text (1527): Cambridge professor on stage:
If you think spraying chemicals to dim the sun is playing God the only alternative is to cull the human population back to 1 billion. Anyone volunteer?
Dead silence.
Then he laughs: Didnt think so. Get over it we now have a permanent duty to manage the planet.
This is NOT a conspiracy clip from 2015.
This is 2025. This is the director of Cambridges Centre for Climate Repair.
And the UK just created a secretive DARPA-style agency called ARIA 800 million of taxpayer money, zero FOIA, zero accountability that is RIGHT NOW funding real-world experiments to spray particles into the stratosphere to block the sun.
Harvards SCoPEx got shut down after global backlash.
So Bill Gates & friends simply moved it to Britain.
Over 160,000 British citizens forced their government to respond to a petition demanding ALL geoengineering be banned.
Governments official reply: We have no plans to deploy.
Translation: ARIA is doing it anyway, behind closed doors.
Meanwhile in America, venture-backed startups are already releasing sulfur dioxide into the atmosphere and selling cooling credits like crypto.
They are literally dimming the sun that grows your food, gives you vitamin D, and keeps Earth alive without asking a single person on the planet for permission.
Watch the full 7:47 expos unedited quotes, funding docs, government statements
One question for you right now:
Do you consent to billionaires and unelected bureaucrats permanently controlling how much sunlight reaches Earth?
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text quote (1317):πΊπΈ GATES' NUCLEAR REACTOR JUST CLEARED THE BIGGEST HURDLE - AND IT'S NOT LIKE ANYTHING YOU'VE SEEN
TerraPower's Natrium reactor in Wyoming just became the first advanced commercial nuclear plant to pass the NRC's full environmental review.
Bill Gates is actually building the future.
This isn't your grandfather's nuclear plant.
The 345 MWe sodium-cooled fast reactor comes with a molten salt energy storage system that turns the entire facility into a grid-scale battery.
Base load? 345 megawatts, rock steady.
Peak demand: Ramps to 500 megawatts in minutes.
No other advanced reactor design can do this.
The implications are massive. Renewables are intermittent. Batteries are expensive and limited.
This thing stores heat, delivers constant power, and surge-scales when the grid needs it most - exactly what's required to actually replace fossil fuels.
Construction on non-nuclear components started in June. Final safety review drops by year-end.
If approved, this becomes America's first utility-scale advanced nuclear plant, replacing retiring coal capacity in the region.
Nuclear energy spent decades stalled by regulation and public fear. Gates put his money where the physics is - and it's moving.
The grid needed this 20 years ago. Better late than extinct.
Source: Interesting Engineering
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text quote (2008):My brain broke when I read this paper.
A tiny 7 Million parameter model just beat DeepSeek-R1, Gemini 2.5 pro, and o3-mini at reasoning on both ARG-AGI 1 and ARC-AGI 2.
It's called Tiny Recursive Model (TRM) from Samsung.
How can a model 10,000x smaller be smarter?
Here's how it works:
1. Draft an Initial Answer: Unlike an LLM that writes word-by-word, TRM first generates a quick, complete "draft" of the solution. Think of this as its first rough guess.
2. Create a "Scratchpad": It then creates a separate space for its internal thoughts, a latent reasoning "scratchpad." This is where the real magic happens.
3. Intensely Self-Critique: The model enters an intense inner loop. It compares its draft answer to the original problem and refines its reasoning on the scratchpad over and over (6 times in a row), asking itself, "Does my logic hold up? Where are the errors?"
4. Revise the Answer: After this focused "thinking," it uses the improved logic from its scratchpad to create a brand new, much better draft of the final answer.
5. Repeat until Confident: The entire process, draft, think, revise, is repeated up to 16 times. Each cycle pushes the model closer to a correct, logically sound solution.
Why this matters:
Business Leaders: This is what algorithmic advantage looks like. While competitors are paying massive inference costs for brute-force scale, a smarter, more efficient model can deliver superior performance for a tiny fraction of the cost.
Researchers: This is a major validation for neuro-symbolic ideas. The model's ability to recursively "think" before "acting" demonstrates that architecture, not just scale, can be a primary driver of reasoning ability.
Practitioners: SOTA reasoning is no longer gated behind billion-dollar GPU clusters. This paper provides a highly efficient, parameter-light blueprint for building specialized reasoners that can run anywhere.
This isn't just scaling down; it's a completely different, more deliberate way of solving problems.
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