FLock.io

Not your models, not your AI

[FLock.io @flock_io]

Every great migration starts with a leap of faith.

@flock_io is moving $FLOCK and FOMO Model Tokens onchain liquidity to @Uniswap on @base, and @RobinhoodCrypto’s Robinhood Chain.

Fly with the unicorns. Fly higher 🦄

[FLock.io Korea @flock_io_korea]

API 키 하나로 모든 모델을 🔑

FLock API 플랫폼 하나면
✅ DeepSeek · Gemini · GLM · Kimi · Qwen 등 16개 모델
✅ OpenAI 코드 그대로, base URL만 Flock으로
✅ 공급자가 느려지면 자동 우회 (스마트 라우팅)
✅ 로그 · 사용량 · 팀 관리 · Playground
✅ 크레딧 충전식 (Stripe · Base Pay · Coinbase)

FLock의 THIS/THAT 결정 모델은 $0 ⚡

👉 https://t.co/2OTjYypJOe

[FLock.io @flock_io]

Explore FLock API Platform: https://t.co/Vwlhn6b18x

[FLock.io @flock_io]

Why juggle multiple AI providers when you can access them all in one place?

One key for top open-source models from @deepseek_ai, @Alibaba_Qwen, @Kimi_Moonshot, @Zai_org, @GeminiApp, and FLock.

One platform. Endless possibilities.

Build with FLock.

[FLock.io @flock_io]

Sarawak, Malaysia’s largest state, is moving first on sovereign AI in Southeast Asia, and we’ve been part of the build with Sarawak AI Centre.

This week, SoftBank, Grab and PETROS are putting $1B into AI infrastructure there, part of $1.85B for Malaysia.

But sovereignty isn’t only about where compute sits. It’s also about how models are trained.

We're building that layer with federated learning and distributed AI, so government bodies and organisations can train their own specialised models and keep full control of their data.

[FLock.io @flock_io]

Sarawak, Malaysia’s largest state, is moving first on sovereign AI in Southeast Asia, and we’ve been part of the build with Sarawak AI Centre.

This week, SoftBank, Grab and PETROS are putting $1B into AI infrastructure there, part of $1.85B for Malaysia.

But sovereignty isn’t only about where compute sits. It’s also about how models are trained.

We're building that layer with federated learning and distributed AI, so government bodies and organisations can train their own specialised models and keep full control of their data.

[Anwar Ibrahim @anwaribrahim]

I welcome the announcement by the SoftBank-led consortium, including Grab and PETROS, to invest in AI Infrastructure Platform in Sarawak and Peninsular Malaysia.

This is a significant moment in the country’s digital transformation and reflects global confidence in Malaysia’s potential to develop and use AI. It supports our ambition to become an AI Nation by 2030, as set out in the National AI Action Plan 2026–2030. The government will work with the relevant state authorities to facilitate this highly anticipated project.

The willingness of global investors like SoftBank and Masayoshi Son to invest in Malaysia reflects strong confidence in our national capabilities, investment climate and political stability.

Integrating SoftBank’s capital and expertise with Grab’s regional AI capabilities and proven track record of deploying operational AI across its ecosystem will significantly enhance Malaysia’s AI infrastructure and global competitiveness.

As Malaysia develops its AI infrastructure, we expect large-scale digital investments to support our sustainability goals. This project must meet applicable federal and state requirements, including those on renewable energy use.

I expect this investment to create skilled jobs for Malaysians and help more of our rakyat build expertise in AI. It should also create opportunities for our local businesses to supply goods and services as Malaysia builds its AI capabilities.

#MalaysiaMADANI
#YakinMADANI

[FLock.io @flock_io]

Our CEO and founder @0x7Sun on what FLock’s building.

Think of it as giving enterprises the capability to train their own specialised AI models that understand their business, without handing over the data that makes them unique.

[GrowWithTiffany @TiffanyWang98]

Every government I've spoken to wants AI in public services. The hesitation is never about the technology. It's about the data: where it goes, who can see it, and what happens if it leaks. That's why we start from the other end. Keep the data where it is, and bring the AI to it.

