Austin Barack retweetet
tao reflexivity drastically misunderstood
kel.@kelxyz_
tao reflexivity drastically misunderstood
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Austin Barack
8.5K posts
Austin Barack
@AustinBarack
Founder and Managing Partner @relayercapital. Previously Partner @coinfund_io. Supporting founders w/ protocol design, gtm, and tokenomics. nfa/dyor
Onchain Beigetreten Şubat 2017
4.6K Folgt21.1K Follower
Value comes from owning the rails or owning the user. If you’re in the middle it’s hard to capture value and easy to be disintermediated.
Hyperliquid is the unique protocol/application to have done both.
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Austin Barack retweetet
✅Etherfi buybacks are back on (no clue why they were off for a few days)
✅ Final investor vest sent out. No more VC overhang.
✅ Daily spend at ATH using cards ($2.5M/d)
✅ Staking TVL back above $6b
✅ Upbit listing yesterday
✅ Adding ~300 new cards a day
✅ CAC going down, ARPU going up, Payback period compressing
sallygazzy mode
note: dcf cap seeded ethfi
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House of all finance
Tokens on Solana@tokens
JUST IN: Hyperliquid now trades more oil, gold, and silver than crypto.
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Templar at the market cap peak of Virtuals from early 2025 is $SN3 at $1,093.07
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Templar was just discussed on the @theallinpod in a conversation with the founder of Nvidia Jensen Huang as a technical breakthrough for AI training. Jensen also said he believes decentralized and open models to be just as critical as closed source models.
$SN3 looks set to make a new high and go on a real run as the market starts pricing it to the size of the opportunity
Austin Barack@AustinBarack
Templar completed the largest distributed and open LLM pre-training run in history. $SN3 is trading at a $40MM mcap. Right now it is not yet listed on any CEXs. A lot of alpha just researching what's interesting and leaning into onchain friction points before it is easy
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Austin Barack retweetet
"Every major AI platform today runs on the same basic trust assumption. You have to trust the provider to handle your data responsibly."
^^^ This doesn't actually capture the issue correctly.
The question is not whether platforms "handle your data responsibly"
The question is whether platforms handle your data at all.
If it's handled, privacy is already lost.
Delphi Digital@Delphi_Digital
Venice just shipped end-to-end encrypted AI inference. Every major AI platform today runs on the same basic trust assumption. You have to trust the provider to handle your data responsibly. @AskVenice has operated with a slightly different architecture. Conversations are stored locally on your device and prompts are not persisted server-side. When you use frontier models, Venice proxies the request so the provider never receives your identity data. However, the same trust assumptions still apply here. If Venice or a partner wanted to intercept data, nothing in the architecture would prevent it. The new launch introduces two hardware-enforced privacy modes. TEE runs inference inside secure hardware enclaves operated by NEAR AI Cloud and Phala Network, isolating computation from the host OS and infrastructure operator. Remote attestation ties a cryptographic certificate to the physical hardware so anyone can independently verify the model is running inside a genuine enclave. You no longer need to trust the GPU operator but you are still trusting Venice's transit layer. E2EE removes that remaining trust assumption. Prompts are encrypted on device before transmission, stay encrypted through Venice's infrastructure, and only decrypt inside the verified enclave. Venice cannot see your data at any point during normal operation. The tradeoff is that responses may be slower, web search and memory are disabled since they would require decryption outside the enclave. Both modes currently run on a handful of open source models through NEAR AI Cloud and Phala Network and are exclusive to Pro subscribers. How robust these guarantees are in practice depends on the attestation implementation and whether independent audits confirm the claims.
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Based on the pace of new product releases and the number of times people (that are not in crypto) have told me about using Venice (they brought it up independently), I would guess Venice hits their next million new users in half the time again (and so on).
ChatGPT is closing in on 1 billion weekly active users and @AskVenice is in my opinion the clear leader in private AI usage. 23% of internet users use VPNs to give you a sense for the size of the opportunity here (and interactions with LLMs arguably involve much more sensitive data and fewer standard privacy protections).
Considering the above opportunity, I think we could see Venice hit 10 million users by end of year and 50 million users by 2028 in a bull case. Now think about how much revenue will be generated and $VVV will be burned
Venice@AskVenice
Today we passed 2,000,000 registered users on Venice 13 months to our first million. Half that to the next To every builder, creator, and free thinker who choose privacy: this is your milestone The uncensorable are unstoppable
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Austin Barack retweetet
Austin Barack retweetet
Bittensor peeps: check out 31:44 - Templar sn3 discussed.
@chamath -- they've achieved a *72* billion parameter model with decentralized training, not a 4 billion parameter model :)
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Austin Barack retweetet
It’s been great working with the @askvenice team to bring verifiable privacy to users that need it most!
Users need to prove their data isn’t beaing leaked to third-party inference providers and this integration makes that possible.
Excited to become a Venice power user 🚀
Venice@AskVenice
Venice AI just released End-to-End Encryption Verifiable by any external party Vires in numeris Here's how it works 🧵
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Austin Barack retweetet
Venice just went Phala-grade on privacy.
Their new TEE mode runs inside hardware-isolated enclaves powered by Phala, with cryptographic proof via remote attestation.
Huge congrats to @AskVenice! 🍾🥂
Venice@AskVenice
Venice AI just released End-to-End Encryption Verifiable by any external party Vires in numeris Here's how it works 🧵
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Austin Barack retweetet
So, basically, the only perennial FUD point for VVV just evaporated.
Externally verifiable privacy for your LLM usage. Finally. Time to level up.
“Every major AI company stores your conversations. Every prompt, every response. Saved, analyzed, and available to employees, third-parties, hackers, and governments.
We believe ubiquitous mass surveillance is an unethical foundation on which to build society.
So Venice was built on a different principle: you don't need to protect what you don't have”
Vires in numeris.
Venice@AskVenice
Venice AI just released End-to-End Encryption Verifiable by any external party Vires in numeris Here's how it works 🧵
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Austin Barack retweetet
It may be obvious in hindsight that we actually built crypto for the machines
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Austin Barack retweetet
NEAR AI's confidential inference now brings @AskVenice users verifiable privacy 👇
Venice@AskVenice
Venice AI just released End-to-End Encryption Verifiable by any external party Vires in numeris Here's how it works 🧵
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AI for everyday consumers with the highest degree of privacy.
2 million Venice users is just scratching the surface.
$VVV continues to be one of my highest conviction tokens for 2026 and with this I'm even more excited about the opportunity.
Venice@AskVenice
Venice AI just released End-to-End Encryption Verifiable by any external party Vires in numeris Here's how it works 🧵
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Austin Barack retweetet
MiniMax M2.7 is now live in Venice (both API and web)
Potentially the best cost/performance model for your @openclaw
Ofek Shaked@VibeCoderOfek
MiniMax just dropped M2.7 and it’s legitimately scary: “88% win-rate vs M2.5… 56.22% SWE-Pro… on par with Sonnet 4.6 in OpenClaw… reduced intervention time to 3 minutes.” Self-evolving agentic model at 1/3 the cost of frontier stuff. The coding arms race just got faster. Who’s testing this first?
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Austin Barack retweetet
A thread on why *insert incumbent broker / exchange will not be able to start innovating like prime steve jobs and outcompete Hyperliquid.
The Incompatability Problem:
MONK@defi_monk
All of a sudden y’all are expecting traditional exchanges who are literally the textbook examples of heavy, slow, incumbent organizations bogged down by regulation to start innovating like prime steve jobs or something
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