130.5K
TAJava thoda serious hai… par enterprise world ko aasaan banane ka kaam aaj bhi yahi karta hai.
Seekh lo, kaam aayega. ☕🔥
#Java #JavaDeveloper #Programming #BackendDev #CodeLife #LearnToCode #techcontent
@talkyobjects
#Java Virtual Machine Optimization
Mira videos de Reels sobre Java Virtual Machine Optimization de personas de todo el mundo.
Ver anónimamente sin iniciar sesión.
Reels en Tendencia
(12)
30.6K
CODid you know that Java behaves differently when comparing wrapper classes like Integer? 🤯
In this quiz, we test a simple line of code:
Integer a = 128;
Integer b = 128;
System.out.println(a == b);
Most beginners expect true, but the correct output is: ❌
👇 Watch the video to learn why Java outputs false here!
This happens because of Integer caching mechanism in Java — only values between -128 to 127 are cached. Anything outside that range creates a new object, so == compares references, not values. 🧠💡
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🎯 You'll Learn:
✔ Java wrapper class behavior
✔ Integer caching
✔ Difference between == and .equals()
✔ Common Java interview question
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💬 Comment below:
Did you get it right? 😎
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🔍 Keywords:
Java quiz, Integer caching, Java interview question, wrapper classes, Java comparison, Java coding challenge, Java beginner tips, Java programming trick
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📌 Hashtags:
#Java #JavaQuiz #CodingQuiz #ProgrammerLife #JavaInterview #JavaTips #CodingChallenge #LearnJava #DeveloperCommunity #ProgrammingFacts #JavaDeveloper #CodeSmart #SoftwareEngineer #TechLearning #programminghumor
@codewithprashantt
222.6K
COJava Developer → Agentic AI Engineer (Complete Roadmap)
Most Java devs stop at calling ChatGPT APIs.
That’s NOT Agentic AI.
Comment "Link" for the perfect resource to learn from Zero to Hero Agentic AI.
Here’s the real path 👇
1️⃣ Core Java stays (huge advantage)
Concurrency • Spring Boot • System Design
2️⃣ AI basics (no heavy math)
AI vs ML vs DL • LLMs • Transformers
3️⃣ Python (only what’s needed)
Scripts • NumPy • Pandas • Requests
4️⃣ LLM fundamentals
Tokens • Prompting • Context window • Hallucinations
5️⃣ Java + LLM integration
Spring Boot APIs • Streaming • Cost optimization
6️⃣ Agentic AI core
Goal → Plan → Act → Observe → Reflect
7️⃣ Tools & Memory (RAG)
Embeddings • Vector DBs • Knowledge retrieval
8️⃣ Agent frameworks
LangChain(Most Enterprise Ready) • AutoGen • CrewAI
9️⃣ Multi-agent systems
Manager • Worker • Critic agents
🔟 Production-ready AI
Guardrails • Monitoring • Security • Cost control
💡 Agentic AI = Distributed Systems + LLMs
💡 Java devs already know HALF of this
Save this 📌
Share with your Java gang ☕
Comment "Link" for the perfect resource to learn from Zero to Hero Agentic AI.
#systemdesign #engineers #developers #softwareengineering #genai
[coding, system design, agentic ai, genAI , developers, software engineer, coders, java]
@coding_with_deepa
5.0M
RIInstead ....
Become "THE" java developer 💪🔥🚀
Do save this reel before it's gone ✨
Learn advanced Java from the right guidance 👇!
