./ the power of local hosting
> real ownership
>> the model and the agent live with you, full control in your hands
> no api limits
>> no limits, runs when you want and as much as you want
> predictable costs
>> no hidden fees and no surprises, you know what you pay for
> https://t.co/3f0VOjjxaM
> real ownership
>> the model and the agent live with you, full control in your hands
> no api limits
>> no limits, runs when you want and as much as you want
> predictable costs
>> no hidden fees and no surprises, you know what you pay for
> https://t.co/3f0VOjjxaM
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# the ceiling vs the horizon
/ the vertical trap traditional cloud providers are fighting a losing war
building bigger datacenters leads to linear growth but ai demand is growing exponentially
we are hitting hard physical limits: power shortages, cooling bottlenecks and massive https://t.co/0Je0Jv6fVb
/ the vertical trap traditional cloud providers are fighting a losing war
building bigger datacenters leads to linear growth but ai demand is growing exponentially
we are hitting hard physical limits: power shortages, cooling bottlenecks and massive https://t.co/0Je0Jv6fVb
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./ problems that stop being problems with VeriLLM by @Gradient_HQ
> no trust in nodes, in a distributed net you can not know in advance if the node running inference is honest
> voting is weak, collusion between participants is possible
> full proofs are slow and expensive https://t.co/L37Jbwcv3v
> no trust in nodes, in a distributed net you can not know in advance if the node running inference is honest
> voting is weak, collusion between participants is possible
> full proofs are slow and expensive https://t.co/L37Jbwcv3v
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./ shift from permanent capex to distributed model
today AI growth hits a hardware cost
>> bigger models need bigger and more expensive data centers
>> result is high entry barrier/vendor lock/endless capital spend
distributed model takes another route and opens access:
> https://t.co/V9tvmKPSfP
today AI growth hits a hardware cost
>> bigger models need bigger and more expensive data centers
>> result is high entry barrier/vendor lock/endless capital spend
distributed model takes another route and opens access:
> https://t.co/V9tvmKPSfP
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heyyy my second contrast pfp pack for @Gradient_HQ community ❣️
./ grad lovers @BogartAso @lless_tes @Pascal2_22 @davidz9 https://t.co/hnqzDYPsXx
./ grad lovers @BogartAso @lless_tes @Pascal2_22 @davidz9 https://t.co/hnqzDYPsXx
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cash burn won’t equate to roi and it’s becoming a major pain point.
unsustainable capex coming in with bidding wars from the same pile of money slows overall growth adoption and causes dependency risks for founders.
whether it’s the cost of capex, the cost of fomo or the cost https://t.co/SOF6Ysp0xD
unsustainable capex coming in with bidding wars from the same pile of money slows overall growth adoption and causes dependency risks for founders.
whether it’s the cost of capex, the cost of fomo or the cost https://t.co/SOF6Ysp0xD
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./ how Echo by @Gradient_HQ speeds up AI research and makes it more efficient
> architecture
inference swarm and training swarm let you scale data generation and model training in parallel with no mutual blocking
> research acceleration
Echo cuts idle compute time and boosts https://t.co/GFfuXKDW2E
> architecture
inference swarm and training swarm let you scale data generation and model training in parallel with no mutual blocking
> research acceleration
Echo cuts idle compute time and boosts https://t.co/GFfuXKDW2E
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A good day to discuss a little bit about Parallax 🫶
Parallax: Distributed Intelligence 📗
Parallax is a key component of @Gradient_HQ concept for creating a decentralized artificial intelligence infrastructure. It rethinks the approach to servicing large language models, https://t.co/qgxiSQEWKe
Parallax: Distributed Intelligence 📗
Parallax is a key component of @Gradient_HQ concept for creating a decentralized artificial intelligence infrastructure. It rethinks the approach to servicing large language models, https://t.co/qgxiSQEWKe
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launching my first collection of contrast pfps for @Gradient_HQ community
they're fully crafted and
truly reflect the soul of project
❣️first models @realsirandrew @manuscripts666 @Leila1113514
./ looking back i’m amazed at how much i’ve leveled up my skill https://t.co/vGYnhBHTPE
they're fully crafted and
truly reflect the soul of project
❣️first models @realsirandrew @manuscripts666 @Leila1113514
./ looking back i’m amazed at how much i’ve leveled up my skill https://t.co/vGYnhBHTPE
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./ what is an AI that grows by itself?
