"Run hard when it gets hard to run. Everything starts with discipline. Practice until you can’t get it wrong - not just until you get it right. If you don’t respect it enough to do it right-when it’s the right way to do it, how can you be trusted in a game?" - Nick Saban

Very good from Konstantin Kisin.

ZEGRAS IS A VIDEO GAME PLAYER

GTOWN Fr. (M) #24 Patrick Crogan: 1. ELITE 2. FREAK ATHLETE w/ VISION 3. FUTURE ALL-AMERICAN 4. ALL OF THE ABOVE

Joey Porter Jr. dropped out of the First Round. That's when his father stepped in.

🔥 Teamsters President Sean O'Brien & Theo Von Roast the Democratic Party "I'll be honest with you, I'm a Democrat but they have f*cked us over for the last 40 years...Since I've been in office 2.5 years, we've given the Democratic machine $15.7 million. We've given Republicans

Netflix is not ready for the primetime!!! #netflix #TysonVsJake #TysonPaul #TysonvsPaul

Congratulations to Tiger and Rory they have brought the LIV golf experience indoors#tgl

Any time you watch a clip of Johnny Carson, you realize what a steaming pile of trash Jimmy Kimmel and late-night “comedy” have become.

And that is why they have massive robot manufacturing facilities. The leadership does not care about their workers.

Electric and Energy is our generation space race Will the US Fall Behind China in AI Without Boosting Energy Production? Will the US Fall Behind China in AI Without Boosting Energy Production? Yes, if the US doesn't significantly ramp up energy production—particularly reliable

baseload sources like nuclear, natural gas, or renewables with storage—it risks ceding ground to China in the AI race by 2030. AI's voracious energy appetite (data centers could devour 8-15% of US electricity by 2030, per IEA estimates) is a choke point:

: The US grid is already strained, with permitting delays and NIMBYism slowing new capacity. China, meanwhile, is bulldozing ahead with state-orchestrated buildouts, leveraging coal, hydro, and nuclear to power its AI ambitions.

This isn't just about raw power—it's about who can scale hyperscale data centers fastest, fueling the compute edge in models like those from Baidu or Alibaba vs. OpenAI/xAI.

The gap? US energy growth is projected at ~1-2% annually without policy shifts (EIA 2025 outlook), while China's hits 4-6% (IEA). For AI specifically, Goldman Sachs warns that US bottlenecks could delay $1T+ in data center investments,

handing China a 20-30% lead in effective compute capacity by decade's end. But it's not inevitable: Targeted reforms (e.g., faster nuclear approvals via the ADVANCE Act) could close it. Let's break it down.

Key Energy-AI Dynamics: US vs. ChinaAI training/inference scales linearly with power—e.g., a single frontier model like GPT-5 might need 100-500 MW dedicated clusters. Without surplus energy, US firms face blackouts, offshoring, or throttling (as seen in Virginia's 2025 grid aler

US Vulnerabilities: Gridlock (pun intended)—the average new power plant takes 5-7 years for approval vs. China's 2-3. 2025 saw hyperscalers like Microsoft lobbying for nuclear restarts, but without DOE fast-tracks, AI growth caps at 20-30% YoY (vs. potential 50%).

China's Momentum: Beijing's "Eastern Data, Western Compute" initiative funnels cheap western hydro/coal to coastal AI hubs. By 2027, China could host 40% of global data center capacity (up from 20%), per Synergy Research—enough to train models 2-3x faster than US equivalents.

Today the country is closer to India in 1947 not for religious reasons but for political reason. It is like the east coast and west coast are like East and West Pakistan