ꜰᴀʀɪᴀ ᴋʜᴀɴ

Good governance isn’t about promises—it’s about delivering measurable results.

*فَبِاَىِّ اٰلَاۤءِ رَبِّكُمَا تُكَذِّبٰنِ ۞*🌻♥️🌙

[MR ROMI 🚀📊 @usmanoffical_]

Writers, you don't need a finished AI film to enter! The Script Track is for original feature screenplays plus a 1-5 min video pitch. Show them where your story could go. 👇

[MR NADEEM AI @Solanagamsx001]

Entering the Pilot Track? PixVerse Canvas must be your primary platform.
Create
Publish
Share Link
Post publicly
Submit
Keep this workflow in mind from day one! 👇

[MR. MOHSIN @VisionCoin3]

Sitting on an AI film idea or a feature screenplay?
This is your sign to start building.
The deadline is later, but your story starts today. Check the full roadmap here. 👇

[Ana de Armas @girlxid]

Pilot or Script? Under the Skin or Worlds Beyond? Here is your complete PixLight roadmap from idea to submission. Everything you need to know before you start creating is right here. 👇

[Hafiz Abdul Rauf Nasir @HAbdulraufNasir]

گلگت بلتستان اسمبلی نے مکہ دفاعی معاہدے کا خیرمقدم کرتے ہوئے مسلم اُمہ کے اتحاد اور اسلامی ممالک کے درمیان باہمی دفاعی تعاون کے فروغ کے لیے قرارداد متفقہ طور پر منظور کر لی۔ قرارداد قائدِ حزبِ اختلاف حافظ حفیظ الرحمن نے ایوان میں پیش کی۔
@CMGBPK
#GilgitBaltistan #GBAssembly #GilgitBaltistanAssembly

[Hafiz Abdul Rauf Nasir @HAbdulraufNasir]

وزیر اعلیٰ گلگت بلتستان امجد حسین کا استور کا دورہ
وزیر اعلیٰ گلگت بلتستان امجد حسین کی استور آمد پر پولیس کے چاک و چوبند دستے نے سلامی پیش کی، جبکہ ڈپٹی کمشنر استور اور ایس پی استور نے انہیں روایتی چوغہ اور ٹوپی پہنائی۔
اس موقع پر وزیر اعلیٰ امجد حسین نے ضلعی انتظامیہ استور اور محکمہ مواصلات و تعمیرات کے افسران کو حالیہ سیلاب اور بارشوں سے متاثرہ شاہراہوں کی فوری صفائی، بحالی اور چینلائزیشن کے حوالے سے ضروری ہدایات جاری کیں۔

[MR LARK DAVIS 🚀📊 @JameFalken]

Paying premium prices for a massive model when only a small slice is relevant to your task feels inefficient.

You’re essentially covering the cost of intelligence you may never use.

@oumi_ai makes a more tailored approach to AI worth considering.

Build around the capabilities your workload actually needs.

Because small inefficiencies can become very real costs at scale.

[Alex Bitoshi @munzxsdv]

Spent two years paying frontier-model prices for a narrow task that still wasn’t handled well.

Then a smaller, specialized model comes along and does the job better for a fraction of the cost.

Hard not to feel like I overpaid for the wrong approach.

Sometimes focused intelligence really does beat brute force.

[AHSAN BILAL @Hwypanda]

Using the exact same model as everyone else doesn’t make your AI strategy unique.

Slapping “AI-driven” on a pitch deck doesn’t create a real advantage.

@Oumi_ai makes the case for building models around what actually matters.

The real edge comes from adapting AI to your specific needs and data.

Generic models are easy to copy; differentiated AI is where the value is.

[Hafiz Abdul Rauf Nasir @HAbdulraufNasir]

14 اگست خوشی کا دن ہے، مگر شور شرابے کا نہیں۔

آئیں جشنِ آزادی کو ذمہ داری اور احتیاط کے ساتھ منائیں۔

باجے بجانے، ون ویلنگ کرنے، تیز رفتاری اور سڑکوں پر غیر ضروری ہارن سے گریز کریں۔

ہماری خوشی کسی دوسرے کے لیے تکلیف نہ بنے۔

آئیں اپنے ماحول کو پُرسکون، محفوظ اور خوبصورت بنائیں۔ 💚🇵🇰

#14August #Pakistan #IndependenceDay #JashnEAzadi #PakistanZindabad #islamabad

[SOPHIA VALE @88C888]

When was the last time a model update actually improved your product without your team doing extra work?

That’s the part most AI workflows still miss.

Real improvement should feel continuous, not like another engineering project.

If the model can’t evolve with the product, what’s really improving?

[Queen Isabell @Queen_1o1]

If a tailored model can deliver better results at a fraction of the cost, that changes the equation.

Why pay frontier-model prices for capabilities your task doesn’t actually need?

@oumi_ai is pushing the idea that specialized AI can compete where it matters most.

Lower cost, stronger task-specific performance, and more control is a compelling combination.

Sometimes the smaller, focused model is the one that wins.

[MR ROMI 🚀📊 @usmanoffical_]

Production should be where your model keeps learning and improving.

Not a place where it stays frozen at the level it shipped with.

Real-world feedback should shape the next version.

The best AI systems should get better through every cycle.

[Amelia Eilish @1z11_]

A lot of enterprise AI budgets still look like paying rent for someone else’s models and calling it a strategy.

Using a generic model isn’t the same as building a real AI advantage.

The stronger play is creating systems that actually reflect your own data and needs.

That’s where long-term differentiation starts.

[MR.ALEX B @TheAlexBitoshi]

Most “AI factory” launches stop at a polished deck and a waitlist.

@Oumi_ai is showing the full loop in action: Evaluate, Synthesize, Train, Deploy, then Compound on a real task.

Watching that process happen live is far more interesting than another launch announcement.

[Munawar Arshad @QwolfAi]

24 hours to go—either watch @Oumi_ai show a model learning on a live task, or catch the recap afterward.

Seeing the learning happen in real time is the part I’m most curious about.

Tomorrow should be interesting.

[Melisa AI @Melisasmith_]

We benchmarked the narrow task head-to-head: an expensive frontier model versus a smaller specialized one.

The smaller model came out on top where it actually mattered.

Turns out bigger isn’t automatically better for every workload.

Sometimes specialization wins on both performance and efficiency.

[Blake Thompson @moonlitebyte]

If a purpose-built model delivers the same quality at a fraction of the cost, the economics get pretty hard to ignore.

Paying 10x more only makes sense if you’re getting something meaningful in return.

For many specific workloads, specialization can be the smarter path.
The real question is what that extra 90% is actually buying you.

[MR. MOHSIN @VisionCoin3]

Not everything needs to be built in-house.
But the technology behind your real competitive edge shouldn’t be something you simply rent.

@Oumi_ai makes building more tailored AI systems feel much more practical.

Keep the generic layers flexible and focus your effort where differentiation matters.

Your proprietary advantage should actually belong to you.

[MR NADEEM AI @Solanagamsx001]

Took me way too long to realize that a general model doesn’t automatically understand what makes my business unique.

It only becomes truly useful when it’s shaped around the problem I actually care about.

The model won’t learn that context on its own.
You have to build the system around your own needs and data.