🚨 NEW BEST PS FOR EACH POSITION 🚨
It is now completely FREE & REPEATABLE with no cooldown!
Eligible Cards:
▪️International Star Performers (They will have 1 PS or PS+ that connects to an IRL moment, but the rest is customisable)
▪️National Pride
▪️National Pride Champs
▪️FUT Birthday
▪️Glory Hunters
@Marrkk11_ gives us his best PS/PS+ for each position 🧵
Check down below 👇
ST:
llama.cpp now has an official website: https://t.co/vztdUpdBWL
Our goal is to make local AI accessible to everyone, and improving the user experience is a big part of that. On the new landing page you’ll find a single-line cross-platform installer. The installation provides a single unified `llama` entrypoint which you can use to run/serve models and interface with 3rd-party agentic applications.
While oriented towards simplified user experience, the new `llama` application also provides all the advanced functionality of the existing llama.cpp tooling with which experienced users are already familiar. Also note that all GGUF models that you might have already downloaded with llama.cpp in the past will be automatically available to use without downloading again (they are stored in the common HF cache on your machine).
We have many improvements in the pipeline both at the UX and at the engine level and we plan to iteratively ship new things over the coming months. One of the main focuses will be seamless integration with local-friendly 3rd-party agents (such as Pi). In the meantime, we’ll continue to listen for feedback from the community and adjust accordingly, so keep letting us know what you think and need.
🇰🇪 Kenya Airports Authority Database Allegedly for Sale
A threat actor claims to be selling a 2TB dataset linked to Kenya Airports Authority (KAA), allegedly containing sensitive operational and user data.
📊 Key Claims:
• ~2TB total data
• Includes:
Internal information systems
User data and service records
Full address details
Asking price: ~$4,000 (negotiable)
🧠 Threat Intelligence Insight:
• Aviation sector data is highly sensitive due to:
Critical infrastructure dependencies
Passenger and operational data exposure
Large datasets like this often indicate:
Long-term access or multiple data sources
Potential mix of internal + customer data
⚠️ Potential Risks:
• Exposure of critical infrastructure information
• Targeting of passengers or staff
• Use in fraud, phishing, or broader aviation-focused attacks
📊 Status: Unverified — based on underground forum listing
⸻
💬 When aviation data is exposed, the impact goes beyond privacy — it touches national infrastructure.
#CyberSecurity #ThreatIntel #DataBreach #Aviation #DarkWeb #CriticalInfrastructure #DDW
The hunger that is waiting for talented Male DJs is still doing push ups while drinking chillers punch …
Whores just put USBs and shake their bums no shame whatsoever …😭😭😭
I created a Github repository to learn System Design, and I'm excited to share that it crossed 30k stars recently.
The repository contains a collection of resources to study:
- System Design Core Concepts
- Networking and API Fundamentals
- Database and Caching Fundamentals
- Distributed Systems, Microservies and Architectural Patterns
- System Design Tradeoffs
- 40+ System Design problems categorized by difficulty level
Check it out here: https://t.co/pkVpi6LxSV
If you find the repo valuable, consider giving it a ⭐️ and share with others.
Thanks to everyone who has starred or forked the repository!
I came across a 3 Month TECH SCHOLARSHIP for Africans and thought someone here might need it.
They’re offering 16+ tech skills and the classes come with a certificate with ACTD, USA badge.
It closes soon, so check it out if you’ve been wanting to start something new.
Apply here 👇🏽
https://t.co/XGPkkEDSZF
If it helps you, share it with someone too
These sites are essential for Data Analysts
1. Mockaroo (https://t.co/ZXBzb025Dt) → generates realistic test data in seconds. I used to spend hours creating fake datasets to practice with. This thing spits out thousands of rows based on whatever parameters you need.
2. SQL Fiddle (https://t.co/oLcpTsDA5S) → test your queries before running them on actual data. Saved me from crashing our database more times than I care to admit.
3. Regex101 (https://t.co/0JIPP9qscM) → makes regular expressions actually make sense. That alone is worth it. I used to copy paste regex patterns and pray they worked.
4. Our World in Data (https://t.co/vu08Mf2n53) → clean, reliable datasets on basically everything. When your boss asks for "industry benchmarks" at 4pm, this is where you go.
5. Datawrapper (https://t.co/doYe0BINms) → creates charts that don't look like they're from 2003. Your stakeholders will think you hired a designer.
6. Mode Analytics (https://t.co/Lhe8yrwInK) → runs SQL, Python, and R in the same place. No more switching between five different tools to finish one analysis.
These tools don't make you a better analyst, they just stop you from wasting time on things that shouldn't take time in the first place.
Thanks to Goodness Nwadibie for sharing, I hope it helps beginners in DA.