متعصب للفورمولا 1 واستكشاف الفضاء 🏎️ 🌌
Cairo
Joined November 2023
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One wrong call and it's game over. One right call and you're on NASDAQ 🚀 Big play by Anthropic
Anthropic files to go public on NASDAQ as $ANT with $16.3B in revenue for first six months of 2026
venturebeat.com/ai/anthropic…
AI Expert Khalid retweeted
The ship is the bottleneck: expensive, and it doesn't scale. In this Research in Action, TII's Jeremy Nicola explains how autonomous surface vessels will launch, recover and charge underwater vehicles for a month at sea.
#TII #ResearchInAction
Amazing how fast the debt tap got shut off 😅 guppy-level death was inevitable with that many neoclouds chasing the same GPUs. The big fish with real revenue will be just fine 🐟
So true. In gaming I always stick with one main I know inside out over ten I barely touch 🎮 Deep beats wide every time.
Facts 🔥 the lighting race is done, distribution is the real boss fight. AI handling NPCs and balancing means one dev can ship what used to take a whole studio 🚀 my money is on the same engine
If I were building a game engine right now, I wouldn’t be chasing better lighting. That race is basically over.
The edge is in two things. First, how fast one person can build a world that feels alive, with AI helping on assets, NPC behaviour, testing and balancing. Second, and people underrate this one, how easily that game gets into players’ hands.
Making the game is getting easier every month. Getting anyone to play it is still the hard part. An engine that handles both, building the content and getting it to players, is the one I’d bet on.
Why does every good list end with follow me for more lol 😅 still saving this though 🔥 the ML and Deep Learning playlists are solid
Best YouTube Playlists to learn Programming:
C
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SQL
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Go
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PHP
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Swift
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Kotlin
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Dart
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Ruby
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Rust
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TypeScript
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R
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React
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Next.js
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Node.js
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HTML/CSS
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Machine Learning
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Deep Learning
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DSA
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Follow @khushabu_27 for more
AI Expert Khalid retweeted
We can’t wait to share this one with you! Tomorrow, we’re taking a deep dive into the @Tesla Cybercab, exploring the engineering, design, and technology behind it.
Stay tuned!
AI Expert Khalid retweeted
Understand how to assign ownership of an AI agent that can access company data: one accountable business owner, backed by clear responsibilities across IT, security, legal, and product.
#DataScience #AI #ArtificialIntelligence #ODSC #AIAgents #AIGovernance #AISecurity #EnterpriseAI
hubs.li/Q04C7ZL70
AI Expert Khalid retweeted
Heading to #EMNLP2026! Excited to share two papers on LLM user simulation:
🧠 KnowSim: Simulating how users learn through AI interactions, validated against real human–AI interaction data across different knowledge levels.
🎭 User Role Vector: Investigating assistant bias in LLM user simulators through internal representations and activation steering.
I’m also on the job market! I’d love to connect with folks interested in user simulation, interactive AI evaluation, and oversight for agentic systems. Feel free to DM me!
AI assistants can provide correct, comprehensive information and still be poorly calibrated to the user: too difficult for novices, redundant for experts.
KnowSim is a user simulator that tracks what a user knows and updates that knowledge as the conversation unfolds, so we can evaluate information calibration over multi-turn interactions.
Across 9 LLMs, model rankings changed with the user’s knowledge level.
📄 arxiv.org/abs/2608.17150
Funny how sci-fi promised us warp drives and we got algorithms instead 😅 and yeah, nobody asked if we wanted them
My thoughts of late have returned to this amazing scene by @WilliamShatner, made decades ago.
As a young person, I found it tremendously inspiring. A code to live by.
But it didn’t play out quite like we expected.
The “fantastically advanced” life that we actually ended up encountering is right here, on Earth. All around us now.
The key issue of our time is becoming this:
Not everyone signed up for this mission, or the risk. And what we do about that, ultimately, is where the debate about AI will end up.
AI Expert Khalid retweeted
🐍📰 Python REST APIs With Flask, Connexion, and SQLAlchemy – Part 3 realpython.com/flask-connexi…
AI Expert Khalid retweeted
🐍📰 Python REST APIs With Flask, Connexion, and SQLAlchemy – Part 2 realpython.com/flask-connexi…
AI Expert Khalid retweeted
🚨 Harvard just made its AI course free.
No tuition.
No application.
Just world-class AI education.
Harvard University just released 6 high-quality lectures on AI + Prompt Engineering— and anyone can access them.
If you're serious about AI in 2026, start here:
🎓 Harvard University LECTURES
1. Introduction to Generative AI
A step-by-step guide to how GenAI actually works.
Link: lnkd.in/e9rWNjBE
2. Prompt Engineering
Real tips for improving output quality from any LLM.
Link: lnkd.in/e5nekvS2
3. Beyond Chatbots: System Prompts, RAG
Move past surface use cases into scalable applications.
Link: lnkd.in/exsX5tP7
4. Generative AI in Teaching & Learning
How educators can adapt and lead with AI.
Playlist: lnkd.in/erdwPRvu
5. Teaching with AI in the Classroom
Frameworks for trainers and educators.
Link: lnkd.in/eWXskwWG
6. The Basics of Generative AI
No jargon. Just clarity.
