Rapper-turned-mogul 50 Cent has become one of the largest private property owners in Shreveport, Louisiana, and is investing in a $50 million entertainment district in an effort to boost the city's economy.

يحدث مغني الراب 50 سنت ضجة في شريفبورت، لويزيانا، من خلال استثماره 50 مليون دولار لإنشاء منطقة ترفيهية جديدة. لا تضع هذه المبادرة فقط 50 سنت كواحد من أكبر مالكي العقارات الخاصة في المنطقة، بل تهدف أيضًا إلى revitalizing الاقتصاد المحلي في واحدة من أكثر المدن احتياجًا في أمريكا. يمكن أن يؤدي استثماره إلى خلق وظائف وفرص جديدة، مما سيكون له تأثير كبير على المجتمع.

El rapero 50 Cent está causando revuelo en Shreveport, Luisiana, al invertir 50 millones de dólares para crear un nuevo distrito de entretenimiento. Esta iniciativa no solo lo posiciona como uno de los mayores propietarios privados de la zona, sino que también busca revitalizar la economía local en una de las ciudades más necesitadas de Estados Unidos. Su inversión podría generar empleos y nuevas oportunidades, teniendo un impacto significativo en la comunidad.

Le rappeur 50 Cent fait sensation à Shreveport, en Louisiane, en investissant 50 millions de dollars pour créer un nouveau district de divertissement. Cette initiative le positionne non seulement comme l'un des plus grands propriétaires privés de la région, mais vise également à revitaliser l'économie locale dans l'une des villes les plus nécessiteuses d'Amérique. Son investissement pourrait créer des emplois et de nouvelles opportunités, ayant un impact significatif sur la communauté.

Rapper 50 Cent is making waves in Shreveport, Louisiana, by investing $50 million to create a new entertainment district. This initiative not only positions him as one of the largest private property owners in the area but also aims to revitalize the local economy in one of America's most needy cities. His investment could bring jobs and new opportunities, making a significant impact on the community.

50 Cent Invests Millions in Shreveport, One of America's Most Needy Cities, to Build New Entertainment Empire

Cursor 2.0 shifts to in-house AI with Composer model and parallel agents, OpenAI completed its for-profit restructuring, and more!

في الحلقة الأخيرة من بودكاست LWiAI، يناقش المضيفون التطورات المهمة في صناعة الذكاء الاصطناعي، بما في ذلك انتقال OpenAI إلى نموذج ربحي وإطلاق Cursor 2.0، الذي يتميز بذكاء اصطناعي داخلي مع نموذج Composer ووكلاء متوازيين. تعكس هذه التغييرات المشهد المتطور للذكاء الاصطناعي وتبرز زيادة تجارية تقنيات الذكاء الاصطناعي، مما يجعلها موضوعًا حاسمًا لأي شخص مهتم بمستقبل هذا المجال.

En el último episodio del podcast LWiAI, los anfitriones discuten desarrollos significativos en la industria de la IA, incluida la transición de OpenAI a un modelo con fines de lucro y el lanzamiento de Cursor 2.0, que presenta una IA interna con un modelo Composer y agentes paralelos. Estos cambios reflejan el paisaje en evolución de la inteligencia artificial y destacan la creciente comercialización de las tecnologías de IA, convirtiéndolo en un tema crucial para cualquier persona interesada en el futuro de este campo.

Dans le dernier épisode du podcast LWiAI, les animateurs discutent des développements importants dans l'industrie de l'IA, y compris la transition d'OpenAI vers un modèle à but lucratif et le lancement de Cursor 2.0, qui propose une IA interne avec un modèle Composer et des agents parallèles. Ces changements reflètent l'évolution du paysage de l'intelligence artificielle et soulignent la commercialisation croissante des technologies IA, ce qui en fait un sujet crucial pour quiconque s'intéresse à l'avenir de ce domaine.

In the latest episode of the LWiAI Podcast, the hosts discuss significant developments in the AI industry, including OpenAI's transition to a for-profit model and the launch of Cursor 2.0, which features an in-house AI with a Composer model and parallel agents. These changes reflect the evolving landscape of artificial intelligence and highlight the increasing commercialization of AI technologies, making it a crucial topic for anyone interested in the future of this field.

LWiAI Podcast #224 - OpenAI is for-profit! Cursor 2, Minimax M2, Udio copyright

Picture this: You're staring at a 3000-line Terraform file at 2 AM, wondering why your simple VPC deployment is taking 45 minutes and why changing one variable broke half your infrastructure. Sound familiar? 🤔

Welcome to the wonderful world of Infrastructure as Code gone wrong! But fear not, dear reader. After 20 years of watching developers turn elegant infrastructure into digital spaghetti, I'm here to share the secret sauce that separates the Terraform wizards from the mere mortals.

Today, we're diving deep into the art of writing efficient, maintainable Terraform code that won't make your future self (or your teammates) want to throw their laptop out the window. Let's transform your infrastructure from a house of cards into a solid foundation that scales! 🏗️

<h2>
 
 
 1. Modularity: Or How Not to End Up with a Terraform Monolith 🧱
</h2>

Remember that colleague who created a single <code>main.tf</code> file with 5,847 lines and proudly called it "well-organized"? Don't be that person! 😅

Modularity is like cooking - you don't throw all ingredients into one giant pot and hope for the best. You create distinct, reusable components that work together harmoniously.

<h3>
 
 
 The Magical Structure
</h3>

Here's a lesser-known fact: Terraform modules can be versioned and published to private registries, just like your favorite npm packages! This means you can treat your infrastructure components like proper software libraries. 


<div class="highlight js-code-highlight">
<pre class="highlight hcl"><code># modules/vpc/main.tf
resource "aws_vpc" "main" {
 cidr_block = var.cidr_block
 enable_dns_hostnames = var.enable_dns_hostnames
 enable_dns_support = var.enable_dns_support

 tags = merge(
 var.common_tags,
 {
 Name = var.vpc_name
 }
 )
}

# modules/vpc/variables.tf
variable "cidr_block" {
 description = "CIDR block for the VPC"
 type = string
 validation {
 condition = can(cidrhost(var.cidr_block, 0))
 error_message = "The cidr_block must be a valid CIDR block."
 }
}
</code></pre>

</div>



<h3>
 
 
 The Organization That Saves Lives
</h3>

A well-structured project looks like this: 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>terraform/
├── modules/
│ ├── vpc/
│ ├── compute/
│ └── database/
├── environments/
│ ├── dev/
│ ├── staging/
│ └── prod/
└── shared/
 ├── data.tf
 └── providers.tf
</code></pre>

</div>



Pro tip: According to HashiCorp's own statistics, teams using proper module organization reduce their deployment errors by 67% and cut development time by 40%! 📊

<h2>
 
 
 2. The Art of Reusability: DRY Applied to Infrastructure ♻️
</h2>

Ah, the classic tale of the developer who copy-pasted the same resource block 47 times with slight variations. Each time they needed a new environment, ctrl+c, ctrl+v, change a few values, and voilà! Until one day they needed to update all 47 instances... 😱

<h3>
 
 
 Variables and Locals: Your New Best Friends
</h3>

Here's a mind-blowing fact: You can use Terraform's <code>locals</code> block to create computed values that adapt based on your environment, making your code incredibly flexible: 


<div class="highlight js-code-highlight">
<pre class="highlight hcl"><code>locals {
 environment_config = {
 dev = {
 instance_type = "t3.micro"
 min_size = 1
 max_size = 2
 }
 prod = {
 instance_type = "t3.large" 
 min_size = 3
 max_size = 10
 }
 }

 current_config = local.environment_config[var.environment]

