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PAHBSE class 12 English(CORE) Question Paper session 2024-25 Set A
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#padhaipoori #padhaipooriclass12 #hbsequestionpaper #hbse #ppinseconds
@padhaipoori
#Coreset Algorithm Paper
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SA🖥️ UGC NET Paper-2 Computer Science – Important Notes 📚
Struggling with theories, algorithms, or tricky PYQs?
Don’t worry — I’ve simplified the most important topics into clear, easy-to-understand notes! 🚀
Perfect for quick revision and smart preparation.
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@sameera.fernaz
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OF❤️ art ❤️Algorithm hack
peepar air plane ✈️ 🎤🎸Content strategy
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@official_aritest
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STJust a message to all my students stay safe out there #chatgpt #college #essay #professor #gptzero
@studyingwithjake
104.8K
PAMeta just released a new AI research paper for VL-JEPA - joint embedding predictive architecture for vision language. Could this be the beginning of the end for LLMs? #ai #tech #education #fyp #research
@parthknowsai
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ITAI algorithm writing paper
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#technology #ai #machinelearning #innovation #robotics #chatgpt #
@itsatechpage
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MU…by way of paper
Taxed from @severum_perspective
@muricans_only
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AVDay 14 of my 50 days of GenAI challenge.
Over the last few days, we built the core components of retrieval systems:
• Embeddings
• Cosine similarity
• Semantic search
• Chunking
• Vector databases
Today, we combined them into a complete RAG pipeline.
The architecture is simple:
Extract text from a document
Split it into overlapping chunks
Generate embeddings for each chunk
Store them in a vector database
Retrieve relevant chunks at query time
Send retrieved context to the LLM
This allows the model to answer questions grounded in your own data — without retraining.
Any PDF can become searchable:
• Resume
• Research paper
• Internal documentation
• Product manuals
This is the foundation of modern enterprise AI systems.
[genai, rag pipeline, pdf rag, document retrieval, chunking strategy, chromadb, embedding pipeline, enterprise ai]
#GenAI #RAG #LLMEngineering #VectorDatabase #AIDevelopment
@average.yash
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DAApple just dropped a bomb on the AI world — and no one’s talking about it.
They released a paper called “The Illusion of Thinking” —
basically saying that all these reasoning models like Claude, Gemini, and GPT?
They’re not reasoning. They’re just memorizing.
To prove it, Apple built three puzzle levels.
Easy? The models crushed it.
Medium? They started to wobble.
Hard? They completely collapsed.
And here’s the kicker — even when Apple gave them the actual solution algorithms, they still failed.
One model did over 100 steps in Tower of Hanoi…
but couldn’t handle 4 moves in a river crossing puzzle.
Why?
Because one was in the training data. The other wasn’t.
This paper doesn’t just poke holes —
it blows open the idea that AI is really thinking.
And for now, AGI? Still a distant dream.
What do you think? Let me know in the comments
#ai #chatgpt #apple
@davi.d_roberts
899.0K
PAA recent paper by scientists from openAI and Apollo research shows that AI models are deliberately lying and deceiving us. #ai #tech #education #science #research #learn #fyp
@parthknowsai
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_DAlgorithm Art
#algorithmicart #engineeringporn #bluepen
@_draw_scape
19.9K
THNot financial advice. Here are my backtest results (all net of costs, 3 yr rolling walk forward out of sample with purged and embargoed tuning, and t+1 execution):
2020: 12.16% CAGR, 13.17% Max DD, 1.09 Sharpe, 4205 trades
2021: 16.33% CAGR, 9.17% Max DD, 1.39 Sharpe, 3329 trades
2022: 13.02% CAGR, 8.99% Max DD, 1.35 Sharpe, 3449 trades
2023: 14.22% CAGR, 8.79% Max DD, 1.42 Sharpe, 3161 trades
2024: 11.45% CAGR, 9.64% Max DD, 1.27 Sharpe, 3798 trades
Research preview only. Past performance is not indicative of future results.
#quant #math
@thedanieljeong
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