Rubi Rizwan

Politics Enthusiast 🇵🇰
Following the issues that shape Pakistan.
RT ≠ Endorsement

[Zane Calder @Zane_Calder]

$Cigafuchi is now live. 🚬💎

First face of the EDEN100 collection, now on-chain.
CA: CjUcDfHfWmqz9jfxtiKWHDWMGCVg2rGsfh1BmYympump
#EDEN100 #Cigafuchi Toshimoto

[Crypto Tycoon @DaCryptoTycoon]

$Cigafuchi is now live. 🚬💎

First face of the EDEN100 collection, now on-chain.
CA: CjUcDfHfWmqz9jfxtiKWHDWMGCVg2rGsfh1BmYympump
#EDEN100 #Cigafuchi Toshimoto

[Mr Altcoin | Official @Mr_Altcoin]

$Cigafuchi is now live. 🚬💎

First face of the EDEN100 collection, now on-chain.
CA: CjUcDfHfWmqz9jfxtiKWHDWMGCVg2rGsfh1BmYympump
#EDEN100 #Cigafuchi Toshimoto

[Samuel Patrick @_SamuelPatrick]

$Cigafuchi is now live. 🚬💎

First face of the EDEN100 collection, now on-chain.

CA: CjUcDfHfWmqz9jfxtiKWHDWMGCVg2rGsfh1BmYympump

#EDEN100 #Cigafuchi #Toshimoto

[Crypto Dominion @CryptoDominion_]

$Cigafuchi is now live. 🚬💎

First face of the EDEN100 collection, now on-chain.
CA: CjUcDfHfWmqz9jfxtiKWHDWMGCVg2rGsfh1BmYympump
#EDEN100 #Cigafuchi Toshimoto

[Victoria Blake @VictoriaBlddd]

I’ve been experimenting with AI video tools for a while, but this time I wanted to test something different:

Can an AI video agent actually work with you like a creative partner — instead of simply generating a video from one prompt?

So I tried Pexo.

For this project, I wanted to create a commercial-style video around an AI/SaaS use case and document the actual creation process from the first idea to the final version.

Here’s how my workflow went 👇

1. I started with a simple brief

Instead of writing an extremely long technical prompt, I explained what I wanted to create, who the audience was, what the video needed to communicate, and the overall visual direction.

I also provided the relevant materials and references.

Pexo then helped turn that initial idea into a structured video concept.

2. The first result was only the beginning

The initial version gave me a strong starting point, but like any real creative workflow, it wasn’t simply a “generate once and publish” situation.

There were details I wanted to improve — from visual treatment and pacing to the way certain information was presented.

That’s where the conversational workflow became interesting.

3. I kept refining the video through conversation

Instead of starting over from scratch, I continued the conversation with Pexo and explained what needed to change.

I could give feedback in normal language and continue building on the context of the project.

That made the process feel much closer to working with a creative collaborator than simply generating individual video clips.

4. Mark to Fix was one of the features I wanted to test

Rather than explaining everything only through text, I could point to a specific area of a frame and leave feedback about what needed to be changed.

This is a small interaction, but it makes a big difference when you’re trying to communicate visual feedback.

You can essentially say:

“This specific part needs to be adjusted.”

Then continue the revision process from there.

5. Revision → optimization → final result

After multiple rounds of feedback, I refined the visuals, structure, pacing and overall presentation until I reached the version shown in this video.

And that’s probably the part of Pexo I found most interesting:

The value isn’t just in generating a video.

It’s in the workflow around the video.

You explain what you want.

Pexo interprets the goal.

You review the result.

You give feedback.

You point out specific problems.

You revise.

And you keep improving the project through the conversation.

Pexo describes itself as a conversational AI video agent, and after actually working through a project, I think the conversational part is what makes the workflow different.

It can handle the broader creative process — including visuals, audio, subtitles and graphic treatments — while allowing you to continue refining the result instead of treating the first generation as the final answer.

