Back

Rahul Agarwal

Founder | Agentic AI...ย โ€ขย 3h

3 ways AI systems are deployed today. Iโ€™ve explained each method below in simple steps. 1.) ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐——๐—ฒ๐—ฝ๐—น๐—ผ๐˜†๐—บ๐—ฒ๐—ป๐˜ (๐˜€๐˜๐—ฒ๐—ฝ-๐—ฏ๐˜†-๐˜€๐˜๐—ฒ๐—ฝ) ๐—™๐—น๐—ผ๐˜„: โ€ข ๐—จ๐˜€๐—ฒ๐—ฟ ๐˜€๐˜‚๐—ฏ๐—บ๐—ถ๐˜๐˜€ ๐—ฟ๐—ฒ๐—พ๐˜‚๐—ฒ๐˜€๐˜ - User types a query or command. โ€ข ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฟ๐—ผ๐˜‚๐˜๐—ถ๐—ป๐—ด โ€” Request travels through the internet to servers. โ€ข ๐—ค๐˜‚๐—ฒ๐—ฟ๐˜† ๐—ฟ๐—ฒ๐—ฎ๐—ฐ๐—ต๐—ฒ๐˜€ ๐—ฑ๐—ฎ๐˜๐—ฎ ๐—ฐ๐—ฒ๐—ป๐˜๐—ฒ๐—ฟ โ€” Request arrives at remote cloud facility. โ€ข ๐—”๐—น๐—น๐—ผ๐—ฐ๐—ฎ๐˜๐—ฒ ๐—š๐—ฃ๐—จ๐˜€/๐—ง๐—ฃ๐—จ๐˜€ โ€” Powerful hardware assigned for model processing. โ€ข ๐— ๐—ผ๐—ฑ๐—ฒ๐—น ๐—ฒ๐˜…๐—ฒ๐—ฐ๐˜‚๐˜๐—ถ๐—ผ๐—ป โ€” AI model runs and processes input data. โ€ข ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ฒ ๐—ฟ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ โ€” Model creates a suitable text or result. โ€ข ๐—ฆ๐—ฎ๐—ณ๐—ฒ๐˜๐˜† & ๐—บ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฐ๐—ต๐—ฒ๐—ฐ๐—ธ๐˜€ โ€” Filters remove unsafe or sensitive content. โ€ข ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐—ฒ ๐—ผ๐˜‚๐˜๐—ฝ๐˜‚๐˜ ๐˜๐—ผ๐—ธ๐—ฒ๐—ป๐˜€ โ€” Converts model result into final text output. โ€ข ๐—ฅ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ ๐—ฟ๐—ฒ๐˜๐˜‚๐—ฟ๐—ป๐—ฒ๐—ฑ ๐˜๐—ผ ๐˜‚๐˜€๐—ฒ๐—ฟ โ€” Sends final answer back to userโ€™s device. _____________________________________________ 2.) ๐—˜๐—ฑ๐—ด๐—ฒ ๐——๐—ฒ๐—ฝ๐—น๐—ผ๐˜†๐—บ๐—ฒ๐—ป๐˜ (๐˜€๐˜๐—ฒ๐—ฝ-๐—ฏ๐˜†-๐˜€๐˜๐—ฒ๐—ฝ) ๐—™๐—น๐—ผ๐˜„: โ€ข ๐—จ๐˜€๐—ฒ๐—ฟ ๐—ถ๐—ป๐—ฝ๐˜‚๐˜ ๐—ฟ๐—ฒ๐—ฐ๐—ฒ๐—ถ๐˜ƒ๐—ฒ๐—ฑ โ€” User sends a request via app. โ€ข ๐—˜๐—ฑ๐—ด๐—ฒ ๐—ฟ๐—ผ๐˜‚๐˜๐—ถ๐—ป๐—ด โ€” Request goes to the closest edge server. โ€ข ๐—ข๐—ฝ๐˜๐—ถ๐—บ๐—ถ๐˜‡๐—ฒ๐—ฑ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น ๐—น๐—ผ๐—ฎ๐—ฑ๐—ถ๐—ป๐—ด โ€” Loads a smaller, faster AI model. โ€ข ๐—Ÿ๐—ผ๐—ฐ๐—ฎ๐—น ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น ๐—ฒ๐˜…๐—ฒ๐—ฐ๐˜‚๐˜๐—ถ๐—ผ๐—ป โ€” Model processes data on the edge. โ€ข ๐—Ÿ๐—ฎ๐˜๐—ฒ๐—ป๐—ฐ๐˜†โ€“๐—ฎ๐—ฐ๐—ฐ๐˜‚๐—ฟ๐—ฎ๐—ฐ๐˜† ๐—ฏ๐—ฎ๐—น๐—ฎ๐—ป๐—ฐ๐—ฒ โ€” Trades some accuracy for quick output. โ€ข ๐—ฅ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป โ€” Edge server creates the final answer. โ€ข ๐—–๐—ฎ๐—ฐ๐—ต๐—ฒ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—น๐˜๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ฟ๐—ฒ๐˜‚๐˜€๐—ฒ โ€” Saves common results for next time. โ€ข ๐—ข๐˜‚๐˜๐—ฝ๐˜‚๐˜ ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜† โ€” Sends response back to the userโ€™s device. โ€ข ๐—ค๐˜‚๐—ถ๐—ฐ๐—ธ ๐—ฟ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ ๐—ผ๐—ฏ๐˜€๐—ฒ๐—ฟ๐˜ƒ๐—ฒ๐—ฑ โ€” User gets results almost instantly. _____________________________________________ 3.) ๐—ข๐—ป-๐——๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ ๐——๐—ฒ๐—ฝ๐—น๐—ผ๐˜†๐—บ๐—ฒ๐—ป๐˜ (๐˜€๐˜๐—ฒ๐—ฝ-๐—ฏ๐˜†-๐˜€๐˜๐—ฒ๐—ฝ) ๐—™๐—น๐—ผ๐˜„: โ€ข ๐—จ๐˜€๐—ฒ๐—ฟ ๐—ถ๐—ป๐—ฝ๐˜‚๐˜ ๐—ผ๐—ป ๐—ฑ๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ โ€” User asks a question or gives a command. โ€ข ๐——๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ ๐—ฟ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ ๐—ฐ๐—ต๐—ฒ๐—ฐ๐—ธ โ€” App checks memory, CPU, and GPU status. โ€ข ๐—ฉ๐—ฒ๐—ฟ๐—ถ๐—ณ๐˜† ๐—บ๐—ฒ๐—บ๐—ผ๐—ฟ๐˜† ๐—ฎ๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜† โ€” Confirms enough space to load the model. โ€ข ๐—–๐—ต๐—ฒ๐—ฐ๐—ธ ๐—–๐—ฃ๐—จ/๐—š๐—ฃ๐—จ ๐—ฐ๐—ฎ๐—ฝ๐—ฎ๐—ฐ๐—ถ๐˜๐˜† โ€” Ensures device can handle model tasks. โ€ข ๐—Ÿ๐—ผ๐—ฐ๐—ฎ๐—น ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น ๐—ฒ๐˜…๐—ฒ๐—ฐ๐˜‚๐˜๐—ถ๐—ผ๐—ป โ€” Model runs fully on the device. โ€ข ๐—ฅ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—น๐—ผ๐—ฐ๐—ฎ๐—น๐—น๐˜† โ€” Model creates the answer offline. โ€ข ๐—™๐—ถ๐—น๐˜๐—ฒ๐—ฟ ๐—น๐—ผ๐—ฐ๐—ฎ๐—น๐—น๐˜† โ€” Runs safety filters on the device. โ€ข ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐—ฒ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ฐ๐˜ ๐˜๐—ผ๐—ธ๐—ฒ๐—ป๐˜€ โ€” Generates lightweight output for display. โ€ข ๐—ฅ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ ๐˜€๐—ต๐—ผ๐˜„๐—ป ๐—ถ๐—บ๐—บ๐—ฒ๐—ฑ๐—ถ๐—ฎ๐˜๐—ฒ๐—น๐˜† โ€” User gets instant, private results offline. โœ… ๐—›๐—ผ๐˜„ ๐˜๐—ผ ๐—ฐ๐—ต๐—ผ๐—ผ๐˜€๐—ฒ (๐˜€๐—ถ๐—บ๐—ฝ๐—น๐—ฒ ๐—ฐ๐—ต๐—ฒ๐—ฐ๐—ธ๐—น๐—ถ๐˜€๐˜)? โ€ข Need maximum accuracy or heavy processing? โ†’ ๐—–๐—น๐—ผ๐˜‚๐—ฑ. โ€ข Need lower latency and regional performance? โ†’ ๐—˜๐—ฑ๐—ด๐—ฒ. โ€ข Need privacy/offline and instant replies? โ†’ ๐—ข๐—ป-๐—ฑ๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ. โœ… Repost for others in your network who can benefit from this.