1. Java Concurrency and Multithreading: ✨
- Online Course: Coursera's "Concurrency in Java" by University of Illinois
-📍YouTube Playlist: "Java Multithreading" by thenewboston
2. Java Design Patterns:✨
- Website: Refactoring Guru (refactoring.guru/design-patterns/java)
- 📍YouTube Playlist: "Design Patterns in Java" by Telusko
3. Java Memory Management:✨
- Article: "Understanding Java Garbage Collection" by Baeldung
- 📍YouTube Playlist: "Java Garbage Collection and Memory Management" by CodeAcademy
4. Java Performance Tuning:✨
- Blog: JavaPerformanceTuning.com
- 📍YouTube Playlist: "Java Performance Tuning Techniques" by CodeGym
5. Java Enterprise Edition (Java EE) / Jakarta EE:✨
- Online Course: Pluralsight's "Java EE: The Big Picture" by Reza Rahman
- 📍YouTube Playlist: "Jakarta EE Tutorials" by Java Brains
6. Java 9+ Modules (Project Jigsaw):✨
- 📍 YouTube Tutorial: "Java 9 Module System" on YouTube by Java Brains
7. Java Spring Framework:✨
- 📍YouTube Playlist: "Spring Framework Tutorials" by Telusko
8. Java Functional Programming:
- 📍YouTube Playlist: "Java Functional Programming" by CodeGym
#softwaredeveloper #javadeveloper #javacode #springboot #javaprogrammer #javaprograming
[ Java developers 2024 , advance java concepts, getting started with java programming, java resources ]
@rizdev.in
199.7K
NIComment "CODING" to get this Free, Open-source Alternative to Lovable and Bolt.
There is finally an open-source alternative to Lovable, Bolt, and Replit. It lets you build full-stack apps with your local AI models. And it is 100% free. Unlimited. Open-source.
No lock-in to big platforms. No constant worry about caps or prices. Perfect for developers and Indie builders who want control over their stack. Their data.
I recently tried it myself. Asked my local model to whip up a simple chat app. Took minutes. Felt like magic.
It is called Dyad AI. First, head to the Dyad AI website. Download the app for your OS. Install it fast.
Now two choices:
1. Hook it to LM Studio or Ollama. Run models like DeepSeek or Qwen right on your machine. Privacy? Check. Speed? Check. Offline work? You bet.
2. Or grab a free API key from OpenRouter. Use their models. Free limits are plenty generous.
Either path works. You get a full-stack builder like Lovable or Bolt. But no credit limits. No rate caps. No paywall surprises.
Think of it like this. Building apps locally is easier than biking to the store. Prototype fast. Iterate. Ship as many as you want. On your terms.
#boltai #Lovableai #opensourceai #dyadai #aicoding #vibecoding #Lmstudio #ollama #aitools #ainews #aiindia #aicommunity
@nick_saraev
43.6K
COJava just changed the game.
Virtual Threads in Java let you run millions of concurrent tasks without the heavy cost of traditional threads.
No complex async code.
No massive thread pools.
Just simple blocking code that scales like crazy.
Concurrency just became cheap and simple.
#Java #VirtualThreads #Java21 #Concurrency #BackendEngineering SystemDesign JavaDevelopers
@codewithupasana
879.1K
CHHandling 1 Million RPS isn’t about code — it’s about smart architecture.
1️⃣ Traffic Distribution (Load Balancers)
➡️ Spreads incoming requests across many servers so nothing overloads.
Example: 1M requests split across 200 servers = ~5K requests per server.
⸻
2️⃣ Scale Out, Not Up (Horizontal Scaling)
➡️ Add more machines instead of making one server bigger.
Example: Flash sale traffic? Instantly launch 50 new API instances.
⸻
3️⃣ Fast Reads with Cache
➡️ Use Redis/Memcached to avoid hitting the database every time.
Example: Cached user data = millions of DB calls saved daily.
⸻
4️⃣ Edge Delivery with CDN
➡️ Static content loads from servers closest to the user.
Example: Users in Delhi fetch images from a Delhi CDN node.
⸻
5️⃣ Background Work with Queues
➡️ Heavy tasks run asynchronously so APIs respond instantly.
Example: Payment succeeds now, email receipt sent in background.
⸻
6️⃣ Split the Database (Sharding)
➡️ Divide data across multiple databases to handle scale.
Example: Usernames A–M on one shard, N–Z on another.
