dan72ros
128.5K posts

dan72ros
@dan72ros
ideas, politics, religion and sometimes dark humor connected to life in Israel. Also, enjoys: steak, the beach https://t.co/delyZIvth5
Israel Beigetreten Ekim 2008
1.7K Folgt1.8K Follower

New Channel 12 poll: 56% of Israelis do not want Netanyahu to be the next PM, 36% want him the next PM. Netanyahu's coalition gets 51 seats, 57 for the opposition, 12 for the Joint Arab List mako.co.il/news-israel-el…

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@AmitSegal When then Sen Obama came to the kotel in 2009 ish he was torn apart as politicizing the wall
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8 types of LLMs used in AI agents 🤖
GPT • MoE • LRM • VLM • SLM • LAM • HRM • LCM
Different models for reasoning, perception, planning, and action — not just chat.
Agentic AI = model orchestration.
#AI #LLMs #AgenticAI #GenAI #MachineLearning

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Want to become a Claude Certified Architect in just 6 weeks?
Here’s a no-BS roadmap to go from learning → building → certified
Week 1 Foundations
→ Learn the core:
• Claude API
• Model Context Protocol (MCP)
• Claude Code
• Claude 101
Week 2 Build
→ Stop consuming. Start creating:
• Real projects with Claude Code
• Agent SDK + APIs
• MCP integrations
Week 3 Understand the Exam
→ Know the game before you play:
• 6 real-world scenarios
• 5 core domains
• Skills needed for each
Week 4 Practice Like a Pro
→ Build what actually matters:
• Multi-tool AI agents
• Team workflows with Claude Code
• Data pipelines + research agents
Week 5 Test Yourself
→ Take mock exams
→ Target 850+/1000
Week 6 Go Time
→ Attempt the real exam
→ One shot. Make it count.

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🧵 Day 7/30
Your app works with 10 servers.
What happens when you scale to 1,000 servers?
How do you distribute users/data evenly without chaos?
That’s where Consistent Hashing comes in.
What is Consistent Hashing?
It’s a technique used to distribute data across multiple servers efficiently.
Instead of assigning data randomly, both:
→ Servers → Keys (users, cache items, requests)
are placed on a logical hash ring.
Each key goes to nearest server.

Nitin.nn@NitinthisSide_
🧵 Day 6/30 — #SystemDesign Your database works fine… until users grow 100x. Then queries slow down, writes queue up, and one machine becomes the bottleneck. That’s where Database Sharding comes in. ⸻ What is Sharding? Sharding means splitting one large database into multiple smaller databases called shards. Instead of storing all users in one DB: → Shard 1 stores some users → Shard 2 stores others → Shard 3 stores others Data is distributed horizontally.
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