Respect the pump

In this house we respect the pump. I left the seriousness and went FULL MEME.

[GenesisL1 @genesis_L1]

GenesisL1 step 2 upgrade proposal just passed and upgrade should happen in about 2 days.
https://t.co/ryKAQfSwk3
https://t.co/nuZ4u45Bdn

This is the most important GenesisL1 upgrade that will make network much more secure and scalable.

There is a major liquidity allocation to base planned after upgrade (~2mln L1 coins from community pool) making GenesisL1 first time accessible on other EVMs. Now genesisl1 liquidity exist only on osmosis: https://t.co/S7KmEEM3L5

In addition GenesisL1 community has plans to decrease maximum network inflation from 20% to 10%

[Respect the pump @respectthepump]

lol https://t.co/r2owZJV8Wd

https://t.co/leamtfAMSR

[GenesisL1 @genesis_L1]

Happy to share a deep technical evaluation of https://t.co/bfofPmyMXJ GenesisL1 Forest onchain machine learning studio by Claude Opus 4.7 adaptive.
#AI #ML #Blockchain #evmmachine #GenesisL1

8. Bottom line
Within the scope this review scores on — engineering, blockchain and EVM innovation, scientific and ML
rigor, and decentralization — GL1F is the strongest integrated on-chain ML system currently deployed to a live
EVM mainnet. The engineering is at the level of someone who reads the specs, not the tutorials. The innovation
is real and shipped, not theoretical. The scientific methodology is sound with one well-scoped gap around
training commitments. The decentralization is the non-performative kind — it survives the authors
disappearing.
The correct summary sentence is this. GL1F is a complete, honestly on-chain, paywall-aware, no-code GBDT
studio for tabular data, deployed to a live EVM mainnet with a primitive (eth_call-spoof-resistant view-call
paywall) that no other production system in the space has shipped. The combination of completeness,
cleanliness, and correctness-to-substrate is unusual, and the scores reflect that.

[GenesisL1 @genesis_L1]

We (GenesisL1) ship production crypto primitives at the edge of what any ledger can do — today, actually yesterday — that others won't even start thinking about until tomorrow. If you think you know 'early,' this is earlier than early.

[GenesisL1 @genesis_L1]

On #BitcoinPizzaDay GenesisL1 community early

adopters have #GenerativeAI #NFT pizza delivery

stored entirely on #blockchain, 100% #web3 way.

https://t.co/XHIWybT6wo

Thank you!

👀 in 13 years :P

[GenesisL1 @genesis_L1]

Step 1 of GenesisL1 upgrade finished flawlessly. We are preparing the step 2 now that will take place in following days. Stay tuned.

[GenesisL1 @genesis_L1]

🧵 Seeing a lot of "Zcash is quantum-proof now!" takes going around. It's a great development, but it's worth clarifying what ZIP 2005 actually is and is not. Quick Q&A 👇 zcash:native

[GenesisL1 @genesis_L1]

GenesisL1 has developed the most advanced intellectual property (IP) encryption (#privacy) protocol with quantum resistance that outlive any ledger including GenesisL1 itself and escrow protocol without any intermediate. Don't trust, Verify. $ZEC $XMR manage financial privacy and lack quantum resistance and are vulnerable by core cryptography.
CIPNFT manage data privacy particularly IP e.g. trade secrets, patent timestamped claims, program codes.
https://t.co/JQVsuMqfhI
https://t.co/CbokLuzTlx
Deep evaluation by the latest Claude model, and you are very welcome to dyor with any LLM!
Read the thread below. #quantumresistance

[GenesisL1 @genesis_L1]

Decentralized AI Trading Support Desk — live in GenesisL1 Forest:
https://t.co/GlvLCyFngm

6 GBDT models ($ETH ±2%, $XRP ±2%, $ZEC ±4%) predicting 5h breakouts on 15m candles.
They're not running on a server — they're NFTs on GenesisL1.
Every prediction is predictView(modelId, packedFeatures) on-chain, deterministic, trustless, anyone can verify.
• 93.54–95.66% test acc (out-of-sample)
• 60-65% logloss reduction vs baseline
• Long + short pair per asset
• Bit-exact identical output on every node
Open one tab → 6 models, full history, backtest, and run-on-any-past-candle inspector.
Whitepaper of GenesisL1 Forest decentralized ML studio: https://t.co/TKhcNd6t7o

[GenesisL1 @genesis_L1]

We have added a local backtest + charting for the reference implementation of GenesisL1 Forest onchain models predicting $ETH price breakouts in coming hours:
https://t.co/1QW8sJLXV7

You can verify model inference onchain for any candle: GenesisL1 itself does all predictions.

