@editbyrjr_kz: Portugal 5:0 Uzbekistan // Ronaldo back // Double frist WC // rate this edit pls // @DYE🇰🇿 pls follow me #rjr #ronaldo #style

🇵🇹𝑹_𝑱_𝑹🇰🇿
🇵🇹𝑹_𝑱_𝑹🇰🇿
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Region: KZ
Wednesday 24 June 2026 09:09:58 GMT
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ace.cct5
ACE🧊 :
Невеш факты говорит
2026-06-24 09:24:39
75
daa_nicc9y
черепук🐢ᛉ :
невеш фактит
2026-06-24 13:17:14
7
zhambylerdaulet7725
Erdaulet_7725 :
Real madrid 5:0 Kairat
2026-06-24 12:15:00
0
aibarchik000
𝐏 𝐀 𝐓 𝐑 𝐈 𝐂 𝐊 💥 :
Невеш-Бедный игрок матча Роналду-Лучший игрок матча и что скажите?
2026-06-24 17:18:35
5
asel.bolekbaeva8
Aslan. :
когда Роналду забил невеш пошел с ним праздновать😂✌
2026-06-24 13:54:21
18
beacon6834
KA7A😔🥲 :
чё невеш сказал
2026-06-24 10:19:29
5
per4ik__edits
🌶️PER4IK TOP🌶️ :
first!
2026-06-24 09:12:37
1
spi14mer
JOE_SPIKER :
брат идею возьму?
2026-06-24 16:55:13
0
anzjunior1
𝑨𝑵𝒁 (RETIRE🥀💔) :
Не болган кормедым
2026-06-24 10:34:02
1
prettxd0777
𝕡𝕣𝕖𝕥𝕥𝕩𝕕🪄 :
2026-06-24 09:51:37
2
eazy8093
𝕰𝕬𝖅𝖄 :
Что невег сказла
2026-06-24 14:49:51
0
slayzx01_t0p
𝕊𝕝𝕒𝕪𝕪𝕪𝕫𝕩||🇰🇿👑 :
можно идею
2026-06-24 13:04:54
0
ro7a_edits
RO7A :
братик когда коллаб?
2026-06-24 17:38:25
0
lydmila_picyn1488
Tsarukyan,Makhachev,Gaethje :
чем тебе не понравился невеш?
2026-06-24 17:57:51
0
flex77754
RA7A👻 :
Бро го колаб
2026-06-24 17:51:45
0
baxt3rinho
Куль :
зидан знал
2026-06-24 18:51:49
0
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Other Videos

🚨 Panicking because your AI's loss is going UP? Don't. It might actually be getting smarter.
 
 If you are transitioning from standard Deep Learning to Reinforcement Learning, you have probably stared at your TensorBoard in absolute confusion. Your agent is surviving longer, your rewards are increasing, but your loss is oscillating wildly and growing in magnitude. 
 
 Here is the First Principle you need to understand: **In RL, Loss $\neq$ Error.**
 
 🧠 **The Quick-Win Mental Model:**
 Think of your RL training like driving a car.
 🏎️ **Loss = The Steering Wheel.** It fluctuates left and right (positive and negative) to adjust the probabilities of your AI's actions. A steering wheel at zero just means you aren't turning.
 ⏱️ **Average Reward = The Speedometer.** This is the ONLY metric that tells you if you are actually moving toward your goal.
 
 ⚠️ **Crucial Rule:** Never square your negative returns to make them positive like you would with MSE. Squaring a -50 penalty turns it into a +2500 reward. You will literally teach your AI to jump off a cliff! Swipe through the carousel to see exactly why. 👉
 
 📚 **The Math Behind the Magic:**
 Want to see the beautiful calculus that makes this work? I just published a complete Deep-Dive on Substack where we derive the Policy Gradient Theorem from scratch. We break down the famous
🚨 Panicking because your AI's loss is going UP? Don't. It might actually be getting smarter. If you are transitioning from standard Deep Learning to Reinforcement Learning, you have probably stared at your TensorBoard in absolute confusion. Your agent is surviving longer, your rewards are increasing, but your loss is oscillating wildly and growing in magnitude. Here is the First Principle you need to understand: **In RL, Loss $\neq$ Error.** 🧠 **The Quick-Win Mental Model:** Think of your RL training like driving a car. 🏎️ **Loss = The Steering Wheel.** It fluctuates left and right (positive and negative) to adjust the probabilities of your AI's actions. A steering wheel at zero just means you aren't turning. ⏱️ **Average Reward = The Speedometer.** This is the ONLY metric that tells you if you are actually moving toward your goal. ⚠️ **Crucial Rule:** Never square your negative returns to make them positive like you would with MSE. Squaring a -50 penalty turns it into a +2500 reward. You will literally teach your AI to jump off a cliff! Swipe through the carousel to see exactly why. 👉 📚 **The Math Behind the Magic:** Want to see the beautiful calculus that makes this work? I just published a complete Deep-Dive on Substack where we derive the Policy Gradient Theorem from scratch. We break down the famous "Log-Derivative Trick" and show how this exact math forms the foundation of PPO—the algorithm OpenAI uses to align ChatGPT. 🔗 **Link in bio to read the full mathematical proof!** 👇 **Question for you:** Have you ever accidentally trained an AI to do the exact opposite of what you wanted? Tell me your funniest RL fail in the comments! #reinforcementlearning #machinelearning #deeplearning #artificialintelligence #math

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