 # This awesome technique automatically calculates subnets!
 availability_zones = data.aws_availability_zones.available.names
 subnet_cidrs = [
 for index, az in local.availability_zones :
 cidrsubnet(var.vpc_cidr, 8, index)
 ]
}
</code></pre>

</div>



<h3>
 
 
 The Power of Data Sources
</h3>

Data sources are like having a conversation with your existing infrastructure: 


<div class="highlight js-code-highlight">
<pre class="highlight hcl"><code>data "aws_ami" "latest_amazon_linux" {
 most_recent = true
 owners = ["amazon"]

 filter {
 name = "name"
 values = ["amzn2-ami-hvm-*-x86_64-gp2"]
 }
}

# Now your AMI is always automatically up to date!
resource "aws_instance" "web" {
 ami = data.aws_ami.latest_amazon_linux.id
 instance_type = local.current_config.instance_type
}
</code></pre>

</div>



Surprising stat: Teams using data sources properly have 23% fewer "it works on my machine" incidents! 🎯

<h2>
 
 
 3. Maintainability: Make Sure Your Future Self Doesn't Curse You 🔮
</h2>

Picture this horror story: A developer creates perfect infrastructure, documents nothing, uses default state files, and then leaves the company. Six months later, nobody dares touch the infrastructure because it's like defusing a bomb blindfolded! 💣

<h3>
 
 
 State Management: The Foundation of Everything
</h3>

Here's a secret weapon most developers don't know: Terraform has a <code>moved</code> block that lets you refactor your resources without destroying them! 


<div class="highlight js-code-highlight">
<pre class="highlight hcl"><code># Backend configuration - TOUJOURS distant !
terraform {
 backend "s3" {
 bucket = "my-terraform-state-bucket"
 key = "prod/terraform.tfstate"
 region = "eu-west-1"
 encrypt = true
 dynamodb_table = "terraform-state-locks"
 }
}

# The moved block - your savior for refactors!
moved {
 from = aws_instance.web
 to = module.compute.aws_instance.web
}
</code></pre>

</div>



<h3>
 
 
 Documentation: Your Life Insurance
</h3>

Smart documentation isn't just comments - it's self-documenting code: 


<div class="highlight js-code-highlight">
<pre class="highlight hcl"><code>variable "database_config" {
 description = &lt;&lt;-EOT
 Configuration for the RDS database instance.

 Example:
 database_config = {
 engine = "postgres"
 engine_version = "13.7"
 instance_class = "db.t3.micro"
 allocated_storage = 20
 }
 EOT

 type = object({
 engine = string
 engine_version = string
 instance_class = string
 allocated_storage = number
 })

 validation {
 condition = contains(["postgres", "mysql"], var.database_config.engine)
 error_message = "Database engine must be either 'postgres' or 'mysql'."
 }
}
</code></pre>

</div>



<h3>
 
 
 Secret Testing
</h3>

Hidden gem: You can use <code>terraform plan -detailed-exitcode</code> in your CI/CD to detect if there are changes to apply. Exit code 2 means changes detected! 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>#!/bin/bash
terraform plan -detailed-exitcode -out=tfplan
case $? in
 0) echo "No changes needed" ;;
 1) echo "Error in plan" ; exit 1 ;;
 2) echo "Changes detected, applying..." ; terraform apply tfplan ;;
esac
</code></pre>

</div>



Industry secret: Companies using automated Terraform testing report 89% fewer production incidents related to infrastructure changes! 🛡️

<h2>
 
 
 Conclusion
</h2>

And voilà! You now have the trinity of Terraform mastery: Modularity, Reusability, and Maintainability. These aren't just fancy French words - they're your survival kit in the Infrastructure as Code jungle! 🌟

Remember, good Terraform code is like a fine wine - it gets better with time, doesn't leave you with a headache, and makes you look sophisticated at dinner parties! 🍷

The secret sauce isn't just in knowing these practices, but in applying them consistently. Start small, refactor ruthlessly, and always think about the poor soul (probably future you) who will maintain this code at 3 AM on a Sunday.

Your mission, should you choose to accept it: Pick one existing Terraform project this week and apply just one of these principles. Watch the magic happen! ✨

What's the worst Terraform horror story you've encountered? Share it in the comments - we could all use a good laugh (and learn from each other's pain)! 😄




<a href="https://buymeacoffee.com/tavernetech" rel="noopener noreferrer"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fjf9tsaj3ugonagdk5vsc.png" alt="buy me a coffee" width="545" height="153"></a>

في عالم البنية التحتية ككود، يمكن أن يكون إدارة ملفات Terraform المعقدة أمرًا شاقًا، خاصة عندما تؤدي التغييرات البسيطة إلى مشاكل غير متوقعة. يشارك هذا المقال رؤى من محترفين ذوي خبرة قاموا بالتنقل عبر هذه التحديات لسنوات. من خلال الكشف عن 'الوصفة السرية' الخاصة بهم، يهدفون إلى تمكين المطورين من تبسيط عملياتهم وتجنب الفخاخ الشائعة، مما يجعل عالم إدارة البنية التحتية أكثر كفاءة وأقل إحباطًا.

En el ámbito de la infraestructura como código, gestionar archivos de Terraform complejos puede ser desalentador, especialmente cuando cambios simples conducen a problemas inesperados. Este artículo comparte ideas de profesionales experimentados que han navegado por estos desafíos durante años. Al revelar su 'receta secreta', buscan empoderar a los desarrolladores para que optimicen sus procesos y eviten trampas comunes, haciendo que el mundo de la gestión de infraestructuras sea más eficiente y menos frustrante.

Dans le domaine de l'infrastructure en tant que code, gérer des fichiers Terraform complexes peut être décourageant, surtout lorsque des changements simples entraînent des problèmes inattendus. Cet article partage des idées de professionnels chevronnés qui ont navigué à travers ces défis pendant des années. En révélant leur 'recette secrète', ils visent à donner aux développeurs les moyens de rationaliser leurs processus et d'éviter les pièges courants, rendant ainsi le monde de la gestion des infrastructures plus efficace et moins frustrant.

In the realm of Infrastructure as Code, managing complex Terraform files can be daunting, especially when simple changes lead to unexpected issues. This article shares insights from seasoned professionals who have navigated these challenges for years. By revealing their 'secret sauce,' they aim to empower developers to streamline their processes and avoid common pitfalls, making the world of infrastructure management more efficient and less frustrating.

Effective Terraforming: Secrets of the Pros

<A HREF="https://www.cnbc.com/2025/11/05/figma-fig-q3-earnings-report-2025.html"><IMG VSPACE="4" HSPACE="4" BORDER="0" ALIGN="RIGHT" SRC="http://www.techmeme.com/251105/i54.jpg"></A>
<A HREF="http://www.techmeme.com/251105/p54#a251105p54" TITLE="Techmeme permalink"><IMG WIDTH=11 HEIGHT=12 SRC="http://www.techmeme.com/img/pml.png" STYLE="border:none;padding:0;margin:0;"></A> Jordan Novet / <A HREF="http://www.cnbc.com/">CNBC</A>: 
<A HREF="https://www.cnbc.com/2025/11/05/figma-fig-q3-earnings-report-2025.html">Figma reports Q3 revenue up 38% YoY to $274.2M, vs. $265.2M est., adjusted operating margin of 12%, vs. 6.5% est., and forecasts Q4 revenue above estimates</A>&nbsp; &mdash;&nbsp; Design software maker Figma on Wednesday reported stronger-than-expected third-quarter revenue and quarterly revenue guidance.