I shared how we take this from pilot to scale in techUK's Digital Transformation in the Public Sector series. Thanks @techUK for having me.

[FLock.io @flock_io]

Win so much.

[Zehua Cheng @zehuac]

The visual effects of presenting both papers are quite interesting. We have more paper presented in CIKM 2026.

[FLock.io @flock_io]

@zehuac @cikm Read about our research: https://t.co/afAzzag4Wn

[FLock.io @flock_io]

Our Chief AI Scientist @zehuac was in Rome to present six FLock papers in the @CIKM 2026 Full Research Track.

Together, they map out what we need to make private AI training affordable, safe, and reliable at scale.

1. Cheaper training

Most training updates the whole model at once, even though the parts affect each other. Gradient Interaction Graph Optimization updates them in a smarter order and reaches the same quality in about a third fewer steps.

2. Safer model merging

Combining two models can work well or ruin both, and normally you only find out after running expensive tests. Curvature Graph Mergeability predicts the outcome in advance from a quick scan of each model.

3. Robustness to bad examples

Showing misleading examples in a prompt can throw off the whole answer. In-Context Learning as Belief Propagation lets the model recognise the odd one out and trust it less, improving accuracy by about 7 points.

4. Keep structured outputs consistent

When AI fills in a form, it often decides each field separately, so a junior job title can end up next to a senior salary. Bethe Consensus Decoding checks the fields against each other and returns a consistent answer, with no retraining.

5. Quantify uncertainty

A model should be able to say “it’s one of these three” when it isn’t sure. Cavity-Calibrated Prediction Sets give guaranteed-reliable shortlists that are up to 58% tighter, so they stay useful.

6. Anonymise training text

Real-world text is full of names and personal information that regulations keep off-limits. Graph-Driven Context-Preserving Anonymization removes 99.8% of it while keeping the text just as useful for training.

Private AI becomes more critical as data becomes every organisation’s edge, and FLock is building at that frontier.

[FLock.io @flock_io]

Full episode on Bae HQ ↓

https://t.co/RLYOyIQgj2

[FLock.io @flock_io]

Our CEO and founder @0x7Sun on what FLock’s building.

Think of it as giving enterprises the capability to train their own specialised AI models that understand their business, without handing over the data that makes them unique.

[jsun @0x7SUN]

When you look at this that 1.7

You will know how amazing

FLock is.

[FLock.io @flock_io]

Open source on @huggingface: https://t.co/BgtCxZTCoB

[FLock.io @flock_io]

Imagine a decision model in a checkout system.

THIS / THAT Model follows the defined risk policy, scores every allowed answer in one pass, and returns one typed decision with a confidence score in milliseconds.

Fully local. No output tokens.

A demo made by community.

[FLock.io @flock_io]

Try it yourself on FLock API Platform: https://t.co/hjh2gN4fI7

[FLock.io @flock_io]

@0x7SUN @zehuac 🤯

[FLock.io @flock_io]

The UK is home to some of the world’s best AI research. Now it needs more AI companies that turn ideas into revenue and stay here.

Three ways to get there:

1. Keep compute spend at home: Pooled, distributed compute keeps AI R&D funding in the UK instead of paying GPU rent to overseas hyperscalers.

2. Use privacy to unlock scale: Federated learning lets hospitals, councils and banks train their own specialised models on proprietary data without it leaving the building.

3. Back the step from pilot to production: Favourable policies and the public sector as an early customer would help far more UK teams land a first contract.

Our Head of EMEA @TiffanyWang98 shared these on the “Buy, Back, or Get Out of the Way” panel at @techUK’s Tech & Innovation Summit 2026. Thanks for having us.

[FLock.io @flock_io]

Trade, own, and earn from real AI model usage: https://t.co/lDOunUd0kH

[FLock.io @flock_io]

Every great migration starts with a leap of faith.

@flock_io is moving $FLOCK and FOMO Model Tokens onchain liquidity to @Uniswap on @base, and @RobinhoodCrypto’s Robinhood Chain.

Fly with the unicorns. Fly higher 🦄