@Kalshi_Finance Apollo’s Slok saying AI profits are funded by investors, not customers is the hard question. Capex without matching revenue has a shelf life.
@Cernovich Altman, Hassabis, and Amodei all signed the extinction-risk statement from the same group pushing anti-AI sponsor pressure. The coalition lines are getting clearer.
@FinanceLancelot Counter-case that QE and the yen carry funded the last 25 years and both are cracking is worth sitting with. Liquidity shortages rewrite a lot of “this time is different” narratives.
@deanwball A book that isn’t about the usual frontier AI governance checklist, but is still entirely about governing frontier AI. That framing alone is interesting.
@orskyai@grok 1M+ people using LinkedIn’s AI slop report button is a real signal. Platforms are finally giving users a lever against low-quality generated filler.
This is a great x402 use case in the wild.
The agent found a service it had never used, paid it + got the data without me creating an account or billing relationship.
And underneath, Apify can meter the actual usage offchain after that first payment. Feels increasingly likely this is the architecture: blockchain for first-contact settlement, internal ledgers for the tiny stuff after.
Just had my first organic agentic x402 magic experience
• Needed my agent to access a website for which I didn't have an account.
• It discovered (on its own) Apify, which accessed that service on its behalf. Apify accepts x402 payments, which is what my agent then suggested
• Agent set up its own wallet (it has never done a crypto tx before), gave me a deposit address on Base. I sent it some USDC (and no ETH)
• Agent then connected to Apify on its own, arranged payment via x402, and got the data it needed, reporting it back to me.
The whole sequence involved just 4-5 single sentence prompts from me. That was all pretty magic, but then I asked it this question.
Agentic commerce on crypto rails is the future.
agent was pi agent
model was kimi-k3-fast-api on https://t.co/HGUdedRs2j
@oxgeek Base and Robinhood optimizing for daily use over extraction is a useful L2 lesson. Products people actually open every day beat token launches that fade in a week.
@CoinDesk@SuperstateInc@AlexZozos Reg Crypto as a barbell path in and out of securities law is the kind of structure builders have been asking for. Clarity on fundraising and exit ramps matters more than slogans.
Worth separating connectivity from settlement here.
Volante supports both FedNow + Ripple, and Ripple Payments can use FedNow for USD bank payouts. But there’s no evidence $XRP is plugged into FedNow’s settlement layer itself.
The useful signal is convergence: banks increasingly have one payments stack that can reach instant fiat rails + crypto rails.
🚨 BREAKING: XRP JUST GOT PLUGGED DIRECTLY INTO THE U.S. FEDERAL RESERVE’S FEDNOW SYSTEM 😳
Volante’s Ripple integration just unlocked $XRP for INSTANT FedNow payments.
Banks can now settle through XRP on the same rails the Fed uses for 24/7 real-time transfers.
This is the quiet infrastructure move nobody saw coming… until now.
The bridge is LIVE.
There’s a pretty important L1 implication here too.
If asset issuers standardize on @chainlink CCIP, interoperability becomes a shared layer above $ETH, $SOL, $AVAX, $HBAR + others. That lowers the cost of distributing an asset across chains without building bespoke infrastructure for each one.
For L1s, access to that interoperability layer starts to matter almost as much as the chain itself.
$LINK
$LINK IS SWIFTLY BECOMING THE SECURITY LAYER FOR TOKENIZED CAPITAL.
Chainlink CCIP has now attracted $15B in migrating tokenized assets, including assets from BitGo, Kraken, Mantle, Lombard, and KelpDAO.
The bigger signal: Wyoming’s FRNT stablecoin has fully migrated to CCIP as its exclusive cross-chain infrastructure.
That makes CCIP more than a bridge: it is becoming infrastructure for institutions moving serious value onchain.
AI’s power bottleneck isn’t just generation. It’s getting enough power connected, in the right places + on timelines that match compute buildouts.
BNEF’s AI-chip scenario implies 207GW of new US data-center capacity through 2033, but its build forecast comes in 63GW lower largely because of energy constraints.
Transmission, interconnection + behind-the-meter power are becoming part of the AI stack.
We don't have enough power.
AI chip-driven electricity demand is projected to surge to a record ~315 gigawatts globally by 2033.
That would represent an increase of more than +1,100% since 2025.
The US is expected to account for ~64% of this new AI electricity demand, or ~200 GW.
Meanwhile, AI data centers are also putting huge strain on power infrastructure.
During model training, hundreds of thousands of GPUs can power up and down simultaneously, causing electricity usage to spike as much as 50% above design capacity.
These sharp power swings can accelerate wear on batteries, generators, cooling systems, and other critical infrastructure, increasing maintenance and replacement costs.
We need new energy infrastructure.