@rema.0723:

_Rema_
_Rema_
Open In TikTok:
Region: FR
Wednesday 07 October 2026 11:35:21 GMT
80003
15208
34
1793

Music

Download

Comments

rayayan91
ℝ𝕒𝕪𝕒𝕟 :
donc tu prédit ta victoire avec la 8/10
2026-10-07 11:48:48
497
mathis.b_y
Mathis :
Forte envie de republier
2026-10-07 17:37:50
53
jussior
JU’SS :
On a pris l’exp maintenant on vas Farmer des boss 🤣
2026-10-07 17:45:55
203
king_shaakaa
☀️ 𝓒𝓱𝓲𝓷𝓪 ⚫️ :
Elle ne m’a pas followback sur insta mais au moins elle a dansé avec moi en boîte 😌😌😌
2026-10-07 17:01:14
21
user.sk95.1
user.sk95.1 :
Et la t’apprends que t’etais juste un defi
2026-10-07 22:06:06
3
yann.2.01
Y.C :
tellement réel c tiktok en plus
2026-10-07 18:54:21
12
yohan19fight
🙏🏿🇲🇶 yohan19fight🇲🇶🙏🏿 :
c'est trop réel
2026-10-07 15:10:07
5
stany.bl
Le ténébreux. :
Wesh 🤣 réel
2026-10-08 00:30:44
1
bent010
Ben M🇸🇳 :
2026-10-07 23:17:33
1
wigo.volaille
wigo volaille 🐔 :
Elle a pris mon numéro mais quand j’ai pris la sienne j’ai tout gâcher, au moins je sais que la personnalité attire 😑
2026-10-07 17:06:43
4
1souleymane_
_1souleymane ンダオ🇯🇵 :
Réel
2026-10-07 20:35:20
1
kader_08.0
kader_08.0🇲🇷 :
2026-10-07 19:09:48
1
r.m01087
zig le zgeg :
2026-10-07 19:38:40
0
nld663
𝑨𝑴𝑷𝑬𝑹𝑬𝑼𝑹𝑬 𝔻 :
2026-10-07 21:23:23
0
kelly_akplogan
Kelly :
2026-10-07 22:02:03
0
michkamuku10
Michka Mukudi :
2026-10-07 22:43:23
0
ak423918167
Ak-077 :
2026-10-08 01:19:45
1
lelouch1.3
🫚ALYNE★ :
Nah bro t’étais juste en édition «d’essai pour 10 jours» 😂
2026-10-08 00:07:56
0
b.prt96
Bilal :
Score partout
2026-10-07 22:29:19
0
real_khalif
Republie-Man :
@All for one1 😏
2026-10-07 23:01:10
0
To see more videos from user @rema.0723, please go to the Tikwm homepage.

Other Videos


"Should I use RAG or long context?" is the wrong question. ⚡ You're going to use both. And memory. The three aren't competing — they answer different questions about what goes in the prompt. Here's the honest comparison 👇 🟡 LONG CONTEXT — put it all in Cost: 198k tokens, every single call. Wait: time-to-first-token climbs with input size. 💥 Breaks when: recall sags in the middle of very long inputs. ✅ Reach for it when: the corpus is small, stable, and needed on every call. 🔵 RAG — fetch only what matters Cost: ~4k tokens per call. 10M chunks in, top 8 out. Wait: one extra retrieval hop. 💥 Breaks when: retrieval misses. If it doesn't fetch it, the model cannot know it — and it will answer anyway. ✅ Reach for it when: the corpus is large, or it changes every day. 🟢 MEMORY — remember the person Cost: ~300 tokens per call. Wait: one key lookup. 💥 Breaks when: yesterday's fact is still true as far as it knows. ✅ Reach for it when: the fact is about this person, across sessions. 👀 The one nobody says: memory is the only one of the three that writes back. RAG reads an index someone else built. Long context reads what you pasted. Memory takes the answer and updates the store — that loop is the entire difference, and it's also why memory rots and the other two don't. 🎯 The rule: pick by what changes. Never → long context. Often → RAG. Per person → memory. 🤖 A support bot runs all three at once: their plan (memory) + today's policy (RAG) + this ticket thread (long context). 📸 Screenshot the comparison. Save it before your next architecture argument. Follow @hackproduct — we turn scary AI-engineering concepts into things you can ship. ⚡ . . #RAG #AIengineering #LLM #longcontext #vectordatabase

About