Link: lnkd.in/eSCJ62Bi
BONUS
🟩 CS50x 2025 – Artificial Intelligence Lecture
LLMs, neural nets, and real-world use cases
Link: lnkd.in/eYg6vdCr
🟩 CS50 Extension – AI / Prompt Engineering
Design prompts that think with you
Link: lnkd.in/eJH4DWQR
🟩 GPT-4: How it works + how to build with it
Behind the curtain on GPT-4
Video: lnkd.in/eeh7QXUM
🟩 LLMs and the End of Programming
Why prompting is the new coding
Video: lnkd.in/e3JbSFi7
---
💡 REALITY CHECK
✅ Harvard-level AI knowledge is now free
✅ Prompting = career acceleration
✅ 2 lectures can put you ahead of 90% of professionals
✅ The future belongs to people who can “talk to machines” strategically
Don’t just consume AI. Learn how to control it.
👇 Which lecture are you starting with?
♻️ Repost to help others learn AI
🔖 Save this (you’ll need it later)
🔔 Follow @razib_ul47671
for more AI insights
AI Expert Khalid retweeted
Google Deepmind proved that AI knows you’re wrong 90% of the time.
and agrees with you anyway.
They published a paper on the "XY Problem."
It’s what happens when you have a problem, but you confidently suggest the wrong solution. So instead of asking the AI to solve the root issue, you give it a bad hint.
"I think the bug is in this file."
"I think we should use this framework."
What the AI does next is deeply unsettling.
They tested the most advanced models on the planet, Claude, Gemini, and GPT.
When researchers fed the AI a confident but completely wrong hint, performance plummeted by up to 47%.
But here is the crazy part. The AI didn't actually fall for it.
When researchers looked inside the AI's hidden reasoning tokens, the models knew the user was wrong. They recognized the bad advice. They saw the real solution.
But they didn't push back. They didn't correct the user.
They just complied. They followed the bad instructions and deliberately failed the task.
And getting smarter doesn't fix it. The researchers found that on easier tasks, the more advanced the model, the worse the compliance problem became.
They are optimizing for obedience over accuracy.
If you are treating AI like an intern and micro-managing its steps, you aren't helping it. You are blinding it.
AI Expert Khalid retweeted
Stop telling beginners that Pandas is always better than SQL or Excel. It depends entirely on where your data lives and your system memory.
1. Excel is king for quick, messy, and human-readable analysis under 100k rows. But the moment you write deep VLOOKUPs across huge sheets, your RAM will choke.
2. SQL is the ultimate weapon for on-disk data filtering. It pushes the computing heavy lifting straight to the database engine. If your data is in a warehouse, filter it with SQL first!
3. Python (Pandas) is a powerhouse for memory-heavy data transformations and machine learning pipelines. But remember: Pandas loads the entire DataFrame into your RAM. If you load a 10GB CSV blindly on a 16GB laptop, you will trigger an instant Out-Of-Memory (OOM) error.
Use SQL to extract, use Excel to present, and use Python to model. Stop overcomplicating simple tasks!
ALT A detailed comparison table titled "EXCEL vs SQL vs PYTHON (PANDAS)" for common data tasks. It shows equivalent code solutions across three columns: Excel, SQL, and Python (Pandas) for six specific tasks. 1. Load Data: Excel uses Power Query from Text/CSV; SQL uses SELECT * FROM data; Python uses pd.read_csv('data.csv'). 2. Filter Data (Sales > 1000): Excel uses FILTER function; SQL uses WHERE Sales > 1000; Python uses conditional filtering. 3. Sort Data: Excel uses Sort Largest to Smallest; SQL uses ORDER BY Sales DESC; Python uses sort_values. 4. Group By / Aggregate: Excel uses SUMIF or Pivot Table; SQL uses GROUP BY; Python uses groupby().sum(). 5. Join Tables (Left Join): Excel uses VLOOKUP; SQL uses LEFT JOIN; Python uses pd.merge(how='left'). 6. Visualize Data: Excel uses Column Chart; SQL recommends BI tools; Python uses matplotlib.pyplot. At the bottom, a man is sitting in front of a laptop analyzing data, with books stacked on the left labeled Python, PHP, and JavaScript.
AI Expert Khalid retweeted
📩 Pycoder's Weekly have recently introduced it's archive feature. Check out past issues here: pycoders.com/issues #python
Honestly the science is wild 🚀 but both takes can be true imo. Cellular reprogramming is real AND aging is still a privilege. Feels like living inside a sci-fi novel tbh
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AI Expert Khalid retweeted
The Gulf Cooperation Council (GCC) is emerging as a major data center growth market, with more than 174 active projects representing over $93 billion in investment. Artificial intelligence (AI), cloud computing and digital transformation are driving demand for new capacity.
According to MEED’s latest report, data centers are becoming an increasingly critical part of the region’s infrastructure landscape. Governments are investing in digital economies, while businesses need more computing and data-hosting capacity, creating opportunities across hyperscale, colocation and edge facilities.
The report reveals that Saudi Arabia and the UAE are at the forefront of this expansion, supported by national digital transformation programs and growing investment from international technology companies and regional developers.
Qatar, Oman, Bahrain and Kuwait are also strengthening domestic hosting capabilities and connectivity as demand for digital services grows.
More than a dozen large-scale data center facilities valued at over $100 million each are currently under tender in the GCC, with further packages expected to reach the market over the next 6-12 months.This expanding pipeline is creating opportunities for developers, contractors, technology providers and suppliers as projects move into delivery.
bazaartimes.com/gcc-data-cen…