أبلغت شركة فيغما عن زيادة ملحوظة بنسبة 38% في الإيرادات على أساس سنوي للربع الثالث، حيث وصلت إلى 274.2 مليون دولار، متجاوزة التقديرات البالغة 265.2 مليون دولار. كما تحسنت الهامش التشغيلي المعدل للشركة بشكل كبير ليصل إلى 12%، مقارنة بـ 6.5% المتوقعة. لا تبرز هذه الأداء القوي مسار نمو فيغما فحسب، بل تحدد أيضًا نغمة إيجابية للربع القادم، حيث تتوقع الشركة أن تتجاوز إيرادات الربع الرابع التوقعات. تعتبر هذه النتائج حاسمة لأنها تعكس زيادة وجود فيغما في السوق والطلب المتزايد على أدوات التصميم الخاصة بها.

Figma ha reportado un notable aumento del 38% en los ingresos interanuales para el tercer trimestre, alcanzando los 274,2 millones de dólares, superando las estimaciones de 265,2 millones de dólares. El margen operativo ajustado de la compañía también mejoró significativamente al 12%, en comparación con el 6,5% esperado. Este sólido desempeño no solo destaca la trayectoria de crecimiento de Figma, sino que también establece un tono positivo para el próximo trimestre, ya que la empresa pronostica que los ingresos del cuarto trimestre superarán las expectativas. Tales resultados son cruciales, ya que reflejan la creciente presencia de Figma en el mercado y la creciente demanda de sus herramientas de diseño.

Figma a annoncé une augmentation remarquable de 38 % de son chiffre d'affaires d'une année sur l'autre pour le troisième trimestre, atteignant 274,2 millions de dollars, dépassant les estimations de 265,2 millions de dollars. La marge opérationnelle ajustée de l'entreprise s'est également considérablement améliorée, atteignant 12 %, contre 6,5 % attendus. Cette performance solide souligne non seulement la trajectoire de croissance de Figma, mais donne également un ton positif pour le trimestre à venir, l'entreprise prévoyant un chiffre d'affaires du quatrième trimestre supérieur aux attentes. De tels résultats sont cruciaux car ils reflètent la présence croissante de Figma sur le marché et la demande croissante pour ses outils de conception.

Figma has reported a remarkable 38% year-over-year increase in revenue for Q3, reaching $274.2 million, surpassing estimates of $265.2 million. The company's adjusted operating margin also improved significantly to 12%, compared to the expected 6.5%. This strong performance not only highlights Figma's growth trajectory but also sets a positive tone for the upcoming quarter, as the company forecasts Q4 revenue to exceed expectations. Such results are crucial as they reflect Figma's increasing market presence and the growing demand for its design tools.

Figma reports Q3 revenue up 38% YoY to $274.2M, vs. $265.2M est., adjusted operating margin of 12%, vs. 6.5% est., and forecasts Q4 revenue above estimates (Jordan Novet/CNBC)

<h1>
 
 
 Laravel Log Cleaner v2.0 - Memory-Efficient Log Management
</h1>

<h2>
 
 
 The Problem 🔥
</h2>

We've all been there: your Laravel app runs fine for weeks, then suddenly your server runs out of disk space. You SSH in, check the logs folder, and find a 5GB <code>laravel.log</code> file.

Sound familiar?

Log files can grow out of control fast, especially in production. But clearing them manually is risky, and heavy monitoring tools like Telescope can slow down your app or even crash your server.

<h2>
 
 
 The Solution ✨
</h2>

I built <a href="https://github.com/jiordiviera/laravel-log-cleaner" rel="noopener noreferrer">Laravel Log Cleaner</a> to solve this exact problem. Version 2.0 just launched with major improvements:

<ul>
<li>🧠 Memory-efficient processing - handles multi-GB files without crashing</li>
<li>📦 Compression support - archive old logs instead of deleting</li>
<li>🔒 Backup creation - never lose important data</li>
<li>🎯 Log level filtering - keep only ERROR logs, discard the rest</li>
<li>👀 Dry-run mode - preview changes before applying</li>
<li>⚡ 50%+ performance improvement on large files</li>
</ul>

<h2>
 
 
 Installation
</h2>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>composer require jiordiviera/laravel-log-cleaner
</code></pre>

</div>



That's it! No config files, no service providers to register. Laravel's auto-discovery handles everything.

<h2>
 
 
 Basic Usage
</h2>

Clear all logs: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear
</code></pre>

</div>



Keep the last 30 days: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30
</code></pre>

</div>



<h2>
 
 
 Advanced Features (What's New in v2.0)
</h2>

<h3>
 
 
 1. Safe Operations 🔒
</h3>

Preview what will be deleted without actually deleting: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30 --dry-run
</code></pre>

</div>



Output: 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>[DRY RUN] Would remove 15,420 lines from laravel.log
[DRY RUN] Estimated space to free: 45.2 MB
</code></pre>

</div>



Create a backup before cleaning: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30 --backup
</code></pre>

</div>



Output: 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>Backup created: storage/logs/laravel.log.backup.2024-11-05-14-30-15
Logs older than 30 days have been removed.
</code></pre>

</div>



<h3>
 
 
 2. Compression Instead of Deletion 📦
</h3>

Archive old logs for compliance or audit purposes: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30 --compress
</code></pre>

</div>



This creates <code>laravel.log.old.2024-11-05.gz</code> - perfect for when you need to keep logs but save disk space.

<h3>
 
 
 3. Log Level Filtering 🎯
</h3>

Keep only critical errors, discard everything else: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=0 --level=ERROR
</code></pre>

</div>



This is huge for production. Most of your logs are probably DEBUG or INFO - useful during development but just noise after a few days in production.

Supported levels: <code>DEBUG</code>, <code>INFO</code>, <code>WARNING</code>, <code>ERROR</code>, <code>CRITICAL</code>

<h3>
 
 
 4. Memory-Efficient Processing 🧠
</h3>

The game-changer for huge log files: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30 --memory-efficient
</code></pre>

</div>



Before v2.0: A 2GB log file would crash PHP with "out of memory" errors 
After v2.0: Processes the same file using stream processing, never loads more than 50MB in RAM

The package automatically detects large files (&gt;50MB) and enables memory-efficient mode, but you can force it with this flag.
<h3>
 
 
 5. Custom Date Patterns 🔍
</h3>

Got non-standard log formats? No problem: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30 --pattern="/^(\d{4}-\d{2}-\d{2})/"
</code></pre>

</div>



<h3>
 
 
 6. Combine Everything 🚀
</h3>

The complete workflow: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=30 --backup --compress --level=ERROR --dry-run
</code></pre>

</div>



This command:

<ol>
<li>Previews what would be deleted (dry-run)</li>
<li>Creates a backup before making changes</li>
<li>Compresses old logs instead of deleting</li>
<li>Keeps only ERROR level logs</li>
</ol>

<h2>
 
 
 Real-World Use Case
</h2>

Here's how I use it in production:

<h3>
 
 
 Laravel 11+ (Current)
</h3>

Schedule in <code>routes/console.php</code>: 


<div class="highlight js-code-highlight">
<pre class="highlight php"><code>use Illuminate\Support\Facades\Schedule;

// Every day at 2 AM - keep 7 days of ERROR logs
Schedule::command('log:clear', [
 '--days' =&gt; 7,
 '--backup' =&gt; true,
 '--level' =&gt; 'ERROR'
])-&gt;daily()-&gt;at('02:00');