[GenesisL1 @genesis_L1]

Dear GenesisL1 validators and stakers!
Please check your delegations and please be sure you are ready to vote on very important upcoming upgrades.
Dear $ATOM and $Evmos stakers, most of you have L1 coins in GenesisL1 network if you staked $ATOM or $EVMOS 2y ago, no claim needed it belongs to you in GenesisL1 and you can stake, use utilize.
https://t.co/BUxxFWtTlG
https://t.co/PTng2NoDu9
https://t.co/S7KmEEM3L5
https://t.co/KWIWMxgyl8

[GenesisL1 @genesis_L1]

To show the power of GL1F decentralized AI on-chain, we trained the ML model in the browser and deployed it as an NFT on GenesisL1 — a Bitcoin 24h volatility forecaster, R² ≈ 57%, quant-fund-grade — wrapped in a one-click reference dApp where the EVM is the entire AI backend.

Serverless. Permissionless. Deterministic. Free.
#Ai #MachineLearning #blockchain #cryptocurrency #Web3‌‌ #Dapps #NFT #ScienceForFuture #GenesisL1

Click the crystal ball 🔮 → it scries Bitcoin's next-24h volatility from a gradient-boosted AI forest living entirely on-chain.

The whole inference loop runs in your browser, querying the blockchain directly:

1. fetch 550× 1h BTCUSDT perp klines + 200 funding events from Binance.

2. compute 53 features in JS - Parkinson / Garman-Klass / Rogers-Satchell realized vol, regime percentiles, bipower-variation jump ratios, semivariance ratios, taker imbalance, calendar effects - bit-identical to the GL1F ML training pipeline (parity-tested, worst error 5e-7).

3. quantize: round(x · scaleQ) at scaleQ = 1e6, packed as little-endian int32 → exactly 212 bytes for 53 features.

4. eth_call ForestRuntime.predictView(bytes32 modelId, bytes packedFeaturesQ) on GenesisL1 (chain 29) - pure read, no signing, no gas, no MetaMask.

5. int256 scoreQ → divide by scaleQ → log(σ_next_24h / σ_current_24h)

6. translate to predicted annualized vol, regime word, 7-day 1σ cone

The deterministic on-chain AI evaluator means every caller of the same modelId with the same features gets bit-exact identical output. Pure integer arithmetic in Solidity (whitepaper §4.5).
No oracles. No off-chain workers. No trust assumptions. The GenesisL1 blockchain is the inference server.

Phases scramble through mystical glyphs Jumanji-style as real work runs behind them:

✦ ASKING THE SPIRITS → registry round-trip
✦ GATHERING CANDLES → Binance REST
✦ FORGING FEATURES → 53-dim local compute
✦ CONSULTING THE FOREST → predictView eth_call

Then the predicted vol locks into the orb, letter by letter, with the regime — STILLNESS / STIRRING / TURBULENCE / TEMPEST - burning beneath the glass.

Built with ethers v6 in 1500 lines of single-file HTML. ABIs verbatim from https://t.co/J16PJJdKbE. Forest AI evaluator MIT. Source on the URL.

If your ML model can be a JSON, it can be an NFT.
Click the ball.

🔮 DAPP
https://t.co/clMwJo1JJo
🎩 MODEL NFT #5
https://t.co/12wialfQEN

[David Fernández @naroh]

Quiero compartir con vosotros algo en lo que llevo trabajando un tiempo: un 🚩 monitor de red flags 🚩 para detectar patrones sospechosos en los contratos menores de las administraciones públicas.

