dazaink

Builder, software developer, technologist, artist, data scientist, ML/AI engineer, blockchain enthusiast

[dazaink @Dazaink]

https://t.co/ZHYTmyybPg

[dazaink @Dazaink]

7 Best Business English Books for Professionals (2026 Guide) https://t.co/iC2T6XGgnp

[dazaink @Dazaink]

@dcorperation @Ksaynak16 While you hold.

[dazaink @Dazaink]

@LucieSHIB Where are the deliverables?

[dazaink @Dazaink]

@LucieSHIB $SHIB will take over Bitcoin and go an independent path

[dazaink @Dazaink]

@darshal_ Send

[Darshal Jaitwar @darshal_]

I'm deleting this soon because it's a legit cash-printing formula.

𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 3)

1. Artificial Intelligence + Data Analyst
2. Machine Learning + Data Science
3. Cloud Computing + Web Development
4. Ethical Hacking + Hacking
5. Data Analytics + DSA
6. AWS Certified + IBM COURSE
7. Data Science + Deep Learning
8. BIG DATA + SQL COMPLETE COURSE
9. Python + OTHERS
10 MBA + HANDWRITTEN NOTES

(72 Hours only ) Cost About - $500

To get: -

1. Follow (So I can DM you )
2. Like & retweet
3. Reply " Send "

[dazaink @Dazaink]

@brandedkamina56 @SHIBCRACKc 2032

[Kshitij Mishra | AI & Tech @DAIEvolutionHub]

Best GitHub Repos to Learn AI From Scratch in 2026:

1. Andrej Karpathy – Neural Networks: Zero to Hero
https://t.co/8wrukS6Vqm

2. Hugging Face Transformers
https://t.co/AtyDLv7NXI

3. FastAI/fastb
https://t.co/DsmaVa0WuT

4. Made-With-ML
https://t.co/bIlKIjWN9J

5. ML System Design
https://t.co/8mgOFAZCQD

6. Awesome Generative AI guide(
https://t.co/AmuUmfvJTD

7. Dive into Deep Learning
https://t.co/ntRDPNjOFr

[Tech with Mak @techNmak]

RAG has evolved far beyond its original form.

When people hear Retrieval-Augmented Generation (RAG), they often think of the classic setup: retrieve documents → feed into LLM → generate an answer.

But in practice, RAG has branched into many specialized patterns, each designed to solve different challenges around accuracy, latency, compliance, and context.

Here are some of the most important categories:
➤ Standard RAG - the original retrieval + generation (RAG-Sequence, RAG-Token).

➤ Graph RAG - connects LLMs with knowledge graphs for structured reasoning.

➤ Memory-Augmented RAG - external memory for long-term context.

➤ Multi-Modal RAG - retrieves across text, images, audio, video.

➤ Streaming RAG - real-time retrieval for live data (tickers, logs).

➤ ODQA RAG - open-domain QA, one of the earliest and most popular uses.

➤ Domain-Specific RAG - tailored retrieval for legal, healthcare, or finance.

➤ Hybrid RAG - combines dense + sparse retrieval for higher recall.

➤ Self-RAG - lets the model reflect and refine before final output (Meta AI, 2023).

➤ HyDE (Hypothetical Document Embeddings) - improves retrieval by first generating “mock” documents to embed.

➤ Recursive / Multi-Step RAG - multi-hop retrieval + reasoning chains.

Others like Agentic RAG, Modular RAG, Knowledge-Enhanced RAG, Contextual RAG are best thought of as system design patterns, not strict categories, but useful extensions for specific use cases.

The image below maps out 16 different types of RAG, their features, benefits, applications, and tooling examples.

Whether you’re building production-grade assistants, domain-specific copilots, or real-time monitoring systems, the right flavor of RAG can make all the difference.

[Alex Prompter @alex_prompter]

R.I.P. basic prompting.

MIT just dropped a technique that makes ChatGPT reason like a team of experts instead of one overconfident intern.

It’s called “Recursive Meta-Cognition” and it outperforms standard prompts by 110%.

Here’s the prompt (and why this changes everything) 👇

[dazaink @Dazaink]

@RealBossShib @SABOTAGE_604 @69onShibarium @Shibtoken So is it over? I own plots of land too lol gawd we got had, where the fuck are the deliverables!? Leash is over? Where is the utility? There never was a project was there? Scam thru and thru

[Akshay 🚀 @akshay_pachaar]

LLM fine-tuning techniques I'd learn if I were to customize them:

Bookmark this.

1. LoRA
2. QLoRA
3. Prefix Tuning
4. Adapter Tuning
5. Instruction Tuning
6. P-Tuning
7. BitFit
8. Soft Prompts
9. RLHF
10. RLAIF
11. DPO (Direct Preference Optimization)
12. GRPO (Group Relative Policy Optimization)
13. RLAIF (RL with AI Feedback)
14. Multi-Task Fine-Tuning
15. Federated Fine-Tuning

My favourite is GRPO for building reasoning models. What about you?

I've shared my full tutorial on GRPO in the replies.

[Tech with Mak @techNmak]

This isn't just a bookshelf, it’s a $300k/year survival kit.

[dazaink @Dazaink]

Look how much I learned on Duolingo in 2025! How did you do? #Duolingo365

[Reuters @Reuters]

A group of Peruvian shamans gathered on a beach in southern Lima to perform their annual New Year ritual, delivering predictions for 2026 that included the fall of Venezuelan President Nicolas Maduro and a serious illness for US President Donald Trump https://t.co/3k94IDkmgj

[dazaink @Dazaink]

@topColoradoTop Where in Colorado