI becomes more accessible, it is vital for governments and companies to share technology and ensure a more level playing field for all AI researchers, regardless of geography.

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Tech Radar

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OpenAI responds to the DeepSeek buzz by launching its latest o3-mini reasoning model for all users

OpenAI has launched its latest o3-mini reasoning model for all users, including the free tier.
The o3-mini model offers improved reasoning capabilities and responds faster than its predecessor.
It aims to compete with DeepSeek, a Chinese AI model that has gained popularity.
OpenAI emphasizes the safety assessments conducted on the o3-mini model.

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Dev

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Installing Nvidia Datacenter GPU Manager on Amazon Linux 2023

Nvidia Datacenter GPU Manager is a suite of tools used for managing and monitoring Nvidia GPUs in the data center.
The Amazon Linux 2 (AL2) EOL date is 6/30/2025 (June 30, 2025). The replacement is Amazon Linux 2023 (AL2023).
Installing Nvidia Datacenter GPU Manager on Amazon Linux 2023 requires using the parameter as 'rhel9' in the repository installation command.
After installing the repository, the datacenter-gpu-manager package can be installed with the command 'sudo dnf install -y datacenter-gpu-manager'.

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TechCrunch

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DeepSeek: Separating fact from hype

DeepSeek is gaining attention in the AI world, but what's really happening behind the hype?
TechCrunch's Equity podcast discusses DeepSeek with Ion Stoica, Professor of Computer Science Division at UC Berkeley and cofounder of Databricks.
Topics covered include the future of AI, DeepSeek on Azure, fostering innovation, and the controversy surrounding its use of OpenAI's models.
Equity podcast returns next week with more discussions on technology and startups.

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Dev

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Secure Multi-Tier Web Application in a Custom VPC

Create a custom VPC with public and private subnets.
Deploy a web application with secure application and database layers.
Utilize security groups and NACLs for traffic control between the tiers.
Enable logging for network traffic monitoring and troubleshooting.

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Digitaltrends

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Apple is no longer working on smart glasses to rival Meta

Apple has reportedly cancelled its project to develop AR glasses to rival Meta.
The cancellation came after attempts to change and improve the design of the glasses.
Apple has previously cancelled other projects like self-driving cars and in-house LED displays.
However, some executives at Apple still hope to create standalone AR glasses in the future.

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Digitaltrends

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This HP Envy laptop with Copilot and a 17-inch screen is $450 off

The HP Envy 17t laptop is currently on sale with a 39% discount from HP.
The laptop features Intel Core Ultra 5 125H processor, Intel Arc Graphics, and 16GB of RAM.
It comes with a 17.3-inch Full HD screen and ample storage space of 512GB SSD.
The offer may expire soon, so interested buyers should purchase it quickly.

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Digitaltrends

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Nvidia’s RTX 5080 doesn’t dethrone the RTX 4090

The NVIDIA RTX 5080 GPU does not beat or outperform NVIDIA's RTX 4090 GPU.
The NVIDIA RTX 5080 GPU is on sale for $1,000 with extremely limited stock while third-party cards are already up to $1,500.
On paper, the RTX 5080 is a weaker card than the RTX 4090 with around 50% fewer CUDA cores.
Real-world performance tests showed the RTX 5080 to be average across gaming suites at 4K and 1440p.
The RTX 5090 still holds sway even in slightly older games in 1440p.
The frame generation feature is the only real standout for the RTX 5080, and arguably its only selling point for any RTX 4080 or 4080 Super owners considering an upgrade.
The RTX 5080 is more efficient than the last-gen king, demanding just 360W, whereas the RTX 4090 could easily pull 450W when pushed hard.
The RTX 4080 Super, but not the 4090 or 5090, can be upgraded to the RTX 5080 and notice performance improvements.
Gamers with around $1,000 burning a hole in their pocket looking for a GPU upgrade should consider the RTX 5080.
Scalper prices for the RTX 5080 are not worth paying.

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Dev

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Incident Response Essentials: Building a Resilient AWS Environment with Wazuh

Cloud misconfigurations account for nearly 65-70% of all cloud security incidents.
Organizations need to understand the basics and implement them properly to prepare for an incident response strategy.
Incident response is a structured framework for managing and addressing security breaches, cyberattacks, and other security incidents within an organization.
AWS Security Incident Response is a new service for quick and efficient security event management.
The incident response framework consists of four essential phases that work together to create a comprehensive security management system - preparation, detection and analysis, containment and eradication, and post-incident recovery.
Wazuh, an open-source SIEM solution, helps in spotting, investigating, and addressing potential security threats by collecting and analyzing logs and alerts in one place.
Continuous monitoring by setting up Wazuh's agent with several AWS security tools improves your AWS environment's security posture and enables automated patching and scanning.
Dependency management, continuous monitoring, and security breadth coverage are essential for maintaining a secure environment.
Amazon GuardDuty and AWS Config can complement your environment by leveraging both open-source tools and AWS's built-in capabilities.
Pairing Wazuh's continuous monitoring with AWS Backup for automated backups and cross-region replication ensures quick and efficient recovery in case of major incident incidence.

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Digitaltrends

1.4k

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Microsoft is letting anyone use ChatGPT’s $200 reasoning model for free

Microsoft is allowing free access to OpenAI's o1 model through the Think Deeper feature in Microsoft Copilot.
This feature is available to Microsoft 365 users and can be accessed through the Copilot web-based chat or the downloadable app.
By enabling Think Deeper, users can receive more detailed and in-depth responses to their queries.
Previously, the o1 model was only accessible through OpenAI's paid tiers, but now it is free for Microsoft users.

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Medium

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Common Myths About Data Analytics and the Truth Behind Them

Data analytics is accessible to businesses of all sizes.
Modern tools make data analytics user-friendly for non-technical professionals.
Cost-effective solutions are available for implementing data analytics.
Data analytics is a process that requires time and diligence.

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Jamiemaguire

368

How To: Resolve Poor Performance on Raspberry Pi 4 When Running Visual Studio Code

To resolve poor performance on Raspberry Pi 4 when running Visual Studio Code, you need to disable hardware acceleration.
Press F1 in VS Code and type 'runtime' to access runtime preferences.
Select 'Preferences, Configure Runtime Arguments' and set it to the recommended value.
After disabling hardware acceleration, Visual Studio Code becomes usable on the Pi.

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Dev

186

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Deploying Amazon API Gateway and Lambda with Terraform

AWS provides multiple ways to deploy infrastructure and code onto their platform, with differing levels of complexity and scalability.
In this example, we'll be deploying an Amazon API Gateway with links to a Lambda Function.
I've come to like Terraform for its more programming like features over CloudFormation, though I do still use CloudFormation in some cases.
The API Gateway has integrations with the Lambda via a proxy.
In this example, we are sending requests to the Production Stage (you could also host dev or test on the same endpoint for example), accessing the items resource (our main endpoint for dealing with our expected database), then we have multiple functions for interactions with those resources, for each request type.
For this example, i'll keep everything in one place to make it easier to understand, but typically you would have separate variables, outputs and maybe a backend file.
We then create a stage with aws_api_gateway_stage to create our production stage, passing in the rest api and the deployment we just created.
If this is the first time running, you should see a lot of creation messages.
This example can be used to expand other types of resources or Lambda functions deployed via Terraform, and in the next Blog Entry we will use this Terraform and deploy it via a Code Pipeline with a CodeBuild instance, allowing us to automate the execution of the Terraform when triggered by a commit to a GitHub repository.
After which you should see creation messages.

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