Cisco beats on FY27 revenue and AI orders, but after-hours dips ~4% as stock trades at $118.8. If this pace sustains, AI demand could help earnings visibility next year. $CSCO

Thank life each morning upon waking,
we have another day to grind on X
Wishing everyone a new day filled with energy!!!

solana:2zMMhcVQEXDtdE6vsFS7S7D5oUodfJHE8vd1gnBouauv
Looking to bid a sweep and reclaim

bitcoin:native
Scalp

JUST IN: Trump says White House Press Secretary Karoline Leavitt will step down at month’s end to take a senior external advisor role. No direct crypto angle, but political staffing shifts can impact regulatory signaling and market sentiment. $BTC $ETH

The Delusional $bull
DducZJ295xLz1MtP3rahxosArfzUedrsV53KoXQNpump
#crypto #altcoins $sol

BlackRock just had the biggest month among onchain asset managers.
Three of the biggest 30-day flows on @RWA_xyz:
→ @BlackRock: +$302M
→ @circle: -$111M
→ @maplefinance: -$213M
At first glance, Circle and Maple look pretty bad here.
But their underlying products were still earning yield during the month.
Circle’s outflow came from USYC redemptions, while Maple’s came mostly from lenders withdrawing from syrupUSDC.
There’s no evidence of a maturity, exploit, or product failure behind either move. Investors simply reduced their positions or moved capital elsewhere.
Zoom out, and you'll see it's

ethereum:native
Distribution continues
Close below $1820 and $1600 comes quick

"This is the true form of the power of participation."
Thorium does not ask for permission. It builds.
Mine Thor. Rise with the power. 💪⛏️ #ToriumNetwork #TOR #Web3 #Mining

Robinhood Chain one month launch numbers are absolutely insane.
Wow.

SlowFish has been stagnant for so many days, and there’s finally some profit-taking. Those with weak conviction who mine, withdraw, and sell are redeeming early and dumping. I think this is a healthy pullback. Those continuing to stake their minted coins are still buying the dip. For anyone not yet in, this is definitely a good time to get in. #slowfish

Boat On The River
Take me back to my boat on the river
I need to go down, I need to come down
Take me back to my boat on the river
And I won't cry out any more
Time stands still as I gaze In her waters
She eases me down, touching me gently
With the waters that flow past my boat on the river
So I don't cry out anymore
Oh the river is wide
The river it touches my life like the waves on the sand
And all roads lead to Tranquillity Base
Where the frown on my face disappears
Take me down to my boat on the river
And I won't cry out anymore
Oh the river is deep
The river it touches my life like the wa

JUST IN: White House hints expanded AI regulation to cover open-source models as testing framework eyes broader oversight.
Implication: potential policy-driven risk and funding shifts for AI developers; watch for crypto relevance if regulators reference AI-enabled tech.

Nebius jumps 34% after Q2 results showing revenue $582.3M and adjusted EBITDA $236.2M, signaling a swing toward profitability despite ongoing net losses. $NBIS

👀👀 they know $Woof.

$TOAD has bottomed
Higher 🐸

$67 is getting interesting. 🧐
I took a closer look at @sixsevenapp and the current numbers caught my attention.
Here’s what the chart is showing:
• ~$29.1M market cap
• ~$349K liquidity
• ~$284K 24H volume
• 6,211 transactions
• 3,764 buys vs 2,447 sells
• 2,652 buyers vs 1,511 sellers
• $142K buy volume vs $141K sell volume
• +1.53% over 24H
The interesting part?
There are significantly more buyers than sellers, but the actual buy/sell volume is almost perfectly balanced.
That tells me there is strong participation around $67, but sellers are still absorbing a lot of the buying pressure.
An

🔥Hundreds of Thousands of GPUs Sitting Idle at Once! xAI Exposes the AI Industry’s Computing Bottleneck
According to an internal memo leaked to overseas media, xAI has approximately 500,000 NVIDIA GPUs, making it one of the world’s largest privately operated computing clusters. However, its model FLOPs utilization (MFU) is only 11%, which has been described internally as “absurdly low.”
For comparison, mature tech giants generally achieve training MFU rates above 40%, while Meta and Google can reach 43–46%. An 11% MFU means that most of these expensive GPUs spend significant amounts of time s