Kerry

Dev & Degen

[Kerry @Caetore]

@MrZEsp @Cryptobruj Pero que cojones, dónde se ha visto eso wtf

[Eric Cryptoman @EricCryptoman]

Time is running out.

You can buy at 2m, you can buy at 6m, or you can buy at 250m+

No bundle, no team tokens, no supply control, no OTC deals or paid marketing, top 10 holders been holding 100+ days. 100% organic HODL culture, like the glory days of 2021.

solana:Hh3oTaqDCKKfdBgsQEvxp9sUwyNf8x9qmKqEMLBWpump

[HODL @hodl2013]

@BitcoinMagazine HODL rewards patience.

[ＤＯＳＫＩ @DZdoski]

@AlgodTrading Join @hyper_tensor the real decentralised ai $TENSOR is building one

[Kerry @Caetore]

@AlgodTrading $TENSOR

[Kerry @Caetore]

@alwayslearnig05 @Cryptobruj Hyperliquid como comentas es mil veces mejor que cualquiera de esos y lighter también pero obviamente a él no le interesa si está ganando más de 50k al mes de referidos de los otros no se va a pegar un tiro en el pie y perder el 90% de sus ingresos por referidos, sería gilipollas

[Kerry @Caetore]

@Cryptobruj @exdalis When vídeo salseante exponiendo tu vida privada 🌚

[Hypertensor @hyper_tensor]

Another update complete: Frameworkized Subnet Template

The subnet template has evolved from a reference implementation into a developer framework for building decentralized AI networks on Hypertensor.

This update introduces reusable framework components that handle the common decentralized infrastructure layer, allowing developers to focus on application logic.

What's included:

• Reusable server framework for P2P networking, peer discovery, consensus startup, telemetry, P2P connection management, and node lifecycle

• Merkle DAG framework with signed immutable DAG nodes, multi-head support, state materialization, synchronization, reconciliation, orphan recovery, and pluggable storage backends

• DAG + GossipSub base classes that handle publishing, validation, replication, synchronization, parent selection, and message routing

• Reusable request/response protocol framework for P2P stream protocols and DAG synchronization

• Network API bridge for external services, AI workers, dashboards, and local applications

• Consensus, telemetry, scoring, and runtime utilities for production decentralized AI operations

• Example implementations for DAG replication, peer state publishing, commit/reveal workflows, monitoring, and server lifecycle management

The goal is simple:

Give developers the substrate required to build a decentralized network that handles proof-of-useful-work AI workloads, so that builders can focus on application-layer logic.

This provides a reusable foundation for decentralized inference networks, agent systems, marketplaces, data networks, and other distributed AI applications built on Hypertensor.

[Kitty @hayotensor]

Basically a blockchain for AI (but uses a DAG)

Instead of transactions, it's the inference lifecycle that gets published to the dag chain

Visual needs to be fixed a bit but it works where each request is the parent node/block and the lifecycle of the request (acceptance, running, complete, etc.) are the children blocks.

Then each request uses the previous request as the parent

[Kitty @hayotensor]

the start of private and decentralized inference

anyone can contribute to hosting models in enclaves

prompts are not stored nor known by miners

goodbye @OpenAI

[Kerry @Caetore]

@criptomussama Airdrop de ladrillos incoming

[X Freeze @XFreeze]

Maybe it's time for the movie now 🍿

[Albo ETH @Alboeth]

This will be my last tweet for a long time.
Hypertensor will be the largest decentralized AI network. I'm all in.
I said what I said.
I'll come back to this tweet one day. 🕐
$TENSOR @hyper_tensor #DecentralizedAI

[Kerry @Caetore]

@Cryptobruj Ahora los stocks también están cayendo a ver a dónde nos arrastran

[ＤＯＳＫＩ @DZdoski]

Major Milestone Unifying Validator Identity and Staking
$TENSOR ☀️

$NOCK $OCT $VVV $TAO $AGRS $QUBIC ethereum:0x40e3d1a4b2c47d9aa61261f5606136ef73e28042 $PRL $WQUIL $JASMY

[Hypertensor @hyper_tensor]

New update complete: Validator-Based Ownership & Staking

This update introduces validators as the primary identity layer under the entire Hypertensor umbrella.

Previously, subnet nodes were independently registered, and users' stakes were delegated to them on a per-subnet basis.

Now, node operators first register a validator identity that can own and operate nodes across multiple subnets. This makes validators easily identifiable participants to whom users can directly delegate stake.

Previously, if a validator operated across multiple subnets, delegators had to discover and stake to each node separately.

Now, delegators stake directly to validators and receive emissions generated from all subnet activity associated with that validator.

The reputation system also benefits from this change. Instead of reputation being isolated to individual subnet nodes, reputation is now accumulated at the validator level. Validators build a track record across all of the networks they participate in, allowing delegation, rewards, penalties, and consensus performance to contribute to a single reputation profile.

Why this matters:

• Establishes validators as first-class network participants
• Creates a foundation for validators to operate across multiple decentralized AI networks
• Aggregates validator reputation, rewards, penalties, and consensus participation
• Aligns validator incentives across all subnets they participate in
• Enables delegation at the validator level and subnet level, making the data structure more coherent and staking decisions easier for users

This update represents a significant optimization of the validator and delegator architecture and its scalability, creating a unified reputation, delegation, and rewards system.

[Kerry @Caetore]

@love__dollie @bearsecrety Reduce esa panza 🌚

[ＤＯＳＫＩ @DZdoski]

@teegeedingdong @bryan_johnson @frankdegods @0xSweep @hyper_tensor $TENSOR Hypertensor makes you believe in decentralised ai is future.