// Weekly deep clean with compression
Schedule::command('log:clear', [
 '--days' =&gt; 30,
 '--compress' =&gt; true
])-&gt;weekly()-&gt;sundays()-&gt;at('03:00');
</code></pre>

</div>



<h3>
 
 
 Laravel 10 and Below
</h3>

Schedule in <code>app/Console/Kernel.php</code>: 


<div class="highlight js-code-highlight">
<pre class="highlight php"><code>protected function schedule(Schedule $schedule)
{
 $schedule-&gt;command('log:clear', [
 '--days' =&gt; 7,
 '--backup' =&gt; true,
 '--level' =&gt; 'ERROR'
 ])-&gt;daily()-&gt;at('02:00');

 $schedule-&gt;command('log:clear', [
 '--days' =&gt; 30,
 '--compress' =&gt; true
 ])-&gt;weekly()-&gt;sundays()-&gt;at('03:00');
}
</code></pre>

</div>



<h3>
 
 
 Result:
</h3>

<ul>
<li>✅ Keeps 7 days of ERROR logs for quick debugging</li>
<li>✅ Archives everything older in compressed format</li>
<li>✅ Never runs out of disk space</li>
<li>✅ No manual intervention needed</li>
<li>✅ Backups created automatically</li>
</ul>

<h2>
 
 
 Performance Benchmarks 📊
</h2>

I tested this on a real production log file from one of my client's projects:

Test File: 1.2 GB, 3.5 million lines

<div class="table-wrapper-paragraph"><table>
<thead>
<tr>
<th>Operation</th>
<th>v1.0</th>
<th>v2.0</th>
<th>Improvement</th>
</tr>
</thead>
<tbody>
<tr>
<td>Clear all logs</td>
<td>45s</td>
<td>12s</td>
<td>
73% faster ⚡</td>
</tr>
<tr>
<td>Filter by date (30 days)</td>
<td>Memory error ❌</td>
<td>18s</td>
<td>
Now possible ✅</td>
</tr>
<tr>
<td>Memory usage (peak)</td>
<td>512MB+</td>
<td>48MB</td>
<td>
90% reduction 🎯</td>
</tr>
<tr>
<td>Compression</td>
<td>Not supported</td>
<td>8s</td>
<td>
New feature 🆕</td>
</tr>
</tbody>
</table></div>

<h2>
 
 
 Why Not Use X? 🤔
</h2>

<h3>
 
 
 vs. Manual deletion (<code>rm laravel.log</code> or <code>echo "" &gt; laravel.log</code>)
</h3>

<ul>
<li>❌ No selective date filtering</li>
<li>❌ Risk of deleting current day's logs</li>
<li>❌ No backup option</li>
<li>❌ Can't filter by log level</li>
</ul>

<h3>
 
 
 vs. Laravel Telescope
</h3>

<ul>
<li>❌ Telescope is heavy (database overhead, UI, background jobs)</li>
<li>❌ Can actually slow down your app in production</li>
<li>✅ Laravel Log Cleaner has zero runtime overhead
</li>
<li>✅ Only runs when you schedule it</li>
</ul>

<h3>
 
 
 vs. Other log cleaner packages
</h3>

Most alternatives:

<ul>
<li>❌ Don't handle memory efficiently (crash on large files)</li>
<li>❌ No compression support</li>
<li>❌ No log level filtering</li>
<li>❌ No dry-run mode for safety</li>
<li>❌ Limited or no backup functionality</li>
</ul>

<h2>
 
 
 Compatibility
</h2>

Current Version (v2.x):

<ul>
<li>PHP 8.1, 8.2, 8.3+</li>
<li>Laravel 9.x, 10.x, 11.x, 12.x</li>
</ul>

Legacy Support (v1.x): 
If you're still on older versions: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>composer require jiordiviera/laravel-log-cleaner:^1.0
</code></pre>

</div>



<ul>
<li>PHP 7.0+</li>
<li>Laravel 7.x, 8.x</li>
</ul>

<h2>
 
 
 Migration from v1.x
</h2>

Upgrading from v1.x? It's seamless!

Step 1: Update via Composer 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>composer update jiordiviera/laravel-log-cleaner
</code></pre>

</div>



Step 2: Check PHP/Laravel requirements

<ul>
<li>Requires PHP 8.1+</li>
<li>Requires Laravel 9+</li>
</ul>

Step 3: Enjoy new features! 
All your existing commands still work. The new features are opt-in via command flags.

Breaking changes:

<ul>
<li>Dropped PHP 7.x support</li>
<li>Dropped Laravel 7.x and 8.x support</li>
<li>If you need these versions, stay on v1.x</li>
</ul>

<h2>
 
 
 Common Use Cases
</h2>

<h3>
 
 
 1. Development: Keep Recent Logs Only
</h3>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=3
</code></pre>

</div>



<h3>
 
 
 2. Production: Aggressive Cleanup with Safety
</h3>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=7 --backup --level=ERROR
</code></pre>

</div>



<h3>
 
 
 3. Compliance: Archive Everything
</h3>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=90 --compress
</code></pre>

</div>



<h3>
 
 
 4. Emergency: Server Running Out of Space
</h3>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code># Preview impact first
php artisan log:clear --days=1 --dry-run

# If safe, execute
php artisan log:clear --days=1 --backup
</code></pre>

</div>



<h3>
 
 
 5. CI/CD Pipeline: Clean After Tests
</h3>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>php artisan log:clear --days=0
</code></pre>

</div>



<h2>
 
 
 What's Next? 🔮
</h2>

I'm considering these features for future releases:

<ul>
<li>🗂️ Multiple log file support (<code>--file=api.log</code>)</li>
<li>📧 Slack/Email notifications on cleanup completion</li>
<li>⚙️ Config file for environment-specific retention policies</li>
<li>☁️ Cloud storage integration (S3, GCS, Azure)</li>
<li>📊 Log analytics before cleanup (show stats)</li>
<li>🔄 Auto-rotation based on file size (not just days)</li>
</ul>

What would YOU like to see? Drop a comment below! Your feedback shapes the roadmap.

<h2>
 
 
 Try It Out
</h2>



<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>composer require jiordiviera/laravel-log-cleaner
php artisan log:clear --help
</code></pre>

</div>



Links:

<ul>
<li>📦 <a href="https://packagist.org/packages/jiordiviera/laravel-log-cleaner" rel="noopener noreferrer">Packagist</a>
</li>
<li>🐙 <a href="https://github.com/jiordiviera/laravel-log-cleaner" rel="noopener noreferrer">GitHub Repository</a>
</li>
<li>⭐ Star on GitHub if you find it useful!</li>
</ul>

<h2>
 
 
 Contributing
</h2>

Found a bug? Have a feature request? Contributions are welcome!

<ol>
<li>Fork the repo</li>
<li>Create a feature branch</li>
<li>Write tests (we use Pest)</li>
<li>Submit a PR</li>
</ol>

Check out the <a href="https://github.com/jiordiviera/laravel-log-cleaner/blob/main/CONTRIBUTING.md" rel="noopener noreferrer">Contributing Guide</a>.




<h2>
 
 
 About Me
</h2>

I'm Jiordi Viera, a fullstack developer from Douala, Cameroon 🇨🇲. I work primarily with Laravel, Next.js, and React. 

I built this package after dealing with production log issues one too many times. What started as a simple script evolved into a full package when I realized others had the same problem.

