@kotpantwithmekk: 💜❤️askitomla kampüs fitcheck @n #fitchecks #fy #gaün #gaziantep

melikee🌟🩷🧿
melikee🌟🩷🧿
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Region: TR
Sunday 11 October 2026 13:55:06 GMT
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mehmettt...y38
《_ʍҽհʍҽԵ_》 :
Üniversite mi podyum mu bilemedim
2026-10-14 06:10:21
59
onr_ayr_izmir35
Onur Ayrıç :
Mor daha iyi 💃🫠
2026-10-15 00:23:11
7
rifatcan353
Rıfat can :
Üniversite hayatı bambaşka bişi
2026-10-13 22:56:43
18
sfysucngiz
𝒮 :
bu kadinlar olaaaaysiii
2026-10-11 15:23:32
2
42turk_42
Trturk :
kıvırcık kıvrım kıvrım kivrilirim 🌹🌹🌹
2026-10-16 17:51:51
1
atalar_27
Ali Akif ATALAR🐆 :
kıvırcığın insta veya tiktok ne bulamadım aw
2026-10-14 10:44:14
3
deniz.can270
deniz can :
kıvırcık saçlı kızlar zafım var
2026-10-14 04:42:15
3
hikmetoo7
HK :
2026-10-13 20:15:02
7
ahmetdemir0027
a.demir :
antebe benzemiyor ama shsh
2026-10-13 22:20:46
3
semih42tofask
OTO _BOYACI _42_Tofaşk🌹💞🚙🤗 :
maşallah neymiş bu kızlar böyle süpersiniz ikiniz de maşallah [Kalpleri ısıtan][Kalpleri ısıtan][Kalpleri ısıtan][Kalpleri ısıtan][Kalpleri ısıtan]
2026-10-14 05:05:41
2
murat.33617
murat 33 :
Kardeşmisiniz
2026-10-14 01:58:18
1
mertbe53
mert.35.35 :
2026-10-14 00:58:34
1
mehmet_tulan07
ANTALYALI :
illaki gözlük kim nederse desin
2026-10-14 05:00:36
1
jandarma213
Ümit dursun :
🥰🥰
2026-10-13 19:39:59
2
alicnnn_
AA :
2026-10-13 17:49:05
2
tahirrrsmh
. :
2026-10-13 19:27:43
2
mhmtdmir123
Mehmet Demir :
2026-10-13 14:08:27
2
can_aslan112
can_aslan112 :
2026-10-13 14:49:09
1
emrekurt015
Emre Kurt9155 :
taş gibi hatun
2026-10-13 23:22:49
2
ilhan.beyyy
ilhan.beyyy :
2026-10-13 23:17:20
1
ilhndy27
"Sol_Yanım" :
kıvırcık saçlı kız gerçekmi❤️
2026-10-15 10:11:28
2
yusufackkgz27
Yusuf Açıkgöz 27🇹🇷📽️🎭 :
2026-10-13 14:44:52
2
mamierrgn
user8263272910 :
ala ala
2026-10-13 22:00:50
1
yusufkzlarslan4224
yusuf kzlarslan :
aşkitomla yıkama check 🥰
2026-10-13 21:19:54
1
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Other Videos

Prompting vs RAG vs Fine-tuning — the question every AI team argues about, answered in one picture. 🧠 Stop asking
Prompting vs RAG vs Fine-tuning — the question every AI team argues about, answered in one picture. 🧠 Stop asking "should I fine-tune?" Ask: is the problem style, facts, or judgment? 1️⃣ Prompting — fixes style. Tell the model how to answer: JSON, concise, this tone. → Use when: the facts are right but the format or tone is wrong. No training data. But the model never learns anything new. 2️⃣ RAG (Retrieval Augmented Generation) — fixes facts. The model still doesn't know it, but it can look it up in your docs. → Use when: facts change often, or live in your private docs. Update the docs, and the answers update the same day. No retraining. 3️⃣ Fine-tuning — fixes judgment. Train on examples until the model makes the call the way your team would. → Use when: the pattern is stable, but no prompt can capture it. Needs good examples, and a retrain every time the pattern changes. 👀 The part nobody says: most "we need to fine-tune" problems are really facts problems. Fine-tuning doesn't keep facts fresh, and when your pricing changes next week, the model won't know. Rule: style = prompt, facts = RAG, judgment = fine-tune. Try them in that order. Where teams go wrong: spending weeks building a training set to teach the model their product docs, when RAG would have shipped in days and stayed current. Send this to whoever just said "let's fine-tune it". 📸 Screenshot the last frame — the whole decision in one line. Save it before your next "should we fine-tune?" meeting. Follow @hackproduct — we turn scary AI-engineering concepts into things you can actually ship. ⚡ . . #AIengineering #machinelearning #softwareengineering #LLM #RAG

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