I grew up watching John Cena and my childhood revolved around his matches. Though my WWE craze faded with time, my respect for him never did. He is probably the only celebrity who follows back a million people. A true champ in and out of the ring. BE HUMBLE! Thanks @johncena🫡🫡 #NeverGiveUp #RiseAboveHate

We need to settle this. You have to fight , and you have to choose your opponent. a) One horse-sized duck b) One hundred duck-sized horses There are no other options. You're in an open field. You got one baseball bat. I've heard serious, passionate arguments for both sides. What's your choice, and what's your strategy???

Grok Imagine just rebooted my childhood in 4K neon 😎 @elonmusk is this cool or not??

Grok imagine✨💫

My first X payout just landed. Here's a transparency report: • Impressions: 10,000,000 + • Payout: $39.63 It’s $39.63, and I'm incredibly grateful to this entire community for every single like, reply, and repost that made it possible. Honestly, I was expecting more for that level of reach, and it’s a bit demotivating. It shows the huge gap between total impressions and monetizable verified impressions. This first step is the most important one. It motivates me to double my hard work and keep creating the best System Design content I can for you all. But I don't believe in algorithms; I believe in hard work. This just motivates me to double down. This is v0.1 . Surely one day we'll push a 4 or 5-digit release! Thank you for supporting the build. 🙏 #XMonetization #Transparency #SystemDesign #Developer

Got my first X payout today. And if I'm being completely honest, I'm feeling pretty broken and confused. I've worked incredibly hard to hit 10M impressions this period and am so grateful for all the engagement. But seeing a payout of $39.63 for that level of reach is just... tough. I know I'm supposed to just be thankful, but it's left me feeling really sad and demotivated. For other creators, is this normal for this many impressions? I don't get the algorithm. I just believe in hard work, and this feels like a gut punch. Thanks @SebsterSpeaks @CreeCoder for helping me. Literally i am feeling sad.😔😞

This video kinda captures all the foundational AI Papers 1. Attention Is All You Need (2017) - Transformer architecture with self-attention for parallel training; foundation of all modern LLMs​ 2. GPT-3 (2020) - Demonstrated in-context learning at scale; models can learn tasks from prompts without fine-tuning​ 3. InstructGPT (2022) - RLHF alignment technique; smaller aligned models outperform larger unaligned ones​ 4. LoRA (2021) - Low-rank adapters for efficient fine-tuning; 10,000x fewer parameters, enables single-GPU training​ 5. RAG (2020) - Retrieval-Augmented Generation; models access external data to reduce hallucination and outdated knowledge​ 6. LLM-Based Agents Survey (2023) - Framework for AI agents with brain (planning), perception (context), and action (tools) components​ 7. Switch Transformers (2021) - Mixture of Experts architecture; trillion-parameter models with sparse activation for efficiency​ 8. DistilBERT (2019) - Knowledge distillation for compression; 40% smaller, 60% faster, 97% performance retention​ 9. LLM.int8() (2022) - Outlier-aware quantization; halves memory with 8-bit storage while preserving accuracy​ 10. Model Context Protocol (2024) - Anthropic's open standard for connecting models to tools, databases, and APIs seamlessly Just Google them and get everything on Arxiv :)

npm i dreams npm i tomorrow npm i everything we once drew on whiteboards Each line a whisper to the machine build this world with me. And somewhere between install and deploy, creation turns human again.

Percentages on a screen, but beneath them stories. Hands waiting for work, eyes searching for a chance. A graph can’t capture the ache of waiting or the relief of a call back. Nations rise and fall by how they treat those left waiting at the gates of opportunity.

Yeah, pain’s the best teacher. Nobody learns from comfort. You touch the fire once, and you remember forever. That’s how people grow not through talks or books, but through bruises. You either run from it or take the hit and adapt. Hurt speeds up education.

The ring becomes memory, the crowd becomes thunder. Cena stands where time pauses, where cheers turn into gratitude. The “Last Time is Now” isn’t farewell it’s a heartbeat saying thank you. For every kid who once whispered “never give up,” this is the echo of their childhood returning for one final roar.

You can almost hear the silence that follows healing. People who fed on your pain will call your peace rebellion. They’ll act confused when you stop explaining yourself. But healing changes the gravity around you; it pulls away what was never meant to stay. Strength always exposes comfort built on your suffering. Freedom has a sound, and it’s not loud it’s steady.