Reply
2

More like this

Recommendations from Medial

Image Description

Rahul Agarwal

Founder | Agentic AI...ย โ€ขย 3d

4 different ways of training LLM's. I've given a simple detailed explanation below. 1.) ๐—”๐—ฐ๐—ฐ๐˜‚๐—ฟ๐—ฎ๐˜๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—–๐˜‚๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป (๐˜€๐˜๐—ฒ๐—ฝ-๐—ฏ๐˜†-๐˜€๐˜๐—ฒ๐—ฝ) Prepares clean, consistent, and useful data so the model learns effectively. 1. Collect text

See More
Reply
1
9
1
Image Description
Image Description

Rahul Agarwal

Founder | Agentic AI...ย โ€ขย 2m

3 ways how most AI systems are built. Iโ€™ve explained each one step-by-step. 1) ๐—ง๐—ฟ๐—ฎ๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—”๐—œ (๐˜€๐˜๐—ฒ๐—ฝ-๐—ฏ๐˜†-๐˜€๐˜๐—ฒ๐—ฝ) 1. ๐—ฆ๐—ฒ๐˜ ๐˜๐—ฎ๐˜€๐—ธ โ€“ Decide what problem the model should solve. 2. ๐—–๐—ผ๐—น๐—น๐—ฒ๐—ฐ๐˜ ๐—ฑ๐—ฎ๐˜๐—ฎ โ€“ Gather lots of example

See More
1 Reply
8
17
1

Download the medial app to read full posts, comements and news.