Solana users can already utilise the in-built bridge on the $PLX bot to bridge their funds to MATIC and trade on Polymarket.
We are however working on a solution that will allow Solana users to trade Polymarket events directly with their SOL and erase the need for any funds bridging.
Stay tuned as we work on making PolyXbot the most advanced bot in the Polymarket ecosystem.
Few key updates for the next release cycle from the PolyXbot team:
1 - We are looking to upgrade our Solana and Polygon RPC's for an even quicker trade settlement. This will translate into a faster experience for all users.
2 - We are looking for more builders and volume based revenue (more details coming soon 👀) and this will be used to modify the flywheel allowing us to purchase back more $PLX tokens and burning them, reducing supply.
3 - We are looking to expand our PLX Score system to an X based agent allowing users to tag the PLX account for any prediction market mentioned in a tweet and get an instant detailed analysis and recommendation.
Please make any more suggestions you would love to see down below.
Top‑10 #Subnets in #Bittensor $Tao to lead 2026 (forecast) #NFA
1) SN64 @chutes_ai — “AWS‑like inference, crypto‑native rails.”
Why: Production inference with external distribution (OpenRouter provider), tons of model SKUs, and visible throughput claims. Fee model is obvious (per‑token usage). Watch: model quality/latency and cross‑provider routing economics.
2) SN51 https://t.co/PrlCSGd0rO — “Rent GPUs, instantly.”
Why: Straight‑line monetization (GPU rentals) with familiar UX; backend is SN51. TAM is rising with post‑DeepSeek demand spikes.
3) SN56 @gradients_ai — “Tune anything; sell fine‑tunes.”
Why: Self‑serve training funnels cash from SMBs/teams; complements SN51 + SN64. Execution cadence is strong.
4) SN35 Cartha (@0x_Markets ) — “On‑chain perps with AI liquidity.”
Why: Perps DEX is one of crypto’s biggest fee pools. Cartha LPs earn fees + emissions; 0xMarkets routes up to 500× leverage, fee split to LPs/treasury, buyback/burn on liquidations. If volumes ramp, revenues are immediate.
5) SN62 @ridges_ai — “Software engineering agents as a marketplace.”
Why: If they nail SWE‑bench/issue trackers with reproducible pipelines, the B2B dev‑ops spend is real. Codebase is active.
6) SN52 Dojo @TensorplexLabs — “Human feedback/data labeling substrate.” Why: Demand for RLHF/RLAIF datasets is chronic; Tensorplex is shipping; obvious fee line.
7) SN36 @AutoppiaAI — “Robotic Process Automation, but with agents.”
Why: Clear BPO automation ROI; IWA benchmarks and validator scoring make it productizable.
8) SN4 @TargonCompute — “Confidential, verifiable compute.”” Why: Enterprise security posture + recent funding momentum gives it a defensible wedge.
9) SN34 @bitmind — “Deepfake/AI‑content detection APIs.”
Why: EU/US platform policy + media platforms need detection; docs/APIs are live already.
10) SN54 MIID @yanez__ai — “Synthetic KYC & fraud stress‑testing.” Why: Banking/compliance budgets are large; MIID’s inorganic identity datasets map directly to anti‑fraud tooling.
On the bubble (credible challengers): SN44 Score (sports CV), SN41 Sportstensor (predictions), SN8 PTN (quant signals), SN43 Graphite (ops research), SN120 affine (RL), etc. — any of these can jump if distribution/fees harden.
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How I ranked things (short + strict)
Scorecard per subnet (0–100):
* Adoption rails (0–25): Are there real integrations or external users today (APIs, marketplaces, exchanges)?
* Revenue line clarity (0–25): Obvious paying customer(s) and fee taps (usage, LP fees, enterprise, API)?
* Moat & network effects (0–20): Data flywheels, validator quality, distribution lock‑in, hard tech.
* Execution signal (0–15): Code/docs cadence, teams funded/shipping, credible partners.
* Liquidity & emissions (0–15): Emission share, α pool depth / venues to support scale.
Method note: emissions ≠ revenue, so I weight adoption + revenue most. I also assume α tokens tend toward a 21M max supply (like TAO) per protocol design; that matters for long‑run FDV math.
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3–5 year “Unicorn” watchlist (working definition)
Definition: Achieve either α FDV ≥ $1B (21M max‑supply path ⇒ order‑of‑magnitude ≈$47.6 per α at full dilution) or annualized protocol revenue ≥ $100M with strong growth and defensible margins. (Protocol docs note that TAO and α tokens ultimately target 21M supply; FDV math follows.) They are:
Chutes (SN64) — If OpenRouter & direct API volumes keep compounding, it’s the clearest path to “AWS‑like” decentralized inference revenues.
https://t.co/PrlCSGd0rO (SN51) — GPU marketplace with straightforward paid demand; secular tailwinds in open‑weights.
Gradients (SN56) — Fine‑tune economy + enterprise adapters (data in, models out).
Cartha / 0xMarkets (SN35) — Perps DEX fee taps (LP fees, treasury take, liquidation economics). If daily volumes reach mid‑tier DEX territory, unicorn math is realistic.
Targon (SN4) — Confidential compute/attestation; enterprise contracts are lumpy but high‑margin.
Ridges (SN62) — SWE agents as CapEx savers; if they become the “Upwork for autonomous repos,” network effects kick in.
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Bottom line:
* Own/accumulate the infra with real customers: Chutes, Lium, Gradients.
* Add the “marketplaces for work”: Ridges (SWE), Autoppia (web tasks), Dojo (human feedback).
* Keep a DeFi fee‑engine: Cartha/0xMarkets into volume.
* Play the policy tailwind: MIID (compliance), BitMind (content auth).
#decentralizedAI $TAO #dtao #alphabetlore
Our community asked and we delivered.
Chinese language support has been added to the $PLX bot making it easier for the Asian community to use the bot.
Now you can interact with Polymarket much easier in whatever language suits you best.
Thank you for the great recommendation, and please let us know what more features you would like to see.
To enable it, simply type the /language command to switch between English and Chinese.
我们的社区提出了要求,而我们兑现了承诺。
$PLX 机器人现已新增中文语言支持,让亚洲社区使用起来更加方便。
现在,你可以用最适合你的语言,更轻松地与 Polymarket 互动。
感谢大家的精彩建议,也请继续告诉我们你希望看到的更多功能。
要启用中文,只需输入 /language 指令,在英文和中文之间切换即可。
🧠Introducing PLX Score — the AI-driven analysis layer for prediction markets.
Built into PolyXbot, PLX Score evaluates any Polymarket event using our proprietary AI engine — blending quantitative market data and qualitative real-world sentiment to generate actionable intelligence.
📊 Quantitative metrics: Orderbook depth, liquidity, spread, volume dynamics.
🗞️ Qualitative signals: News sentiment, social narratives, and historical patterns.
Each market is scored by the PLX AI Engine, which processes real-time data and assigns a composite PLX Score — guiding users toward optimal trading decisions with clarity and confidence.
This is more than analysis. It’s insight — driven by data, refined by AI. Powered by $PLX.
Try it yourself on any market in the PolyXbot Telegram bot.
💡 Example below: PLX Score’s take on the Nevada Governor Race 2026.
Good morning and happy Monday from the $PLX team.
We rolled out some critical updates over the weekend and we are now testing and gearing up to our most important update yet.
What if your PolyXbot could tell you everything you needed to know about a specific market......
More details coming soon.