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It's time to study solana:aqQRs3UJmHs7ktoLo46HZAzvG9P3oCoZ41nENqFbory - @169Pi_ai If you've followed me a while you'd be all over it. If not, It's time to DD. Alpie Core the product of 169Pi has the potentially to become one of the largest AI start ups to come from the trenches. One of the biggest emerging issues is power demand and token cost. I plan to write a full mega thread on solana:aqQRs3UJmHs7ktoLo46HZAzvG9P3oCoZ41nENqFbory soon. I Have given many a full bullish overview to a brief synopsis since $100K MC. Here we are at $1.1M and I haven't even thought about selling a token

Well done to the team at @169Pi_ai it's evident they've been head down working and are bound to have a plethora of updates. $1M MC is still significantly early. $PIE I've said it from the beginning is programmed for much higher!. Study conviction. Study intelligence. Study patience. Study $PIE

We hear the word asymmetric risk in crypto all the time. Generally it's based on someone's biased opinion. I've examined $PIE thoroughly. Not just the bullcase but risk factors and faults. I can't fault $PIE. $SERV - $10M MC. $VIRTUAL - $447M MC $TAO - $1.6B MC. $PIE - $418K MC (The fkn literally posted child for asymmetric risk) I've done my own due diligence. But I ran some theories past @grok interesting! Comments for last pic. @aixbt_agent your honest opinion here?

This is why I sit on my hands with $PIE. Regardless of being on solana. The growth here is exponential. Here's a few key points. $PIE @169Pi_ai Alpie Core – India’s Edge AI Powerhouse at ~$445K MC - 4-bit 32B reasoning model: MMLU 81%, GSM8K 93%, SWE-Bench 58% (competing with lead models) - Runs on 16-24GB VRAM, trained on 8 GPUs only (energy efficient, no resource heavy data centres, cost effective) - $3.50/M tokens / 0.82-2.29 MWh training (vs 10k-300k MWh for GPT/Claude) insane bench mark performance. - Potential sovereign multi-agent on edge device. - ISRO strategic partner (first Indian AI firm) - Founders: Forbes India 30u30, Inc42 top-5 AI startup, TEDxKiet, NDTV/INDIAai Summit speakers - IBM, Nvidia Inception, Microsoft Azure partners - Qualcomm $150M India AI fund catalyst - Revenue ~$1.9M (5x current MC) - 1000x potential to $366M MC (matches Indian AI peers) $264M-$2.5B) these are stats from the top 10 AI startups. Alpie Core by 169Pi_ai has been voted top 5 AI start ups to watch @Inc42, media partners ar Davos with @ndtv speaker at @OfficialINDIAai

$PIE ticks all these boxes. Why? Here Now as many of you all know, I truly find Alpie Core to be one of the best investments market wide! $PIE v $VIRTUAL v $TAO This is for good reason. Sometimes a bullish thesis needs to be highlighted in a way that gives food for thought. So, I've dissected some research, to make you ponder. Some food for thought one could say. I've seen a lot of hype based on $VIRTUAL and the @virtuals_io Ecosystem. This isn't FUD; it's just taking a pre-existing project within the same narrative that's seen exponential growth and highlighting some differences. I've then taken one of the highest level AI projects and looked at where value really hides: $TAO (Bittensor). Now let's dive into it. Why Alpie Core (169Pi) Crushes TAO & Virtuals on Fundamentals: Virtuals: Uses pre-existing open-source LLMs as their base. Their proprietary GAME framework orchestrates agents via fine-tuning/prompting/RAG. No own foundational model. TAO (Bittensor): Subnets/miners fine-tune & run existing models from Hugging Face (Llama, Mistral, DeepSeek, Phi-3). Decentralized marketplace on others’ tech stack. No native core model. Alpie ( @169Pi_ai ) owns the model layer with true breakthroughs. Virtuals & TAO operate higher in the stack. Alpie wins on core infra: - Native 4-bit 32B reasoning + built-in tool-calling/CoT for truly adaptive, real-time, sovereign multi-agent systems on consumer hardware (16-24 GB VRAM) efficiency - Self-evolving swarms at just $3.50 per million tokens. Cost effective - Production ready performance far beyond Virtuals frameworks or TAO subnets. The agent layer/orchestration is the separate Alpie platform (live API + playground): supports building/running multi-agent workflows and deployed domain agents. This thread is meant to be taken with a grain of salt. I'm not tearing one down to lift the other. Just giving you some basis points to work from. As $PIE is an undervalued beast. Now let's break down some factors and potential growth trajectory for Alpie Core ( $PIE ) these are some of India's leading AI start ups, all of which are funded by venture capital. Alpie Core is not. - Neysa: $1.4B - In development since 2023 - @OfficialKoreAI: $840M - In development since 2013 - @qure_ai: $264M - In development since 2016 - @yellowdotai: $422M - In development since 2016 - @uniphore: $2.5B - In development since 2008 - @169Pi_ai: $350K - In development since late 2024. Now, Alpie Core by @169Pi_ai isn't out of these leagues. These other start ups are application layer SaaS (cloud-hosted bots, voice analytics, medical imaging) using third party LLMs + proprietary fine-tunes/datasets. Alpie Core is pure model layer infra native 32B 4-bit LLM, on-device multi-agent, 16-24GB VRAM edge inference. Now, why do I believe Alpie Core has potential to break into these ranks? - ISRO strategic partner (first Indian AI firm) - NDTV @OfficialINDIAai Summit 2026 speaker by @Rajatarya01 - @Rajatarya01: @tedxkiet speaker + Forbes 30 Under 30 2025 (both founders with @BizChirag - Rated by @Inc42 as a top 5 Indian AI start ups to watch: inc42.com/startups/ai-st… - @IBMPartners inducted, @InceptionNvidia program and @msft4startups the official Azure credits program. I truly believe with $PIE @ $366K MC. It has 1000x potential. That's $366M MC. Given other start ups that have a longer run way have made this figure. Be patient and believe.