USA is not the only Christian country R€taπds. The picture I showed is of a Hungary, A Teensy Christian country which has produced more Noble Prizes, Olympics Gold Medalist than millions of Ponges spreading Cancer in Indian society.

Pathfinders Xclusive RoundTable | Beyond Flags | Details Coming soon! x.com/i/spaces/1OGwbnXkojvKB…

Meet Clover-35B-A3B-Preview 🍀 the first open-weight production diffusion language model (dLLM) with 35B total parameters capable of 680 tps on a single card at BF16. Clover exhibits strong performance against both dLLM and AR models and is available today at @huggingface @ModelScope2022 and at our website

Nonsense. Democrats pull this stunt each election. "I've always voted Republican but this year they've driven me away. I'm voting Democrat". 🤦😂

JUST IN: 🇨🇦🇮🇳 Air India officially launches nonstop flights between Toronto, Canada, and Mumbai, India.

🇺🇸 13 STATES. MILLIONS OF VOTERS. ELECTIONS THAT COULD COME DOWN TO A HANDFUL OF BALLOTS. If you live in Texas, Ohio, Michigan, Pennsylvania, Wisconsin, Arizona, Nevada, Georgia, North Carolina, Maine, Iowa, Kansas, or Alaska, please pay attention. These states are home to consequential U.S. Senate, gubernatorial, and congressional contests this November. American elections have been decided by razor thin margins. Sometimes thousands of votes. Sometimes hundreds. Occasionally, just a handful. Think about that. The difference between who represents you in Congress, who governs your state, and the policies that shape your future could come down to a few ballots. With Election Day just one week away, early voting deadlines are approaching rapidly. We’ve put together a battleground guide to help you prepare. Your vote is your voice. And in a close election, every single voice matters. 🇺🇸 November 3, 2026. Check your deadlines: Vote.gov - Indian American Advocacy Council (IAAC)

Someone predicted 150k layoffs earlier this year for $MSFT $AMZN $META $GOOGL to the tune of 160K to 200K. Wait. That was me. Precinct.

Big tech will layoff between 150K to 220K over the next 2 years. The AI boom across Big Tech is a capital allocation problem. The MAG7 — $MSFT $AMZN $META $GOOGLE $AAPL + $NVDA and $TSLA Microsoft, Amazon, Meta Platforms, Alphabet, Apple, plus NVIDIA and Tesla — have all converged on the same strategic reality: AI is now the core platform shift, and it demands an extraordinary amount of capital up front. Microsoft is now running at roughly $45–50 billion per year in capex Amazon is higher still, with $60–65 billion per year, Meta,is back up to $35–40 billion annually, Google sits in the $45–50 billion range. Apple is the outlier, closer to $10–15 billion, but that reflects a different strategy. Exclude NVIDIA, which sells the picks and shovels the MAG7 are collectively committing roughly $200–220 billion per year to AI-related capex. Over two years, that’s $400–440 billion. That’s the bill. The obvious question is: where does that money come from? There are only three sources: debt, organic free cash flow growth, and cost reduction. Everything else is storytelling. Let’s start with debt. These companies have pristine balance sheets, but they are not going to lever them recklessly in the middle of an arms race. Rating agencies, shareholders, and boards all impose soft limits. A reasonable assumption, and one that matches historical behavior; is that net incremental debt will not exceed roughly 50% of annual cash flow or revenue growth. In practice, that caps new debt funding across the MAG7 at about $120–150 billion over the next two years. That still leaves the majority of the AI bill unfunded. Next comes organic free cash flow growth. Assume reasonably healthy growth about 12–15% annually for most of the group, higher for Meta — and assume margins are held roughly flat. That’s not aggressive; if anything, it’s generous given that AI infrastructure is margin-dilutive in the short term. Under those assumptions, incremental free cash flow over the next two years looks roughly like this: Microsoft generates $35–40 billion. Amazon adds $30–35 billion. Meta, because of its advertising leverage and post-2022 cost reset, throws off $45–50 billion. Alphabet contributes $35–40 billion. Apple adds $25–30 billion. In aggregate, that’s about $170–195 billion of incremental free cash flow over two years. Now add it up. You’ve funded $120–150 billion via debt. You’ve funded $170–195 billion via growth. Best case, you’re at $345 billion. Worst case, closer to $290 billion. Against a $400–440 billion capex requirement, that leaves a gap of roughly $75–130 billion. This is the part that most commentary conveniently avoids. That gap has to be closed, and it can’t be closed by wishful thinking. Buybacks won’t be eliminated - they are too central to capital return narratives. Dividends won’t be cut. Pricing alone won’t do it. And AI itself does not generate enough near-term profit to fund its own infrastructure build-out. So the adjustment happens where it always does: operating expenses. And within opex, the largest and fastest-moving line item is headcount. Big Tech employees are expensive. Fully loaded cost, salary, equity, benefits, taxes, facilities: sits around $250,000 to $300,000 per employee per year. Eliminate a role and over a two-year horizon you save $500,000 to $600,000. Now the math becomes unavoidable. If you need to close a $75 billion gap, that’s roughly 150,000 jobs over two years. If the gap is $130 billion, it’s closer to 210,000–220,000 jobs. Spread across a combined workforce of roughly 1.9–2.0 million employees, that’s a 7–11% cumulative headcount reduction. Not in one dramatic announcement. Not evenly distributed. But continuously, quietly, and relentlessly. This is why the layoffs we’ve already seen feel “unsatisfying” to observers. They don’t look like a purge because they’re not. They’re structural reallocation. Headcount is being used as the shock absorber that allows AI capex to scale without collapsing margins. This also explains which teams get cut. Low-growth, low-margin, or weakly AI-adjacent businesses become funding sources. At Microsoft, that shows up in gaming and peripheral product orgs. At Amazon, it’s developer tooling and internal enablement layers where revenue attribution is indirect; SageMaker-adjacent roles rather than Bedrock or core infrastructure. At Meta, Reality Labs remains the most obvious long-dated option competing with near-term AI returns. This is not a judgment on whether those businesses are “bad.” It’s a recognition that in a constrained capital environment, optionality loses to immediacy. If a team does not directly grow AI revenue or directly reduce AI cost, it is, by definition, a place where capital can be reclaimed. The important point is that none of this requires inside information. It falls straight out of publicly available capex guidance, balance-sheet constraints, revenue growth assumptions, and basic unit economics. The AI arms race is real. The capex is real. The margin constraints are real. And once you accept those premises, the conclusion follows almost mechanically: headcount reduction is not a temporary correction, it is a financing mechanism. Over the next two years, the question isn’t whether further layoffs happen across the MAG7. The math says they must. The only real questions are pacing, distribution, and which teams become the next funding sources.