Bitrecs retweeted
Novelty Search tonight.
2 protocol upgrades to Subtensor.
Conviction + TAO Flow V2
2 subnet teams building on Bittensor.
\\ @cacheon_ai :: #SN14
\\ @Bitrecs :: #SN122
Live via Bittensor Discord
Hosted by @const_reborn
9PM UTC / 5PM EDT
Bitrecs retweeted
Over 5mo ago, @const_reborn said we should see @Bitrecs become SOTA in shop recommendations.
It looks like that’s already starting to happen.
Bitrecs tested miners on the Amazon All Beauty ecommerce dataset, measured with NDCG@10.
Their bittensor-powered recommendation models are already scoring higher than some published SOTA results on that benchmark:
> gemma-3-27b-it: 0.20
> MiMo-V2-Flash-TEE: 0.13
> published SOTA: 0.06–0.09
The interesting part is that the models are doing this without being specially trained on that exact task first. They’re using LLMs to rank products directly.
They started with a smaller curated set of 100 products. Next is:
100 → 500 → 1,000 → full catalog
Bitrecs could become one of the strongest AI recommendation engines for ecommerce.
Bittensor | $TAO
Like I’ve always said, we need more subnets with real products solving real-world problems for everyday users.
To be honest, I didn't pay much attention to SN122 @Bitrecs until the Stitch brief, but now I’m actually intrigued.
What they’re doing is, helping online stores recommend better products to customers using AI.
Ever wondered why you go on Amazon and see products you actually need being recommended to you?
That’s because Amazon has one of the most powerful recommendation systems in ecommerce, but it’s centralized.
With @Bitrecs, a regular store owner doesn’t need to build their own AI recommendation system. Bitrecs gives them access to enterprise-grade recommendation AI.
And not just any recommendation AI, one powered by a network of miners competing to create better recommendation models and prompts, meaning it keeps improving over time.
With Bitrecs, merchants can:
> add AI product recommendations to their store
> use modern, clean recommendation layouts
> track performance through analytics and dashboards
> choose which AI models power recommendations
> install it easily
Any merchant or business owner can use Bitrecs. They’re already driving value for 100+ merchants and are targeting 1000+ merchants.
Their miners are also scoring high on NDCG@10, which means they’re moving closer to SOTA-level recommendation performance.
Ngl, I love seeing deAI and Bittensor being used by everyday users like this.
Keep cooking, Bitrecs.
Bitrecs retweeted
Replying to @Bitrecs
@Bitrecs (Bittensor SN122) is an AI powered product recommendation engine built for ecommerce and V2 changes how recommendation systems are built entirely.
Instead of a static model, miners compete to craft the highest-performing prompt artifact. Validators score submissions on-chain. The winner gets deployed to live Shopify stores via Winner-Takes-All. Real shopper data feeds the next round. The system gets smarter with every transaction.
Key strengths:
🧠 Multi-LLM intelligence combines ChatGPT, Claude, Gemini, Grok, Kimi, Qwen & more
🔄 Self improving flywheel every sale improves the next prompt competition
🔗 Decentralized inference powered by CHUTES (SN64) for model routing
🔒 Privacy preserving zero PII or customer data collected
🛒 Plug and play one-click install for Shopify & WooCommerce
📈 Proven results merchants reporting up to 15% AOV lift













