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Thread đ§ľ: Why $PHA, $AR, $AKT are not just old projects⌠but future AI infra giants
OG infra plays with REAL hardware networks the kind that can quietly do 10xâ50x in the AI cycleđđ
1/
Everyone is chasing the next shiny AI tokenâŚ
But few are paying attention to the projects that have quietly spent 5+ years building real infrastructure.
â Phala Network
â Akash Network
â Arweave
These arenât narratives.
These are foundations.
2/
AI is not just software.
AI =
⢠Compute (GPUs)
⢠Storage (data)
⢠Secure execution
And guess what?
These 3 OGs dominate each layer:
â˘Akash â Compute marketplace (GPU power)
â˘Arweave â Permanent data storage
â˘Phala â Confidential AI execution
Thatâs the full stack.
3/
Letâs start with @akashnet đ
Akash is basically:
đ âAirbnb for GPUsâ
â˘Anyone can rent or provide compute
â˘Prices set via open marketplace (not corporations)
â˘Up to ~80% cheaper vs AWS/Google Cloud
It already supports AI workloads, LLMs, inference, training
As AI demand explodes â GPU scarcity becomes real.
Akash wins here.
4/
Now @onlyarweave đ
AI runs on data.
And data needs:
â permanence
â censorship resistance
â reliability
Arweave solves this with permanent storage (pay once, store forever)
In a world of:
⢠AI datasets
⢠model weights
⢠on-chain knowledge
Storage = gold.
5/
Now the most underrated piece: @PhalaNetwork đ
Phala is solving a massive problem:
đ âHow do you run AI without leaking data?â
â˘Uses Trusted Execution Environments (TEE)
â˘Enables private + verifiable AI computation
â˘Even the cloud provider canât see your data
This is HUGE for:
⢠enterprises
⢠finance
⢠personal AI agents
6/
Now connect the dots đ§
AI stack (decentralized version):
â˘Compute â Akash
â˘Storage â Arweave
â˘Execution/Privacy â Phala
This is literally a Web3 alternative to AWS + OpenAI + Google Cloud combined
But decentralized.
7/
Why these OGs have an edge over new projects:
1. Hardware network takes YEARS to build
You can fork code.
You canât fake:
⢠GPU supply networks
⢠storage nodes
⢠real infra distribution
Akash already has live providers & GPU clusters
Phala runs on TEE-enabled hardware globally
These arenât ideas â theyâre deployed systems.
8/
2. Battle-tested through multiple cycles
Most new AI tokens =
đ narrative first, product later
These guys survived:
⢠2018 bear
⢠2022 collapse
⢠low attention cycles
And kept building.
Thatâs rare.
9/
3. Real economic activity
â˘Akash â active compute marketplace
â˘Phala â processing AI workloads + tokens daily
â˘Arweave â storing actual data permanently
Not just âpartnership announcementsâ
â actual usage.
10/
4. Positioned for AI explosion
AI growth =
â demand for GPUs
â demand for data storage
â demand for privacy
Centralized infra will struggle with:
⢠cost
⢠monopolies
⢠censorship
Decentralized infra becomes inevitable.
11/
Most people are still thinking:
âWhich AI coin will pump?â
Wrong question.
Better question:
đ âWho owns the rails AI will run on?â
12/
Final thought:
The biggest winners wonât be the loudest projectsâŚ
Theyâll be the ones quietly building:
⢠compute networks
⢠storage layers
⢠execution environments
for YEARS.
And when demand hits
theyâre already ready.
$PHA $AKT $AR = not hype plays
They are infrastructure bets
NFA