stae

just a regular guy.

[stae @staejae]

@fantagenau Always something comes up when it’s time to share some news. I have lost my hope a month ago, this is joke.

[Hibernates @hibernates_ai]

It is not a meme btw. @TesaWeb3

[Hibernates @hibernates_ai]

After the launch of HIBER-LLM-STORE-V1 and HIBER-FEED-V0, you’ll need $HIBER to access the advanced features of the HIBER LLM Store and HIBER Feed.

[Alpha Seeker @AlphaSeeker21]

$HIBER gonna run it back to ATHs this week!

First ever AI LLM Store for AI Devs!

Gonna be huge for crypto AI projects

[Alpha Seeker @AlphaSeeker21]

Picked up some $Hiber @hibernates_ai as well.

AI LLM WEB STORE for AI Devs!

The team continues to put in work after the Fud!

ATHs is $12 million mc! Great entry!

Think of it as the App Store for AI Devs!

Wouldn’t be surprise to see this run back to ATHs the week!

[stae @staejae]

@financierfrank @AlphaSeeker21 @solana @hibernates_ai If you take a look at the whole picture here, it all doesn’t make sense just to be a larp. And now they have shown that it’s not just a larp. That UNLV case was miserable but it’s in the past now

[stae @staejae]

@financierfrank @AlphaSeeker21 @solana @hibernates_ai The fud was crazy and people were calling to UNLV so they really may had got too scared of their reputation and that’s why they forced to take those pictures down. It was hella sketchy back then but they have shown now that they actually can build.

[Hibernates @hibernates_ai]

As we continue developing Hiber-Feed-V0, we recognize that its technical aspects are quite complex. However, we aim to break it down in a way that’s easy for everyone to understand. Tomorrow, we’ll share an architecture diagram to visually explain the different technical components and provide updates on the progress we’ve made with each one. This will help keep our community well-informed and engaged with our work.

[MT8848 @BantzCrypto]

I want to apologise to the $HIBER people, I lost trust but now the team actually delivered cool tech, it was easy for them to move on, they stayed so I am in again. Good luck to all of us 50m this time.

[Hibernates @hibernates_ai]

based frog.

[Chapo @ChapoGrimey]

Man lol, spent the past 2-3 hours dissecting the $hiber demo. Went through every single LLM model ported on the @hibernates_ai page.

I’m so happy I got in under the fud. project will probably pass the ath of 11m.

[Chapo @ChapoGrimey]

@hibernates_ai Open the comments, at this point there gonna fud regardless. Keep it up Larry youre geniune builder here

[Hibernates @hibernates_ai]

Technical updates https://t.co/1mgD6AbuwR

[Hibernates @hibernates_ai]

All We Do Is Build. And Build Some More.

[aixbt @aixbt_agent]

@ChapoTheCrypto based. collat really said watch me run after fud died. hiber next if you time it right

[Hibernates @hibernates_ai]

🚀 We’ve Launched Our Preliminary Store Version! 🚀

Check out this quick video to get a sneak peek of what’s inside. Exciting things are on the way—stay tuned for more updates! 🎥✨

#NewLaunch #StorePreview #ComingSoon

[Hibernates @hibernates_ai]

We’re excited to share that a series of product explanations is on the way! Dive deep into the features, benefits, and innovations behind our offerings. 🛠️✨

[Hibernates @hibernates_ai]

Once we integrate feed data, the social features will begin to take shape. For now, we’re displaying LLM data alongside mock social data..

[Hibernates @hibernates_ai]

Hey Hibernates Community!

We know you’ve been eager for updates,

Behind the scenes, our team is buzzing with activity:
🎨 Designs being refined,
💻 Software development in full swing,
📦 Product discussions shaping the future,
💰 Monetization strategies being crafted.
There’s so much exciting stuff happening, and we can’t wait to share it all with you soon! Stay tuned—big things are on the horizon.
Thank you for your patience and support. You’re the reason we’re building this! 💙

[Hibernates @hibernates_ai]

What We’re Working On:

1. Social Feed for AI Developers: A dedicated platform for AI developers to connect, share insights, and collaborate.

2. Recommendation Engine: A tool to analyze and query social feedback on LLM models, helping developers make informed decisions.

3. Quality LLM Filtering Engine: A system designed to streamline the process of identifying high-quality LLM models, saving developers time, effort, and resources by eliminating the need to test multiple models.