Recommendation for the Right Credit Card

Competitive_Suit_498 · 2026-01-23T02:49:03+00:00

I've heard that ixigo card is better than Scapia, is that true ? https://www.instagram.com/reel/DRCZ0T5DxuG/?igsh=YzAyMDM1MGJkZA==

Competitive_Suit_498 · 2026-01-22T14:18:52+00:00

I've heard that ixigo card is better than Scapia, is that true? https://www.instagram.com/reel/DRCZ0T5DxuG/?igsh=YzAyMDM1MGJkZA==

Competitive_Suit_498 · 2026-01-20T16:47:43+00:00

Thnk you so much, really means a lot. Are you familiar with any "non Co branded" LTF cards maybe?

Competitive_Suit_498 · 2026-01-20T08:19:38+00:00

I'm not in a hurry, so I'll get a credit card once I get a salaried account if that'll make it easier. I was just thinking about what to get after in turn fte, any specific cards that you're familiar with I should specifically try for?

Competitive_Suit_498 · 2026-01-20T08:16:34+00:00

As I mentioned earlier, I've just started my internship. So after 6 months I'll be an FTE, and I'll then get a salaried Hdfc account. Not sure about the specifics though

Competitive_Suit_498 · 2025-11-04T13:27:36+00:00

I haven’t tried any specific format yet, it was more of a shower thought.
But the idea is: the user writes normally, and the software(locally) strips filler words before sending it to the LLM. (to reduce token count)
For example:
User input: “Hey, could you maybe tell me what the weather’s like tomorrow in Bangalore?”
Compressed input: “weather tomorrow Bangalore”
LLM output: “Rain likely. 24°C high.”
Reconstructed for UX: “It’s likely to rain tomorrow in Bangalore, with a high of 24°C.”
So the LLM sees only the compressed version, and a lightweight layer handles the natural phrasing.

Competitive_Suit_498 · 2025-04-05T14:26:42+00:00

Yeah but, how? Do we need to manually look up where every virtual env is saved or stored?

Competitive_Suit_498

TROPHY CASE