If this package helps you, consider:

<ul>
<li>⭐ Starring the <a href="https://github.com/jiordiviera/laravel-log-cleaner" rel="noopener noreferrer">GitHub repo</a>
</li>
<li>📢 Sharing this article</li>
<li>☕ Buying me a coffee (if you're feeling generous)</li>
</ul>

Connect with me:

<ul>
<li>🌐 Website: <a href="https://jiordiviera.me" rel="noopener noreferrer">jiordiviera.me</a>
</li>
<li>🐙 GitHub: <a href="https://github.com/jiordiviera" rel="noopener noreferrer">@jiordiviera</a>
</li>
<li>💼 LinkedIn: [Add your LinkedIn if you have one]</li>
<li>🐦 Twitter/X: [Add your handle if you have one]</li>
</ul>

Other projects:

<ul>
<li>
<a href="https://codepit.jiordiviera.me" rel="noopener noreferrer">Codepit</a> - A minimal platform to share code snippets</li>
</ul>




Thanks for reading! If you found this helpful, please leave a ❤️ and share your experience in the comments below.

Happy logging! 🚀

<h1>
 
 
 Laravel #PHP #OpenSource #DevOps #WebDev #BackendDevelopment
</h1>

تأتي Laravel Log Cleaner v2.0 لتحدث ثورة في كيفية إدارة المطورين لملفات السجل، حيث تعالج المشكلة الشائعة لاستخدام مساحة القرص بشكل مفرط. تقدم هذه النسخة الجديدة إدارة فعالة للذاكرة مع ميزات مثل الضغط والنسخ الاحتياطي، مما يسهل على المطورين الحفاظ على تطبيقاتهم دون الخوف من نفاد المساحة. إنها نقطة تحول لأي شخص يستخدم Laravel، مما يضمن عمليات أكثر سلاسة وأقل متاعب عند إدارة ملفات السجل.

Laravel Log Cleaner v2.0 llega para revolucionar la gestión de archivos de registro de los desarrolladores, abordando el problema común del uso excesivo del espacio en disco. Esta nueva versión presenta una gestión de registros eficiente en memoria con características como compresión y respaldo, facilitando a los desarrolladores el mantenimiento de sus aplicaciones sin el temor de quedarse sin espacio. Es un cambio radical para cualquier persona que use Laravel, asegurando operaciones más fluidas y menos complicaciones en la gestión de archivos de registro.

Laravel Log Cleaner v2.0 arrive pour révolutionner la gestion des fichiers journaux des développeurs, en répondant au problème courant de l'utilisation excessive de l'espace disque. Cette nouvelle version introduit une gestion des journaux efficace en mémoire avec des fonctionnalités telles que la compression et la sauvegarde, facilitant ainsi la maintenance des applications sans craindre de manquer d'espace. C'est un changement de jeu pour quiconque utilise Laravel, garantissant des opérations plus fluides et moins de tracas en matière de gestion des fichiers journaux.

Laravel Log Cleaner v2.0 is here to revolutionize how developers manage log files, addressing the common issue of excessive disk space usage. This new version introduces memory-efficient log management with features like compression and backup, making it easier for developers to maintain their applications without the fear of running out of space. It's a game-changer for anyone using Laravel, ensuring smoother operations and less hassle when it comes to log file management.

Laravel Log Cleaner v2.0 - Memory-Efficient Log Management with Compression & Backup

Most AI deployments wait for a prompt. Real operations do not. A manager defines a goal, delegates work, and people go collect facts, make decisions, and return results. What we need is AI agents that have an intent and initiate conversations with a goal.

The system below mirrors that familiar pattern with task templates, action chains, a watchdog that moves work forward, and scout agents that initiate conversations. It is simple to describe, strong in practice, and it scales. Everything described here is doable with existing technologies.

Let's look at the main components that make up such a system:

<h1>
 
 
 System Components
</h1>

<h2>
 
 
 1) Task template
</h2>

A task template is the starting point. It contains an action chain plus basic metadata like name and description. Task Templates are executed by an event, on a schedule, when criteria are met, or on demand by a human. 
When a template is executed, it becomes a task instance with its own state and audit trail.

<h2>
 
 
 2) Action chain
</h2>

An action chain is a list of actions that run in order inside a task. Each action has an embedded AI agent and the watchdog oversees execution. Actions come in a few types:

<ul>
<li>Scout Agents. Initiates a conversation with one or more counterparties and collects structured data. Scouts are detached by design. People can ignore a message or take time to answer, so the system must tolerate latency and silence. Scout agents are implemented by temporarily replacing the normal support agent in the support chat with it self and initiating a conversation with a pre-defined templatable greeting.</li>
<li>Create PDF. Uses a Word template and a simple JSON [key name]/[description] schema to generate a finished document as an artifact.</li>
<li>Compose and send email. Writes an email from instructions and can attach artifacts created earlier in the chain.</li>
<li>Perform other actions. Talk to an API, make a change in the database, post to a queue, or anything else needed. The sky is the limit here.</li>
</ul>

Every action in the task template and subsequently in the executed task instance includes:

<ul>
<li>Instructions. Plain language guidance that becomes part of the system prompt. For example, write an email about subject X or collect data about subject Y.</li>
<li>Input. The output of the previous action or fields fetched from the task data store.</li>
<li>Output. A structured payload for the next action and for the task data store.</li>
<li>Timeout policy. What to do if the action does not complete in time. Abort the task, alert a human, or ignore and continue.</li>
</ul>

The task has a general data store. Any action can write to it. Subsequent actions can read from it. This keeps the chain loosely coupled and easy to extend. LLMs are fantastically adopted to reading loosely structured data and understanding it’s context.

<h2>
 
 
 3) Watchdog
</h2>

The watchdog advances the chain. It starts actions, monitors completion, enforces timeouts, and dispatches the next step. If an action stalls, the watchdog retries, switches channel, escalates to a human, or bails out per policy. It also keeps the log, timestamps each event, and stores artifacts. Think of it as the manager who checks progress and pushes the work forward.

<h2>
 
 
 4) Document templates
</h2>

A document template is a Word file with {{tags}} and a schema for expected data. Templates can attach to a PDF action to produce a signed or branded document. They can also attach to a scout action so the scout knows exactly which fields to collect. The schema is the contract. It gives the system a way to validate outputs before side effects happen.

<h1>
 
 
 Three simple use cases
</h1>

<h2>
 
 
 1) Collect pizza orders from the whole office
</h2>

Let's start off with something simple to illustrate the functionality of each component in the chain.

<ol>
<li>The task dispatches scouts to everyone on the team.</li>
<li>Each scout opens a chat, gathers order, size, and special notes, then writes the result into the task data store.</li>
<li>When all scouts complete or hit a timeout, the next action composes a single email to the pizzeria and sends it.
Instructions for the final action that composes an email, has access to the task instance data store and an agent doing the job in the task template can be as simple as: </li>
</ol>

<code>Write a pizza order to some,local@pizza.joint using the available requests in the data store, deliver the order to our office at Some Street 123 and invoice Acme Inc account number #123 or bring a card terminal. 
</code> 
The role of the timeout and bail out functions here would be that if a scout fails to collect the pizza wishes from a team member, ignore it and send the order out at 11:30 anyway.

<h2>
 
 
 2) Help a customer file an insurance claim
</h2>

Next let's examine a different flow and another way to trigger an execution of a task instance.

<ol>
<li>In support chat, the customer tells the default agent that they need help filing an insurance claim.</li>
<li>The default agent selects the “insurance claim” task template and it is executed.</li>
<li>The template includes a Word document and a schema that lists incident fields.</li>
<li>A scout opens a conversation with the customer, collects the fields, and writes the JSON to the task data store and outputs it as the input to the next action.</li>
<li>A PDF action fills the Word template and outputs a final document.</li>
<li>An email action writes a short cover note and sends the PDF to the insurer mailbox.</li>
</ol>

Task templates automatically becoming tools that your customer default support AI agent can dispatch is the revolutionary part here. 

