Read and subscribe to Grayscale's crypto research blog The Stack grayscale.com/the-stack

The fight that made Zcash possible

Nothing to see here. Just The Zcash ETF $ZCSH crossing $1 BILLION in AUM. AUM for the world’s first $ZEC fund has nearly tripled in just one month since launching. Onwards.

The infrastructure powering AI was also built for Bitcoin. @Hut8Corp, @Core_Scientific, @RiotPlatforms, @TeraWulfInc, @CipherInc and others built years of power, land, and grid-connected capacity for mining. That same infrastructure is now fueling the massive demand for AI compute boom. Across these mining companies, thousands of megawatts are still available and being contracted. $GCPU gives investors exposure to the companies building and operating AI's physical layer. For GCPU's current holdings, please visit etfs.grayscale.com/gcpu

Hyperscalers control ~70% of compute capacity today but the bigger opportunity may be in the specialists ⬇️

When you spend all night looking at Solana data

Stablecoins are a great way to hold dollars

Tokenized equity trading on @RobinhoodApp, @BNBCHAIN, and @solana has been on the rise, and the SEC just issued its Innovation Exemption. The order allows onchain trading of tokenized stocks in a manner consistent with US securities laws. Grayscale Research believes it shows that blockchain infrastructure can benefit US markets while remaining fully compliant. Read more on the Innovation Exemption here: grayscale.com/the-stack/sec-…

Always a good hang with the @therollupco team Thanks @avax for hosting an excellent event

$STRC vs $BTC

Zcash $ZEC through the highs

Grayscale’s compute bottleneck thesis is on point: Inference demand is colliding with grid queues, permits, transformers, and political resistance. Owners of already-energized capacity capture the rents. Their note also names the other side of that market: decentralized GPU marketplaces like Akash. We don’t wait 5 years for a new campus. We put unused, already-powered GPUs to work -- from data centers, miners, and Homenodes -- and price them in an open marketplace.

Onchain ≠ public. Spend from shielded ZEC with Zodl CrossPay and the person you're paying receives BTC, stablecoins, and more. All without putting your wallet on display.

Let's just say the timing seems good $SUI 🇸🇬

Grayscale AI Compute ETF (Ticker: $GCPU) is now trading. Why AI Compute? ⟶ AI's growth is constrained by physical compute. Data centers have just six months of capacity¹, and new ones take two to five years to build². ⟶ AI infrastructure capex is projected to exceed $1 trillion annually³. ⟶ $GCPU portfolio includes native data center businesses, plus operators repurposing existing power and land for AI, including Bitcoin miners. $GCPU offers exposure to AI’s physical layer, now accessible through brokerage or investment accounts. Learn more: etfs.grayscale.com/gcpu

Hyperliquid is now one of the largest perps exchanges by open interest 😯 It's likely coming to the US in a deal with Kraken/Payward using permissioned HIP-3* markets Blog post from @grayscalemzhao: grayscale.com/the-stack/hype…

Head of Research at @Grayscale, Zach Pandl, shares his take on the dark side of the force in AI and what defends against it: "This is a megatrend in society well beyond crypto, well beyond technology investors" "We are AI optimists, we count ourselves among the excited and enthusiastic about AI. That being said, new technology does create new risks." "There's a kind of dark side of the force, and surveillance risks are an important one. We need to think about what are the tools that help us defend ourselves, that give users autonomy."

Pontes is ECB’s system for settling transactions in tokenized securities in central bank money Pontes is Latin for “bridges”, as in bridges between Target2 and blockchains (public or permissioned) Will be curious to see what chains they are using

“having a privacy-preserving and decentralized approach to verifying humanness is essential” - Gareth Davies, Chief Product Officer at Auth0 (Okta)

Explosive AI demand: AI token consumption is projected to increase 24x by 2030 driven by AI agents. Persistent supply bottlenecks: Demand can scale rapidly, while new supply capacity can take years to deliver because of grid and permitting constraints, data-center construction timelines, hardware shortages, and political opposition. Investment implication: We believe this supply-demand imbalance will favor owners of energized compute capacity.

Report from Grayscale Research on investing for the compute bottleneck ⬇️⬇️