⸻
7️⃣ Rate Limiting
➡️ Prevent abuse and traffic spikes from taking the system down.
Example: Limit clients to 100 requests/sec to block bots from killing the API.
⸻
8️⃣ Lightweights Payloads
➡️ Smaller payloads = faster responses + less bandwidth.
Example: Send only required fields instead of massive JSON blobs.
Please follow for more such videos🙏
#systemdesign #softwaredevelopers #programming #tech #interview
[API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]
@chhavi_maheshwari_
137.2K
CYTop Virtual Machine Softwares Every Hacker Must Know 🔥🫡
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Follow @cybersecurityminds to get unlimited cybersecurity & hacking info 🤓
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#cybersecurity #darkweb #linuxuser #termuxhacking #kalilinuxtools #operatingsystem #cybersecurity #ethicalhacking #informationsecurity #learnhacking #kalilinux #pentesting #hackyourself #hackermindset #securityawareness #hacking101 #cybereducation #hackertools #whitehat #blackhat #hacker #mindset #virtualmachines #virtualbox #devoloper #ethicalhacker #virtualmachine
@cybersecurityminds
51.5K
ITBuilding automation workflows from scratch wastes days of your time.
Mapping logic. Testing connections. Debugging errors. Starting over when something breaks.
Most people accept this as part of automation but it doesn’t have to be.
Thousands of working workflows already exist. Free. Tested. Ready to use.
Over 7,000 n8n automation templates in one massive catalog.
Marketing sequences. AI agent workflows. Business processes. Engineering tasks. All built and documented by people solving real problems.
Each workflow comes complete. Ready-to-import files. Full documentation. Screenshots showing exactly what it does.
You don’t build from scratch. You browse. Download. Import. Done.
Most people spend a week building what they could clone in five minutes.
So if you want access to the site, comment ‘AUTOMATION’ below and I’ll send you the link directly.
#ai #automation #nocode #businessautomation #aiagents
@itsjamesmwild
257.4K
SAMaster Java in 30 Days with these resources 💯
Follow me , then comment “Java” and send this reel to my DM to get resources Link 🔗
https://drive.google.com/file/d/19HpNNcnwEGTkZn4irnCXA7QOzfPXdEQn/view?usp=sharing
{placements , jobs , internship, resume , java , roadmap , unemployment , layoffs , employment , it , technology , tech , computer , college , coding }
#internship #job #placements #resume #roadmap #java #python #layoffs #technology #coding #coding #dsa #college #employment #unemployment #layoffs
@sagar_mee_
45.5K
SITHIS is the ULTIMATE backend for vibecoding…
STOP USING SUPABASE
every time your AI wants to see your backend data… it has to make a tool call
that’s absolute bulls***
let me introduce you guys to… 🫡
#ai #chatgpt #coding #vibecoding #tech
@sina.growthtech
144.3K
ARIf you’re just getting into machine learning, this is the best place to start.
R2D3 is a free, interactive website that teaches you how machine learning works through animated visualizations. No equations upfront. No wall of theory. You scroll, and the model builds itself in front of you.
What the video couldn’t cover:
The site walks you through a decision tree, one of the most foundational algorithms in ML, using a real dataset of homes in San Francisco and New York. You watch the model draw boundaries on the data, test them, and adjust when they are wrong.
The concept it ends on is overfitting, what happens when a model learns the training data too well and fails on anything new. Seeing it visually is the moment a lot of things in ML suddenly click.
Built by Stephanie Yee and Tony Chu. Completely free, no sign-up required.
Link in the pinned comment.
#ai #artificialintelligence #technews #algorithm #fyp
@arnitly
✨ Guía de Descubrimiento #Java Virtual Machine Optimization
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Descubre el contenido más reciente de #Java Virtual Machine Optimization sin iniciar sesión. Los reels más impresionantes bajo esta etiqueta, especialmente de @rizdev.in, @chhavi_maheshwari_ and @sagar_mee_, están ganando atención masiva.
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