How many different jobs performed by some human in the office are essentially: Go talk to someone about something, write a document about it and send it to someone? Think about it, quite a lot. 
Now just by defining the necessary task templates in an admin interface for each of these and selecting them to become available as tools lets you automate a lot of processes.

<h2>
 
 
 3) Update all customer phone numbers
</h2>

<ol>
<li>The task dispatches scouts to every customer.</li>
<li>Each scout asks for the current phone number and returns a structured payload.</li>
<li>A database action validates the format and updates the record. Errors are logged for human review.</li>
</ol>

This example is powerful because the scout agents can all run in parallel. Updating the customer database can be done in 30 minutes for all customers compared to humans doing the work in a series. 
Timeout and bail out parameters here can be set to like a day and alerts generated for scouts that were not able to complete their tasks.

<h1>
 
 
 Why full platform control matters
</h1>

Scout agents only work when you control the full system where the chain runs. You need to open and manage chat threads with a separate chat agent handling them, attach forms and files, tag each message with a correlation id, and capture consent. You need to validate outputs against a schema before taking any action. You need clean audit logs. Stitching this across many unrelated tools is brittle.

This is why platforms like Salesforce, Odoo or others are natural homes for detached chains. Both combine workflow, data, and communications. You can create records, run server actions, post to chat, and store artifacts in one place. You can also add human review steps that see the full context. If your organization cannot use these, you can build the ecosystem in house. The key is ownership of channels and data paths.

Chat control is critical. A scout that cannot open a thread, send a reminder, switch channel, or record consent will fail in real life. The watchdog needs reliable signals from the chat layer to decide whether to retry, escalate, or move on.

<h1>
 
 
 How this mirrors human work
</h1>

This model behaves like a team. A manager defines a mission. Scouts go talk to people, collect facts, and return structured notes. Specialists draft a document or update a system. The watchdog is like a manager. It keeps time, nudges when needed, and escalates when something blocks. The result is predictable progress from intent to artifact without long back and forth.

The difference is that the system never forgets a field, always writes in the right format, and enforces time limits. It also produces an audit trail that shows who said what and when, what data was used, and which decision happened next. And all this can run in parallel and scale on demand.

<h1>
 
 
 Implementation checklist
</h1>

<ol>
<li>Pick a platform where you can control chat, data, and actions in one place.</li>
<li>Define a task template with a short action chain that solves one narrow problem.</li>
<li>Write the scout instructions and the output schema. Keep it concrete.</li>
<li>Add a Word template with {{tags}} for any document you need to produce.</li>
<li>Implement timeout policies. Soft timeout for a nudge. Hard timeout for failover.</li>
<li>Validate every output against the schema before any side effect.</li>
<li>Log transcripts, artifacts, and decisions for audit and training.</li>
<li>Track a few simple metrics. Completion time, first try rate, timeout rate, and cost per completed task.</li>
</ol>

<h1>
 
 
 The power factor is the scout
</h1>

The scout is what turns a static workflow into a living one. It is the agent that can initiate conversations and create new information by talking to people. Everything else is plumbing. Once you can send respectful, purpose built scouts that collect exactly the fields you need, the rest of the chain becomes routine. The watchdog moves the work along. The PDF has the right data. The database stays clean. Customers get what they need without long calls.

That is how detached agent chains become practical. They behave like people, run inside systems you control, and leave artifacts other systems can trust.

Author bio: Antti Kaipila is the founder of <a href="https://nuuduu.com" rel="noopener noreferrer">Nuuduu</a>, a direct service platform that uses AI to automate service delivery.

يظهر نهج جديد للذكاء الاصطناعي يحاكي السلوك البشري من خلال السماح للوكلاء ببدء المحادثات والعمل نحو أهداف محددة دون انتظار التعليمات. يستخدم هذا النظام المبتكر قوالب المهام وسلاسل الإجراءات لتبسيط العمليات، مما يجعله سهل الفهم وفعالًا في الممارسة العملية. من خلال تمكين الذكاء الاصطناعي من اتخاذ المبادرة، يمكن للشركات تعزيز الإنتاجية واتخاذ القرارات، وهو أمر بالغ الأهمية في بيئة اليوم السريعة.

Está surgiendo un nuevo enfoque de la IA que imita el comportamiento humano al permitir que los agentes inicien conversaciones y trabajen hacia objetivos definidos sin esperar a que se les indique. Este sistema innovador utiliza plantillas de tareas y cadenas de acciones para optimizar las operaciones, lo que lo hace no solo fácil de entender, sino también efectivo en la práctica. Al permitir que la IA tome la iniciativa, las empresas pueden mejorar la productividad y la toma de decisiones, lo cual es crucial en el acelerado entorno actual.

Une nouvelle approche de l'IA émerge, imitant le comportement humain en permettant aux agents d'initier des conversations et de travailler vers des objectifs définis sans attendre de prompts. Ce système innovant utilise des modèles de tâches et des chaînes d'actions pour rationaliser les opérations, le rendant à la fois simple à comprendre et efficace en pratique. En permettant à l'IA de prendre l'initiative, les entreprises peuvent améliorer la productivité et la prise de décision, ce qui est crucial dans l'environnement rapide d'aujourd'hui.

A new approach to AI is emerging that mimics human behavior by allowing agents to initiate conversations and work towards defined goals without waiting for prompts. This innovative system uses task templates and action chains to streamline operations, making it not only simple to understand but also effective in practice. By enabling AI to take the initiative, businesses can enhance productivity and decision-making, which is crucial in today's fast-paced environment.

Detached agent chains that work like people do

Andrew Cuomo's campaign embraced AI — and it made him a toxic laughingstock, while Zohran Mamdani cruised to victory.
The post <a href="https://futurism.com/artificial-intelligence/andrew-cuomo-ai-toxic">Andrew Cuomo&#8217;s Extensive Use of AI Made His Campaign a Toxic Joke</a> appeared first on <a href="https://futurism.com">Futurism</a>.

اعتمدت حملة أندرو كومو بشكل كبير على تقنية الذكاء الاصطناعي، لكن بدلاً من تعزيز فرصه، تحولت إلى مصدر للسخرية، مما جعله موضع سخرية في الساحة السياسية. في هذه الأثناء، حقق زوهرا مامداني النصر، مما يبرز الفارق الواضح بين نهجيهما. تسلط هذه الحالة الضوء على المخاطر المحتملة للاعتماد المفرط على التكنولوجيا في الحملات السياسية، مما يذكر المرشحين بأن الأصالة والاتصال بالناخبين أمران حاسمان لتحقيق النجاح.

La campaña de Andrew Cuomo se basó en gran medida en la tecnología de IA, pero en lugar de mejorar sus posibilidades, se convirtió en objeto de burla, convirtiéndolo en un hazmerreír en la arena política. Mientras tanto, Zohran Mamdani emergió victorioso, destacando el marcado contraste entre sus enfoques. Esta situación subraya las posibles trampas de depender en exceso de la tecnología en las campañas políticas, recordando a los candidatos que la autenticidad y la conexión con los votantes son cruciales para el éxito.

La campagne d'Andrew Cuomo a fortement misé sur la technologie de l'IA, mais au lieu d'améliorer ses chances, cela a conduit à des moqueries, faisant de lui un objet de ridicule sur la scène politique. Pendant ce temps, Zohran Mamdani a remporté la victoire, soulignant le contraste entre leurs approches. Cette situation met en lumière les pièges potentiels d'une dépendance excessive à la technologie dans les campagnes politiques, rappelant aux candidats que l'authenticité et la connexion avec les électeurs sont essentielles pour réussir.

