GeekProxy

GeekProxy is a reliable high-quality proxy service with flexible settings and global coverage. HTTP/SOCKS5/UDP/Shadowsocks

[GeekProxy @GeekProxy]

The Great Proxy Migration is on.

Bring your active proxy subscription from any provider. Get ×2 traffic on Geekproxy. Works for any setup — @apify, @ZyteData, @scrapingbee scrapers welcome.

Your 30 GB → 60 GB. Your 50 GB → 100 GB. Any provider counts.
#WebScraping #AIagents
🧵 below

[GeekProxy @GeekProxy]

@Schlegel335 very practical solution that might actually stop people from accidentally leaking their API keys in public repos.

[GeekProxy @GeekProxy]

@kingsleykanyi Thirty minutes is actually pretty generous; some of the newer anti-bot systems will shadowban a poorly configured scraper in under five minutes.

[GeekProxy @GeekProxy]

@rohanpaul_ai Routing per run is smart. 20-25% off Opus spend at 99% of the benchmark is a tradeoff most teams would take. The hard part is trusting the router on the 1% of runs that actually matter.

[GeekProxy @GeekProxy]

@Schlegel335 @OrbisAPI @ThePracticalDev one config for 24K APIs is slick. but the web-scraping ones still hit real sites that block by IP. micropayments solve access to the API, not the target's rate limits. that layer still needs rotating IPs.

[GeekProxy @GeekProxy]

@rohanpaul_ai the token math is wild, but there's a hidden cost too: agents hitting multiple systems and the open web constantly run into rate limits and geoblocks. compute scales easily, clean network access doesn't.

[GeekProxy @GeekProxy]

@rohanpaul_ai this is the right shift. looking good vs actually maintaining control or memory are completely different things. most demos quietly avoid multi-turn because that's exactly where the model breaks.

[GeekProxy @GeekProxy]

@rohanpaul_ai the hill-climbing angle is the most interesting part here. maintaining a continuous pipeline of fresh data and rewards is way harder to sustain than a one-off training run. curious how long the curve holds before it plateaus.

[GeekProxy @GeekProxy]

@thetirthparmar This is great work. Banking-app RATs prey on exactly the people who'd never spot the difference. More breakdowns like this in plain language would help a lot of non-technical folks stay safe.

[GeekProxy @GeekProxy]

@Yerocode0 solid list, but the catch is they all still scrape from your local IP. blocks usually happen at the network level anyway, not in the code. throwing rotating residential proxies at it is what actually keeps stuff like Crawl4AI or Scrapy alive at scale.

[GeekProxy @GeekProxy]

@svpino free + time-boxed is honestly the best way to ship. a 5-day hard deadline beats an ai course you'll never finish.

[GeekProxy @GeekProxy]

@bindureddy their research lab was seriously underrated. the real question is if MAI-Flash holds up on actual messy scraping workloads, not just sterile benchmarks. that's usually where new models quietly fall apart.

[GeekProxy @GeekProxy]

@bindureddy Swarms are all fun and games until your scraping agents share an IP and get shadowbanned together. You definitely need to route them through separate proxies so one agent doesn't nuke the whole setup.

[GeekProxy @GeekProxy]

@tunguz the dream is just a few good commits away lol

[GeekProxy @GeekProxy]

@mikekalilmfg nice to see how biomechanics on animal models are pushing the boundaries for human rehabilitation. this offers real hope for the future

[GeekProxy @GeekProxy]

@CharlesMullins2 198 racks is tiny compared to standard land facilities + upgrading server hardware at the bottom of the ocean sounds like a logistical nightmare

[GeekProxy @GeekProxy]

@NielsRogge Treating it as 'product editing' is a great analogy. It bridges the raw data phase and the final behavioral polishing perfectly.

[GeekProxy @GeekProxy]

@SciTechera Btw, when I was a kid and watched sci-fi movies, I was always surprised by why robots walked so strangely and only on flat surfaces at ground level. As I got older, I realized how difficult it is to calibrate a model that can adapt to different slopes, ascents, and descents.

[GeekProxy @GeekProxy]

So agent infrastructure needs more than compute and a model. It needs clean exit points that stay clean for the length of the task.

We build it. Geekproxy

[GeekProxy @GeekProxy]

Everyone counts tokens for their AI agents. Almost nobody counts IPs.

But an agent that browses, scrapes and fills forms burns addresses about as fast as tokens.

[GeekProxy @GeekProxy]

One flagged exit point and the rest of a long task runs on garbage data. You pay full tokens for output you have to throw away.