most AI systems are not built for growth >>> load goes up/requests go up >>> problems start fast:
- services need to be moved
- architecture needs a rewrite
- clusters get added
- system stops for updates
end result >>> https://t.co/NxZYqOORy5
most AI systems are not built for growth >>> load goes up/requests go up >>> problems start fast:
- services need to be moved
- architecture needs a rewrite
- clusters get added
- system stops for updates
end result >>> https://t.co/NxZYqOORy5
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./ Parallax by @Gradient_HQ = win
> local compute for privacy and control
Parallax keeps your data and inference local and you own everything
> support for many open models
40+ open models ready to run
> scaling >>> turns everything into one cluster
connects normal devices into https://t.co/KrS8rD16n5
> local compute for privacy and control
Parallax keeps your data and inference local and you own everything
> support for many open models
40+ open models ready to run
> scaling >>> turns everything into one cluster
connects normal devices into https://t.co/KrS8rD16n5
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./ having powerful inference and training layers Echo and Parallax is big
but without a solid data channel it all loses meaning
this is where Lattica comes in linking all layers and giving safe scalable transfer of all kinds of data/trajectories/tokens
Lattica opens up:
> https://t.co/kTO312vwmN
but without a solid data channel it all loses meaning
this is where Lattica comes in linking all layers and giving safe scalable transfer of all kinds of data/trajectories/tokens
Lattica opens up:
> https://t.co/kTO312vwmN
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./ how Echo changes trends
and opens new moves thanks to splitting training and inference >>>
> time for experiments
splitting layers gives mad flex to test new RL setups and hybrid models
you can try new training strategies
> speed and stability
splitting layers lets you run https://t.co/0DwH3qF4HW
and opens new moves thanks to splitting training and inference >>>
> time for experiments
splitting layers gives mad flex to test new RL setups and hybrid models
you can try new training strategies
> speed and stability
splitting layers lets you run https://t.co/0DwH3qF4HW
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./ Power of Parallax in Open space
Open intelligence opens new dimensions of creation.
you build and ship when you want and how you want.
no cloud lock in/no subscriptions/no other peoples rules.
Control stays with you.
Parallax runs where compute already exists https://t.co/DbG4wYQPlF
Open intelligence opens new dimensions of creation.
you build and ship when you want and how you want.
no cloud lock in/no subscriptions/no other peoples rules.
Control stays with you.
Parallax runs where compute already exists https://t.co/DbG4wYQPlF
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spent three days trying to cook pfps for @Gradient_HQ community…
still not 1000% happy with result
it turned out way harder than i expected
but made fun lil art with @HexxRL and @VinoisAsian
u can peep pfp drafts below https://t.co/5v5g6akn8E
still not 1000% happy with result
it turned out way harder than i expected
but made fun lil art with @HexxRL and @VinoisAsian
u can peep pfp drafts below https://t.co/5v5g6akn8E
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> high capex
> latency
> low throughput
./ Echo fixes root problems, not symptoms, by splitting training and inference.
- inference does not need to live on expensive centralized gpus.
it can run in distributed or local environments, where compute already exists and is cheap. https://t.co/iJP7K4IsLY
> latency
> low throughput
./ Echo fixes root problems, not symptoms, by splitting training and inference.
- inference does not need to live on expensive centralized gpus.
it can run in distributed or local environments, where compute already exists and is cheap. https://t.co/iJP7K4IsLY
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./ how the perfect Sovereign AI by @Gradient_HQ equation comes together
Sovereign AI is artificial intelligence that belongs to you and follows your rules.
today most AI lives inside centralized services. you get comfort, but you lose control.