Andrew Cuomo's campaign heavily relied on AI technology, but instead of boosting his chances, it turned into a source of ridicule, making him a laughingstock in the political arena. Meanwhile, Zohran Mamdani emerged victorious, highlighting the stark contrast between their approaches. This situation underscores the potential pitfalls of over-relying on technology in political campaigns, reminding candidates that authenticity and connection with voters are crucial for success.

Andrew Cuomo’s Extensive Use of AI Made His Campaign a Toxic Joke

In an AI‑driven economy, where every release carries risk, it is engineering leadership that turns that risk into resilience.

في الاقتصاد المدفوع بالذكاء الاصطناعي اليوم، يلعب القيادة الهندسية دورًا حاسمًا في تحويل المخاطر إلى مرونة، مما يجعل الأتمتة عاملًا رئيسيًا للنمو.

En la economía impulsada por la IA de hoy, el liderazgo en ingeniería desempeña un papel crucial en la transformación de los riesgos en resiliencia, convirtiendo la automatización en un factor clave para el crecimiento.

Dans l'économie actuelle axée sur l'IA, le leadership en ingénierie joue un rôle crucial dans la transformation des risques en résilience, faisant de l'automatisation un facteur clé de croissance.

In today's AI-driven economy, engineering leadership plays a crucial role in transforming risks into resilience, making automation a key factor for growth.

Automation to Trust: The New Currency of Growth

Investment around the town of Sines totals almost 5% of GDP as the country seeks to retool its economy for the 21st century.

تسعى البرتغال إلى تحديث اقتصادها من خلال جذب مراكز البيانات، وخاصة حول مدينة سينيش، حيث تقترب الاستثمارات من 5% من الناتج المحلي الإجمالي. يبرز هذا التحول جاذبية البلاد المتزايدة كمركز تكنولوجي، كما يهدف إلى تنويع الاقتصاد بعيدًا عن السياحة، مما يضمن نموًا مستدامًا في المستقبل.

Portugal está avanzando para modernizar su economía al atraer centros de datos, especialmente alrededor de la ciudad de Sines, donde las inversiones se acercan al 5% del PIB. Este cambio no solo destaca el creciente atractivo del país como un centro tecnológico, sino que también busca diversificar su economía más allá del turismo, asegurando un crecimiento sostenible para el futuro.

Le Portugal fait des progrès pour moderniser son économie en attirant des centres de données, notamment autour de la ville de Sines, où les investissements approchent 5 % du PIB. Ce changement met en lumière l'attrait croissant du pays en tant que pôle technologique et vise également à diversifier son économie au-delà du tourisme, garantissant une croissance durable pour l'avenir.

Portugal is making strides to modernize its economy by attracting data centers, particularly around the town of Sines, where investments are nearing 5% of the GDP. This shift not only highlights the country's growing appeal as a tech hub but also aims to diversify its economy beyond tourism, ensuring sustainable growth for the future.

Portugal Has Plenty of Tourists. Now It Wants Data Centers

Two minor-aged girls were thrown from a Ferris Wheel at Louisiana during the Harvest Festival. Witnesses recalled how they heard horrifying screams.

وقعت حادثة مأساوية في مهرجان الحصاد في لويزيانا عندما تم إلقاء فتاتين صغيرتين من عجلة فيريس، مما ترك الشهود في حالة صدمة وهم يتذكرون الصرخات المرعبة. يسلط هذا الحدث الضوء على أهمية تدابير السلامة في حدائق الملاهي ويثير القلق بشأن رفاهية الأطفال خلال مثل هذه الاحتفالات.

Un trágico incidente ocurrió en el Harvest Festival de Luisiana cuando dos niñas fueron arrojadas de una noria, dejando a los testigos en estado de shock al recordar los gritos horripilantes. Este evento resalta la importancia de las medidas de seguridad en los parques de atracciones y plantea preocupaciones sobre el bienestar de los niños durante tales festividades.

Un incident tragique s'est produit lors du Harvest Festival en Louisiane, lorsque deux jeunes filles ont été projetées d'une grande roue, laissant les témoins sous le choc en se remémorant les cris horrifiants. Cet événement souligne l'importance des mesures de sécurité dans les parcs d'attractions et soulève des inquiétudes quant au bien-être des enfants lors de telles festivités.

A tragic incident occurred at the Louisiana Harvest Festival when two young girls were thrown from a Ferris wheel, leaving witnesses in shock as they recalled the horrifying screams. This event highlights the importance of safety measures at amusement parks and raises concerns about the well-being of children during such festivities.

Louisiana Harvest Festival Tragedy: Witnesses Recall Screams as Two Girls Thrown From Ferris Wheel

<img width="1600" height="900" src="https://analyticsindiamag.com/wp-content/uploads/2025/11/AI-Is-Free-in-India-Until-It-Isnt.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="" style="display: block; margin: auto; margin-bottom: 5px;max-width: 100%;" link_thumbnail="" decoding="async" loading="lazy" srcset="https://analyticsindiamag.com/wp-content/uploads/2025/11/AI-Is-Free-in-India-Until-It-Isnt.jpg 1600w, https://analyticsindiamag.com/wp-content/uploads/2025/11/AI-Is-Free-in-India-Until-It-Isnt-1300x731.jpg 1300w, https://analyticsindiamag.com/wp-content/uploads/2025/11/AI-Is-Free-in-India-Until-It-Isnt-768x432.jpg 768w, https://analyticsindiamag.com/wp-content/uploads/2025/11/AI-Is-Free-in-India-Until-It-Isnt-1536x864.jpg 1536w" sizes="auto, (max-width: 1600px) 100vw, 1600px" />“The main risk is that we might end up relying too heavily on Western tech companies that distribute their products in India.”
The post <a href="https://analyticsindiamag.com/global-tech/the-heavy-price-of-free-ai-in-india/">The Heavy Price of Free AI in India</a> appeared first on <a href="https://analyticsindiamag.com">Analytics India Magazine</a>.

يتناول المقال تداعيات خدمات الذكاء الاصطناعي المجانية في الهند، مسلطًا الضوء على الفوائد والعيوب المحتملة. بينما يمكن أن يؤدي الوصول المجاني إلى تكنولوجيا الذكاء الاصطناعي إلى تعزيز الابتكار والنمو الاقتصادي، فإنه يثير أيضًا مخاوف بشأن الاستدامة والتكاليف طويلة الأجل المرتبطة بالاعتماد على هذه الخدمات. فهم هذا التوازن أمر بالغ الأهمية لصانعي السياسات والشركات أثناء تنقلهم في المشهد المتطور للذكاء الاصطناعي في البلاد.

El artículo discute las implicaciones de los servicios de IA gratuitos en India, destacando tanto los beneficios como los posibles inconvenientes. Si bien el acceso gratuito a la tecnología de IA puede impulsar la innovación y el crecimiento económico, también plantea preocupaciones sobre la sostenibilidad y los costos a largo plazo asociados con la dependencia de estos servicios. Comprender este equilibrio es crucial para los responsables de políticas y las empresas mientras navegan por el paisaje en evolución de la IA en el país.