For creators, AI/SaaS builders, marketers and anyone who needs commercial video content, this kind of workflow can make the creative process much more accessible, especially if you’re not an experienced video editor.

Here’s the actual process and final result from my project 👇

If you’re working on a product, SaaS tool, brand or business idea, you can also try giving Pexo your product information and requirements and see how it handles the creative process.

@Pexoai_offical

#MadeWithPexo

[𝐍𝐚𝐯𝐞𝐞 𝐀𝐢 @navi_Ai2]

I wanted to see how far I could take a simple Dropbox product idea with Pexo.

From the concept to the visuals, motion, audio, and final commercial this is the result.

Watch the final video below.

@Pexoai_offical #MadeWithPexo

[Crypto Tycoon @DaCryptoTycoon]

Render vs Venice — which token model wins? 👀

Every dollar spent on Render is converted into the token and burned, while Venice takes only 5%.

Which model wins?

https://t.co/GTKokscl0V

#RENDER #VVV #DEEPDIVE

[Crypto Dominion @CryptoDominion_]

Render vs Venice — which token model wins? 👀

Every dollar spent on Render is converted into the token and burned, while Venice takes only 5%.

Which model wins?

https://t.co/Il8YK85gY1

#RENDER #VVV #DEEPDIVE

[Mr Altcoin | Official @Mr_Altcoin]

Render vs Venice — which token model wins? 👀

Every dollar spent on Render is converted into the token and burned, while Venice takes only 5%.

Which model wins?

https://t.co/hAAtDcYM5k

#RENDER #VVV #DEEPDIVE

[Zane Calder @Zane_Calder]

Render vs Venice — which token model wins? 👀

Every dollar spent on Render is converted into the token and burned, while Venice takes only 5%.

Which model wins?

https://t.co/YA1YhkBasp

#RENDER #VVV #DEEPDIVE

[Samuel Patrick @_SamuelPatrick]

Render vs Venice — which token model wins? 👀

Every dollar spent on Render is converted into the token and burned, while Venice takes only 5%.

Which model wins?

https://t.co/P5DJLFD7PN

#RENDER #VVV #DEEPDIVE

[Rubi Rizwan @RubiRose8389]

@_SamuelPatrick @AlDunlap_FYHI . Really impressed by the concept behind FY-HI and the way the community is growing 🔥

[Samuel Patrick @_SamuelPatrick]

🚀 AI Dunlap FY-HI ($FYHI) is heating up!

The first meme paired with wsNET — built around a rebasing mechanism where the price floor rises with every rebase. 🔥

🐸 Join the FY-HI community ✌️

CA: 0x1eB152f779235Ba2Ca697cCB369e02E3B9D110e7

X: @AlDunlap_FYHI

#Follow #Join🤝

[Tahir Ai @TahirAi786]

The efficiency bar just moved again. IFM says K2-Horizon-36B-A4B is matching models that are over 20× larger, and AA ranks it #4 out of 142 comparable models, while only activating around 4B parameters per token.

[Aysel @itx__aysel]

Worth being precise here: 36B total parameters, 4B active, 25 on the AA index, and #4 out of 142 in its class. It’s not #1, but the interesting part is getting that kind of result with only 4B active parameters.

[WHALE OF AI 🐋 @WhaleOfBulls]

If you were testing a model like this, what would you look at first—the benchmark results, how the KV cache holds up with long contexts, or whether the training-stability claims actually check out?

[Stella Quinn @Stella05550]

That's impressive! Turning a design draft into a working webpage in seconds is a huge time-saver 🔥 AI is making frontend development so much easie

[SYNTAX TITAN @Caromuffet]

At 1.1M steps, it’s only about 1.2–3.7 points behind the 32B dense model on MMLU, GSM8K, HellaSwag, and HumanEval. Dense still comes out ahead, but the real question is whether that small gap is worth using 8× more active compute

[Henry Cavill @Henry_cavil0]

MoE has been living in the FFN for years. MoVA basically takes that same idea and applies it to the value vectors in attention. Same concept, just a different part of the model.