Sovereign AI flips the model >>>
> https://t.co/tM6ZtEF1Zz
Sovereign AI is artificial intelligence that belongs to you and follows your rules.
today most AI lives inside centralized services. you get comfort, but you lose control.
Sovereign AI flips the model >>>
> https://t.co/tM6ZtEF1Zz
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Top 5 Core Capabilities of @Gradient_HQ Project 📗
1⃣ Edge computing
---------------------
▫️ Gradient enables distributed computing across many independent devices. Instead of relying on centralized servers, computing tasks are distributed among network participants. This https://t.co/ihKapSKul1
1⃣ Edge computing
---------------------
▫️ Gradient enables distributed computing across many independent devices. Instead of relying on centralized servers, computing tasks are distributed among network participants. This https://t.co/ihKapSKul1
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I love it when something wonderful happens at @Gradient_HQ . For example, you can learn about 5 cool things VeriLLM does 🫶🫶🫶
VeriLLM presents a new approach to distributed inference, focusing not only on scalability but also on reliability as a primary system property. https://t.co/b71hfHLdtu
VeriLLM presents a new approach to distributed inference, focusing not only on scalability but also on reliability as a primary system property. https://t.co/b71hfHLdtu
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OIS:
- Protocols
🔗Lattica: communication
✔️Veri: verification
🕵️[—]: privacy
- Core MLSys
💻Parallax: serving
🔬Echo: learning
🤖[—]: simulation
🦾[—]: train
🎼[—]: MA
- Gradient ☁️
🔚Inference Endpoints
⏳[—]
🏋️*****
👾[—]
🧑🧑🧒🧒[—]
./ @Gradient_HQ OIS coming together.. 👀 https://t.co/Jief3RJCbV
- Protocols
🔗Lattica: communication
✔️Veri: verification
🕵️[—]: privacy
- Core MLSys
💻Parallax: serving
🔬Echo: learning
🤖[—]: simulation
🦾[—]: train
🎼[—]: MA
- Gradient ☁️
🔚Inference Endpoints
⏳[—]
🏋️*****
👾[—]
🧑🧑🧒🧒[—]
./ @Gradient_HQ OIS coming together.. 👀 https://t.co/Jief3RJCbV
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web3 traveler 🗺️ | believer 💞 | ± contributor 🌟 Scout @soneium Tech Guru @Gradient_HQ ShroomieBeliever @0xfairblock
1.2K Followers
11 Contributions
thinking about crypto // drawing wen it gets annoying / failed vibe curator (─‿‿─)♡
2.5K Followers
3 Contributions
📘 Telegram - https://t.co/mrjkyskdUl 👑 Top Content_Creator | INFLUENCER 👑 ✹ Believer Web3 Project ✹
1.1K Followers
3 Contributions
push past limits | real niu for @Gradient_HQ | part time troll | full time janitor | professional edging specialist
2.3K Followers
2 Contributions
I swear to god that it's all in the making I swear to god, I'ma fall if I fake it pfp by @shinori_san
1.1K Followers
1 Contributions
4.8K
Total Members
+ 0
24h Growth
+ 3
7d Growth
Date Members Change
Feb 10, 2026 4.8K +0
Feb 9, 2026 4.8K -2
Feb 8, 2026 4.8K -2
Feb 7, 2026 4.8K +2
Feb 6, 2026 4.8K +2
Feb 5, 2026 4.8K +3
Feb 4, 2026 4.8K -2
Feb 3, 2026 4.8K +4
Feb 2, 2026 4.8K -3
Feb 1, 2026 4.8K +5
Jan 31, 2026 4.8K +0
Jan 30, 2026 4.8K +3
Jan 29, 2026 4.8K +0
Jan 28, 2026 4.8K —
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