L'article aborde les implications des services d'IA gratuits en Inde, mettant en lumière à la fois les avantages et les inconvénients potentiels. Bien que l'accès gratuit à la technologie IA puisse stimuler l'innovation et la croissance économique, il soulève également des préoccupations concernant la durabilité et les coûts à long terme associés à cette dépendance. Comprendre cet équilibre est crucial pour les décideurs et les entreprises alors qu'ils naviguent dans le paysage évolutif de l'IA dans le pays.

The article discusses the implications of free AI services in India, highlighting both the benefits and potential drawbacks. While free access to AI technology can drive innovation and economic growth, it also raises concerns about sustainability and the long-term costs associated with reliance on these services. Understanding this balance is crucial for policymakers and businesses as they navigate the evolving landscape of AI in the country.

The Heavy Price of Free AI in India

Australia expanded its world-first under-16 social media ban to include Reddit and Kick, effective December 10. Nine platforms—Facebook, Instagram, TikTok, X, YouTube, Snapchat, Threads, Reddit, and Kick—face AU$49.5M fines for non-compliance. WhatsApp and gaming platforms are exempt.

أستراليا اتخذت خطوة جريئة من خلال توسيع قانونها الصارم بشأن وسائل التواصل الاجتماعي، حيث تطلب الآن من تسع منصات، بما في ذلك Reddit وKick، حظر المستخدمين الذين تقل أعمارهم عن 16 عامًا أو مواجهة غرامات كبيرة. هذا القانون، الذي سيدخل حيز التنفيذ في 10 ديسمبر، يهدف إلى حماية القاصرين عبر الإنترنت، لكنه يثير مخاوف بشأن حرية التعبير وإمكانية تطبيقه. مع غرامات تصل إلى 49.5 مليون دولار أسترالي لعدم الامتثال، فإن الآثار المترتبة على شركات وسائل التواصل الاجتماعي كبيرة، مما قد يعيد تشكيل كيفية عملها في أستراليا.

Australia ha dado un paso audaz al ampliar su estricta ley de redes sociales, exigiendo que nueve plataformas, incluidas Reddit y Kick, bloqueen a los usuarios menores de 16 años o enfrenten multas considerables. Esta ley, que entrará en vigor el 10 de diciembre, tiene como objetivo proteger a los menores en línea, pero plantea preocupaciones sobre la libertad de expresión y la viabilidad de su aplicación. Con multas que alcanzan los 49,5 millones de dólares australianos por incumplimiento, las implicaciones para las empresas de redes sociales son significativas, lo que podría cambiar la forma en que operan en Australia.

L'Australie a pris une mesure audacieuse en élargissant sa loi stricte sur les réseaux sociaux, exigeant désormais que neuf plateformes, y compris Reddit et Kick, bloquent les utilisateurs de moins de 16 ans ou fassent face à des amendes lourdes. Cette loi, qui entrera en vigueur le 10 décembre, vise à protéger les mineurs en ligne, mais soulève des inquiétudes concernant la liberté d'expression et la faisabilité de son application. Avec des amendes atteignant 49,5 millions de dollars australiens pour non-conformité, les implications pour les entreprises de médias sociaux sont significatives, pouvant remodeler leur fonctionnement en Australie.

Australia has taken a bold step by expanding its strict social media law, now requiring nine platforms, including Reddit and Kick, to block users under 16 or face hefty fines. This law, effective December 10, aims to protect minors online but raises concerns about freedom of expression and the feasibility of enforcement. With fines reaching AU$49.5 million for non-compliance, the implications for social media companies are significant, potentially reshaping how they operate in Australia.

World's Strictest Social Media Law: 9 Platforms Must Block Everyone Under 16 or Pay $33M

NASA confirms 3I/ATLAS visible tonight — learn when and where to spot the rare interstellar comet lighting up Earth's skies before it vanishes again.

هذا المساء، سيكون عشاق الفلك على موعد مع رؤية المذنب النادر 3I/ATLAS، الذي أكدت ناسا أنه سيكون مرئيًا من الأرض. إنها فرصة فريدة لمشاهدة ظاهرة سماوية لن تدوم طويلاً، مما يجعلها حدثًا لا بد من حضوره لعشاق الفلك والمراقبين العاديين على حد سواء. معرفة متى وأين تنظر يمكن أن تعزز التجربة، لذا احضر منظارك واستمتع بهذا الحدث الرائع بينما يستمر!

Esta noche, los observadores del cielo tendrán la oportunidad de ver la rara cometa interstelar 3I/ATLAS, confirmada por la NASA como visible desde la Tierra. Es una oportunidad única para presenciar un fenómeno celestial que no durará mucho tiempo, lo que lo convierte en un evento imperdible tanto para los entusiastas de la astronomía como para los observadores ocasionales. Saber cuándo y dónde mirar puede mejorar la experiencia, así que agarra tus binoculares y disfruta de este espectacular evento mientras dure.

Ce soir, les passionnés d'astronomie auront la chance d'observer la comète interstellaire rare 3I/ATLAS, confirmée par la NASA comme visible depuis la Terre. C'est une occasion unique de voir un phénomène céleste qui ne durera pas longtemps, ce qui en fait un événement incontournable pour les amateurs d'astronomie et les observateurs occasionnels. Savoir quand et où regarder peut améliorer l'expérience, alors prenez vos jumelles et profitez de ce spectacle spectaculaire tant qu'il dure !

Tonight, skywatchers are in for a treat as NASA confirms that the rare interstellar comet 3I/ATLAS will be visible from Earth. This is a unique opportunity to witness a celestial phenomenon that won't last long, making it a must-see for astronomy enthusiasts and casual observers alike. Knowing when and where to look can enhance the experience, so grab your binoculars and enjoy this spectacular event while it lasts!

3I/ATLAS Comet Visible Tonight — Astronomer Reveals How to See the Interstellar Visitor from Earth

Colombian President Gustavo Petro again slammed U.S. counterpart Donald Trump over the sanctions against him and his family, saying they are "not only profoundly rude, but an insult to the Colombian nation, a humiliation."

انتقد الرئيس الكولومبي غوستافو بيترو الرئيس الأمريكي دونالد ترامب بسبب فرض عقوبات عليه وعلى عائلته، واصفًا هذه الإجراءات بأنها 'غير مهذبة بشكل عميق' و'إهانة للأمة الكولومبية.' يسلط هذا التبادل الضوء على العلاقات المتوترة بين كولومبيا والولايات المتحدة، مما يبرز تأثير السياسة الدولية على كرامة الأمة.

El presidente colombiano Gustavo Petro ha criticado al presidente estadounidense Donald Trump por imponer sanciones contra él y su familia, calificando estas acciones de 'profundamente groseras' y de 'insulto a la nación colombiana.' Este intercambio resalta las tensas relaciones entre Colombia y Estados Unidos, enfatizando el impacto de la política internacional en la dignidad nacional.

Le président colombien Gustavo Petro a critiqué le président américain Donald Trump pour avoir imposé des sanctions contre lui et sa famille, qualifiant ces actions de 'profondément impolies' et d' 'insulte à la nation colombienne.' Cet échange met en lumière les relations tendues entre la Colombie et les États-Unis, soulignant l'impact de la politique internationale sur la dignité nationale.

Colombian President Gustavo Petro has criticized U.S. President Donald Trump for imposing sanctions on him and his family, calling the actions 'profoundly rude' and an 'insult to the Colombian nation.' This exchange highlights the strained relations between Colombia and the U.S., emphasizing the impact of international politics on national dignity.

50 Cent Invests Millions in Shreveport, One of America's Most Needy Cities, to Build New Entertainment Empire

50 Cent Invests Millions in Shreveport, One of America's Most Needy Cities, to Build New Entertainment Empire

Was this article worth reading? Share it