Jules Tamara

[Jana @MTDillard3712]

Here are some pretty good hacks that could come in handy if you have some of these problems.

[DGov @omoluabi1sq]

A divorced woman advises ladies on marriage and what they need to do to avoid pitfalls in marriage to avoid divorce.

[Muscle Mode @MuscleModeHQ]

Dumbbell shoulder workout

[full slack @fullslack_]

Jessica Tarlov is essentially telling El-Sayed he should be required to support Israel as a religious ethnostate in order to earn votes from a fringe minority of disingenuous zionists who conflate Judaism with Zionism.

[Charlotte Asaaba @AsaabaCharlotte]

Men deserve to be respected and being loved right....

[Daily Fitness @DailyFitHQ]

Just 3 rounds of this routine everyday, you can notice significant changes in your physique.

[MARX @9ja_mARCx]

This guy has PhD in photography; the art of positioning

[Enezator @Enezator]

Be sure to save practical kitchen tips, it will save lives

[Alok Kumar @Alokkumarzz]

A $300,000 loan at 6.5% costs $382,633 in interest over 30 years. One extra rule changes that: interest is only ever charged on what you still owe.

Bookmark & watch today, no matter what.

[Classic Moments ✨ @Sunflower15025]

I’ve lost count of how many times I’ve watched this… this dad and son are just too funny! 😂

[Sport boy @Sp_bo1]

هذة تمارين الصدر و الكتف الذي يجب ان تفعلها في البيت للحصول على مظهرًا عريضًا ومتناسقًا

[Fitness Hub @FitHubHQ_]

Just 3 rounds of this routine everyday, you can notice significant changes in your physique.

[T-Mika ✨ @tipoupee]

Siw gade sa ou pa leve kanpe, epiw fèmen 2 zye’w pouw ap woule tankou’w te nan bann nan.
Lè ayisyen ap pale, fèmen’l!
Mezanmi 🔥🔥🔥🔥🔥🔥😂😂😂

[Eęѵվ  @SteevyDope]

Mood 😂

[shobhanai @HeyShobhan]

Hiring Tony Robbins today costs 1 million dollars for just one day.

This is a 21-minute tape recorded in his own home more than 30 years ago.
There, he explains exactly how to get anyone to say yes.
The same material for which they now charge a fortune... completely free.

It's a rare, unfiltered recording from the time when he still didn't charge millionaires just for being in the same room.

When someone says no, they give two excuses:
“I don’t have time” or “I don’t have money”
Neither is true.

The real reason is that they still don’t believe it’s worth it.
It’s not a money problem. It’s a state problem.

Tony teaches something he calls “attack and confess”
Instead of arguing the objection, you confess your own:

“I had the chance to go six months ago and I didn’t until two months ago.
I can’t even imagine the time I wasted”

The room goes silent. No one argues.

Then he gets the person on the “yes train”
Each little yes adds to the next.
Until saying no at the end feels harder than saying yes.

When it’s time to sign, the person has already said yes five times without realizing it.

Just 21 minutes.
There you learn the two only moves that people pay 1 million a day for:
how to read anyone’s state… and how to shift it.

Most people spend years guessing in sales.
He wrote it on a flipchart in his living room in less than half an hour.

A seat in that room cost $125 dollars.
Today it costs $1 million dollars a day to sit in front of him.

The tape is free right now.
And the answer is in this video.

[Prince Fynn @Prince_Fynnd]

Every man should do kegel exercise at home to improve blood flow and harder erections.

[Hurricane @HurricaneCrypt0]

THIS IS F**KING INSANE

This guy in just 16 minutes teaches you how to monetize a YouTube channel in 9 days

bookmark it, you’ll need it later

[Nutrition Guide @NutritionGuide_]

If your hips and spine feel locked, this is the reset.

[Dhruv kumar @Dhruvkumar16797]

🚨Leave Netflix tonight.

Watch this 2 h 34 min Stanford class.

It's the clearest, most complete, and brutally honest explanation out there on how ChatGPT and Claude are really built.

From Tokenization and BPE to the Transformer architecture, the training pipeline, and the next-token decoder. No fluff. No marketing. Just the truth.

Doesn't matter if you've never touched a line of AI code or if you spend your days launching Agents: by the end, you'll suddenly connect a ton of pieces you've been trying to fit together for years.

The real core boils down to this:

How text turns into numbers the model can "eat" (BPE tokenization)
The sole mission of a language model: predict the next token
How the Transformer uses Attention so tokens can pass messages to each other
In training, the NLL loss pushes the probability of the entire sequence
In generation, the decoder builds the response token by token

The big-picture view that takes most people years to form… this class delivers it to you complete in one sitting.

Free up your time.
This could be, no exaggeration, the most valuable class you watch this month.