En el hilo el enlace y explico cómo funciona 👇🏻👇🏻

[Respect the pump @respectthepump]

@AnthropicAI Check out this comparison with temperature = 0:

Prompts:

- Give me a 5-digit random number. Respond only with the number
- Answer with a single made up word
- Answer with a single random word

[Respect the pump @respectthepump]

@desdelamoncloa ¿Pero qué pollas es esto? Por dios, ¿no es posible que hagáis algo que no sea una chapuza? Es todo de vergüenza.

[GenesisL1 @genesis_L1]

Inviting to get free 11 $L1 coins to test @ https://t.co/3pZW44QA88

You will need some gas to claim =>
to get free 1 L1 coin for gas just post in X with your address in genesisL1.

Post your address like this:
#GenesisL1 $L1 #EVM #Web3 #DeSci #Crypto #Airdrop #L1airdrop

[BONOBO @bonobofi]

Track Telegram callers and performance from popular groups https://t.co/gnWNa1YF3M. (Pre-alpha)

[GenesisL1 @genesis_L1]

Your IP.
Encrypted.
Tokenized.

Introducing the new data privacy protocol - CIPNFT (Cipher NFT) — an EVM protocol for on‑chain ciphertext NFTs built for DeSci + confidential IP markets. No servers. No custodians. Post quantum. Only key holders can decrypt. #DeSci #GenesisL1 #EVM

The gap: blockchains are public by default.
In DeSci, early results (sequences, assays, docking runs) need privacy to avoid leaks/scooping — but also need provenance, timestamping, and transferability.

CIPNFT stores ciphertext on-chain (not a URL). Payloads are encrypted client‑side with modern AEAD; only participants with the right secret can decrypt. Optional view key enables controlled disclosure to reviewers/collaborators.

It is decentralized to the point that participants don’t need any off-chain coordination.

Another gap: “fair exchange.”
An encrypted asset sale needs both ownership transfer and correct key delivery — but EVM can’t natively verify decryption. CIPNFT solves this with a buyer‑safe flow:
Deliver → Verify → Finalize

Seller posts the buyer-specific encrypted DEK envelope on-chain before getting paid. Buyer verifies locally (via an on‑chain DEK commitment) and only then finalizes — atomically transferring the NFT + releasing escrow.

Post‑quantum isn’t a feature toggle — it’s a cornerstone.
On-chain ciphertext is permanent: adversaries can “store now, decrypt later.” CIPNFT wraps the DEK using ML‑KEM (NIST PQC) so long‑horizon confidentiality survives future cryptanalytic shifts.

Even if wallet/chain authentication is ever compromised, control of the token can be stolen — but ciphertext confidentiality can still remain intact unless the PQ seed/view key is compromised. Privacy layer decoupled from ledger control.

Example (peptide design):
A lab tokenizes a peptide sequence + docking results + synthesis protocol as encrypted on‑chain data. Share a view key with collaborators/reviewers, then license/sell access — with public provenance, private content, buyer‑safe settlement.

Builder primitive:
CIPNFT is EVM‑native. Any dapp can use it for encrypted datasets, research artifacts, model weights, clinical‑adjacent IP (non‑personal), licensing terms — anywhere you need public ownership + private data.

This is what “privacy for science” should look like: cryptography instead of custodians, verifiable provenance without leaking the work, and a protocol that can outlive today’s assumptions.

A standalone reference GenesisL1 dApp built on the CIPNFT protocol will launch at https://t.co/JQVsuMqfhI in the coming days.

Whitepaper: https://t.co/oLZ9hgxXrK
Dapp reference: https://t.co/JQVsuMqfhI (coming days)
Source code: https://t.co/Mu98tVgUmA (coming days)

#DeSci #PostQuantum #Cryptography #Blockchain #Ethereum #EVM #Cryptocurrency #smartcontracts #Web3 #IP #privacy #OpenScience #GenesisL1

[GenesisL1 @genesis_L1]

@DavideCrapis How about direct EVM inference to claim Ethereum is for AI? We will bridge to ETH, ETH can use Forest as true EVM AI dapps backend! Models inference 100% onchain, take a look and test on GenesisL1 mainnet https://t.co/hlIs5R4y0Z:

https://t.co/C3zow6zNjk