“What if tomorrow’s headlines were written by algorithms, not editors?” That’s the quiet disruption behind AI-powered newsroom workflows and Java sits at the core of it. You need to first understand what an AI newsroom workflow really means. It’s a modular system that ingests data, writes drafts, curates images, and publishes stories automatically, responsibly, and at lightning speed. It helps with → Real-time news generation and updates → Fact-checking through AI and NLP pipelines → Personalized feeds for every reader It runs on structured policies: editorial oversight, ethical AI filters, content traceability, and source transparency. Using Java, engineers design these workflows with Spring Boot microservices, connect pipelines through Kafka, run NLP models via TensorFlow Java API, orchestrate tasks in Camunda, and store outputs in Elasticsearch for instant search. Each service handles a phase from scraping to summarization to publishing with clear boundaries and audit trails. Responsibilities of an AI Newsroom System → Ingest, analyze, and summarize large data streams → Maintain human review loops before publishing → Scale global content delivery without bias or drift Keep these in mind and you can explain how Java powers the invisible newsroom where speed meets editorial integrity. ➕ Follow me, @kisalay_Cool95 , for Tech, AI & Career Insights ♻️ Reshare to help others take action.

“What if influence could be measured, not just felt?” That’s the silent math behind influencer analytics platforms and Java quietly keeps it running. You need to first understand what an influencer analytics backend really means. It’s a data engine that tracks engagement, reach, and sentiment across platforms turning likes into insight and patterns into prediction. It helps with → Campaign ROI and audience authenticity → Real-time engagement dashboards → Fraud detection through behavioral analysis It operates on strict principles: verified metrics, deduplication, privacy compliance, and anomaly scoring. Using Java, engineers build data pipelines with Spring Boot microservices, stream metrics through Kafka, run aggregations in Flink or Spark, and store results in ClickHouse or PostgreSQL. Sentiment analysis hooks into TensorFlow Java API, while Redis handles leaderboard caching. APIs expose insights securely via gRPC or REST. Responsibilities of an Analytics Backend → Collect and clean data from social platforms → Detect fake engagement and bot clusters → Deliver real-time insights to brands and creators Keep these in view and you can clearly explain how Java powers the unseen intelligence behind digital influence. ➕ Follow me, @kisalay_Cool95 , for Tech, AI & Career Insights ♻️ Reshare to help others take action.

“What if safety scaled faster than the internet itself?” Some days it feels impossible. Too much content. Too little time. That’s why distributed content moderation matters. And yes, Java can carry it. It’s a system that ingests posts in real time, scores risk, applies policy, and loops humans in when it’s messy. Fast. Consistent. Traceable. It helps with → Real time abuse detection at global scale → Policy enforcement without hurting reach → Full audit trails for appeals and regulators It runs on rules and judgment. Signatures for the obvious. ML for the gray. Humans for the hard edge cases. Using Java, teams wire Spring Boot microservices, stream events through Kafka, run online scoring with Flink, and use TensorFlow Java API for models. Drools handles policy logic. Redis caches verdicts. Elasticsearch/OpenSearch powers audits and search. gRPC connects services. WORM or append only storage preserves evidence. PII gets masked. Every decision is explainable. Responsibilities of a Moderation Platform → Ingest, normalize, and classify content in milliseconds → Apply policy with versioned rules and safe rollouts → Escalate to reviewers with context and timelines Quiet truth. Good moderation feels invisible because it works before you notice. ➕ Follow me, @kisalay_Cool95 , for Tech, AI & Career Insights ♻️ Reshare to help others take action.

“What if social media could govern itself responsibly at scale?” That’s the quiet challenge behind compliance and governance for social platforms and Java often runs the backbone of it. You need to first understand what compliance and governance systems really mean. They’re the silent frameworks ensuring content, privacy, and moderation follow laws and internal ethics without breaking the flow of conversation. It helps with → Data privacy and consent management → Policy enforcement across global regions → Real-time compliance audits and traceability It operates under tight principles: accountability, transparency, explainability, and lawful data retention. Using Java, teams build these systems with Spring Boot microservices, Kafka for compliance events, Drools for policy enforcement, and Camunda for regulatory workflows. ElasticSearch stores immutable audit logs, Keycloak manages identity and consent, while JCA/JCE secures user data. APIs sync with regulators and internal tools for instant review and reporting. Responsibilities of a Compliance Framework → Track policy violations and generate evidence trails → Automate regulatory reporting across jurisdictions → Protect user rights through encryption and audit readiness Keep these in view and you can explain how Java silently upholds digital democracy where freedom meets accountability. ➕ Follow me, @kisalay_Cool95 , for Tech, AI & Career Insights ♻️ Reshare to help others take action.