Thread Writer || Content Creator || Artist || Researcher
Joined June 2023
- Tweets8.9K
- Following2.5K
- Followers2.5K
- Likes23.8K
Hold on guys, and think about this.
Look at Web3, where everyone is working just to make money, chasing new airdrops every single day.
You give the most important time of your life to these projects, and in the end, you either get flagged as "not eligible" or you end up earning just a few dollars.
Now, imagine if you had learned a real skill instead-you wouldn't have to stress or worry about airdrops at all.
That’s why you need to focus on building skills. The airdrop era is gradually coming to an end, and you are wasting your precious time, money, and health on it.
I’m not saying you should quit completely, but do not make it your main source of income.
Airdrops are either ending soon, or they are about to turn into mere pocket change (peanuts).
Gprove Succinct Ogs 🩷.
Huge congrats to Succinct’s Rahul Dalal, one of the cryptographers behind FlashProve, @AnthropicAI’s provable inference system built on zkSNARKs.
Why: Today, AI runs on a “just trust me” model. Users can’t verify that a response came from the model they chose, or that an attacker didn’t tamper with it along the way. As AI takes on higher-stakes work, that create tension for users, labs, and regulators alike.
What: Researchers from Anthropic, EPFL, MIT, and @SuccinctLabs built FlashProve, a system that lets a model provider commit to a specific model and then prove each response was produced by it, without revealing the weights. Under the hood, it uses zkSNARKs, the same cryptographic technology Succinct uses to secure $13.5B in deposits on Ethereum L2s.
So What: FlashProve proved Llama 4 Maverick, a 400B-parameter LLM, at 110 tokens/sec on a single H100 GPU, with ~19 MB proofs. That puts proving at roughly 70 to 95x the cost of running the model. The previous standard for the same model was ~0.02 tokens/sec.
What’s Next: FlashProve is still a research prototype, but it’s a step change toward the question we asked with Flock earlier this year: how close can proving get to computing? The closer it gets, the less reason there is to release any output without a proof attached.
Congrats again to Rahul and the FlashProve team, and great to see @Starknet, @Mantle_Official (proven by Succinct), and several zkML projects cited.
0xINFO HUB retweeted
Huge congrats to Succinct’s Rahul Dalal, one of the cryptographers behind FlashProve, @AnthropicAI’s provable inference system built on zkSNARKs.
Why: Today, AI runs on a “just trust me” model. Users can’t verify that a response came from the model they chose, or that an attacker didn’t tamper with it along the way. As AI takes on higher-stakes work, that create tension for users, labs, and regulators alike.
What: Researchers from Anthropic, EPFL, MIT, and @SuccinctLabs built FlashProve, a system that lets a model provider commit to a specific model and then prove each response was produced by it, without revealing the weights. Under the hood, it uses zkSNARKs, the same cryptographic technology Succinct uses to secure $13.5B in deposits on Ethereum L2s.
So What: FlashProve proved Llama 4 Maverick, a 400B-parameter LLM, at 110 tokens/sec on a single H100 GPU, with ~19 MB proofs. That puts proving at roughly 70 to 95x the cost of running the model. The previous standard for the same model was ~0.02 tokens/sec.
What’s Next: FlashProve is still a research prototype, but it’s a step change toward the question we asked with Flock earlier this year: how close can proving get to computing? The closer it gets, the less reason there is to release any output without a proof attached.
Congrats again to Rahul and the FlashProve team, and great to see @Starknet, @Mantle_Official (proven by Succinct), and several zkML projects cited.
Trust the process
Trust the @inkonchain
Trust the $ink
Binance confirmed that hackers used a fake job interview and an “internal AI tool” to gain access to an employee’s laptop and reach internal crypto wallets.
This was a classic social engineering attack. In crypto, the human layer remains one of the weakest points. Fake recruiters, fake interviews, and malware disguised as internal tools are becoming common.
Without cold wallets, multi-sig, and strict device policies, internal systems are highly vulnerable.
JUST IN: Binance says hackers used a fake job interview to hack an employee and gain access to its internal crypto wallets.
0xINFO HUB retweeted
gm 𝕏 family ☕️
still here!
still building!!
we dont fold , we build through every cycle!!!
Happy Tuesday 🍂 🧡
Art by ITIA
Want to know the ugly truth about "big" Crypto Twitter KOLs?
A project recently hired 200+ KOLs with over 10 Million combined followers. Every single one had a 400+ Ethos score and 100+ Smart Followers. They all posted twice.
The final result? Only 280 NFTs sold at $5.
Why? Because botted followers and engagement pods don't buy anything. It's the same accounts recycling likes and AI-generated replies to look influential while hiding their referral links because nobody clicks them.
Stop paying for fake numbers. Build a real community instead.