Evan Brooks

Exploring crypto trends, decoding tech shifts, and collecting stories from cities worldwide.
Music-driven mind • Tech-first lifestyle • Traveling for perspectiv

[LIFE AI @LifeNetwork_AI]

Access to AI is important.

Access to healthcare infrastructure is transformative.

When research, clinical development, and healthcare innovation become more connected, breakthroughs can move more efficiently from the lab to real-world impact.

The future of healthcare isn't built in isolation.

It's built together.

[Evan Brooks @BrooksEvan36]

@MahamangalT @grok this is so powerful, vibes are immaculate ��✨

[Evan Brooks @BrooksEvan36]

@eXe1lo Thats wild but honestly kinda impressive no cap

[LIFE AI @LifeNetwork_AI]

Read more from WHO:
https://t.co/Dpsnx0LEGK

[0xAnni @0x_Anni]

🚨Pixar spends four years and $20,000,000 to animate a chase like this.

this took one person, a prompt, and an afternoon.

no studio
no render farm
no crew
and clips like this print watch time, the only currency YouTube actually pays in.

the full build is in the article 👇

[Frezz @Frezzwnie]

A FOLDING DESK IN NAIROBI IS THE SUPPLY CHAIN BEHIND YOUR $200 AI SUBSCRIPTION. THE LAB IS JUST THE RESELLER

kelvin is 29, six used 3090s on an open frame, bought the lot off a closed mining telegram for $710 a card

a million tokens costs him about $0.04 of power.

he serves llama 70B and qwen on vast ai, openai bills the same compute at 10x and keeps the gap

$3,840 in. $290 out. nothing leaves the flat, no rate limits, no claude invoice

his girlfriend asks why the bedroom is always warm

pause at 0:09 — count the cards, there are six, you can only see three from the front, the back row is doing the real work

the moat was never the model.

it's that you didn't know the supplier fits on a desk

[LIFE AI @LifeNetwork_AI]

Cancer is one of the world's largest health challenges.
WHO estimates that global cancer cases could rise from 20.6 million in 2024 to nearly 35 million by 2050.
But the cancer story is also a story of prevention.
Up to 40% of cancers are linked to preventable risk factors. With earlier detection, better risk monitoring, stronger screening systems, and more equitable access to care, many outcomes can change.
The future of cancer care is not only about treating disease later.
It is about building systems that help identify risk earlier and guide people toward the right intervention sooner.

[Alibaba Cloud @alibaba_cloud]

Expanding AI infra for Japan's agentic AI future.

Alibaba Cloud has launched its 5th data center in Tokyo and brought Model Studio to Japan, enabling enterprises to build next-generation AI agents with the latest Qwen models.

Building the foundation for the agentic AI era.

[Outplay @OutplayHQ]

Turn more dials into conversations and more conversations into meetings with Outplay's AI-powered calling platform.

[Evan Brooks @BrooksEvan36]

@Bober_smart bro this scaling is insane, the views are actually viral on another level

[Evan Brooks @BrooksEvan36]

@uqTNb2qR3420616 Love this vibe home pub energy and that pizza sounds like a win

[LIFE AI @LifeNetwork_AI]

Chronic disease is one of the biggest pressures on healthcare systems.

In the U.S., 90% of the nation’s $5.3 trillion in annual healthcare expenditures are for people with chronic and mental health conditions.

But chronic disease is also one of healthcare’s biggest opportunities.

Many risks can be measured, monitored, and managed earlier: blood pressure, glucose, weight, physical activity, nutrition, sleep, adherence, and other long-term health signals.

With better preventive infrastructure, healthcare can move from reacting to disease toward helping people stay healthier for longer.

[Grimmer @0xGrimmer_]

A $4,699 BOX THAT FITS IN YOUR HAND KILLS AN $850 - A - MONTH CLOUD BILL - AND PAYS FOR ITSELF BEFORE THE YEAR IS OUT

00:02 no per-hour meter. no api tax on every test. no client data leaving the building.

nvidia's ceo held it up on stage: 1.2kg, the size of a sandwich. inside is a gb10 grace blackwell superchip, 128gb of unified memory, and up to 1 petaflop of ai.

that's enough to run inference on 200-billion-param models and fine-tune 70b ones, on your desk.

the math is the whole trick: a cloud gpu runs $3 to $4+ an hour. leave it on, test agents daily, and the bill goes from annoying to painful. the box is $4,699 once. at $500 a month saved it pays back in under a year. over five years it's under $1,000 a year.

and if you sell the work, one private ai project bills $3,000 to $10,000. one client covers the whole machine, then it's pure leverage: prototype without watching a meter spin.

the uncomfortable part isn't that the box is fast. it's that the cloud was never the default, it was a tax you agreed to. compute is moving from rented clusters back onto the desk.

save this and turn one recurring ai bill into owned hardware before renting starts to feel backwards.

[Comr. Pluto @plutozee3]

@LifeNetwork_AI Everyone deserves access 🦅

[Chris Riccio - LifeAI ☀️ supporter @CelinaRicc39259]

@LifeNetwork_AI This is the kind of access we actually need

[Insomnia @insomnia_vip]

A 28-YEAR-OLD CHINESE DEVELOPER FOUND A SMARTER WAY TO SECURE AI GENERATED CODE

His workflow combines Claude Code with Codex so every major code change is automatically reviewed by multiple AI agents that validate security findings cross check potential vulnerabilities and help resolve issues before deployment

As AI generates more production software the next competitive advantage won't come from writing code faster but from building systems where AI continuously audits and improves the work of other AI models

The future of software development is AI checking AI

[Evan Brooks @BrooksEvan36]

@LifeNetwork_AI This idea of accessible self-care tools connects beautifully with open-source software movements, where democratizing knowledge leads to collective empowerment in health too.

[MavexAI @0xMavex]

the girl dancing in the pink lace top clears $5,400 a month.

she was built inside one markdown file.

no cloud bills. no chasing every new model drop. one obsidian note, claude, and n8n - running local, compounding while everyone else burns cash on gpus.

here's the stack:

step 1 - karpathy's 1-file method.

one giant note. everything dumps at the top: ideas, datasets, training logs, prompt tests. old stuff sinks. every few days you reread and pull the survivors back up.

no folders. no tags. no plugins. the rereading IS the system.

step 2 - the flaw hits at 10,000 lines.

no human rereads that. claude does. point it at the vault and ask:

→ "what worked on my last fine-tune"
→ "find the 3 datasets i keep circling"
→ "which hyperparameters failed in february"

exact quotes from your own notes. 15 seconds.

step 3 - n8n removes you.

once a week it triggers claude: read the last 7 days, surface the 5 experiments worth pulling up, flag contradictions, queue the next training job.

the vault stays alive without you touching it.

the timeline:

week 1: feels like nothing. $0.
week 4: first "wait - i already solved this drift in january." hours saved.
month 3: you ship custom agents and fine-tunes faster than funded teams. package them, sell to clients and marketplaces. $5,400/mo with the vault as your unfair advantage.

the catch nobody posts: the vault doesn't sell anything. $5,400 comes from packaging and closing clients - the system just makes you faster than everyone pitching against you. and it only compounds if you actually dump daily. an empty vault automated by n8n is a very organized zero.

most builders lose their best ideas across 6 notebooks and 3 chats.

this one wins because dumping takes zero discipline - and claude does the remembering.

notion stores what you thought.
this thing ships models that dance and pay rent.

[ENG. Fadi -🇵🇸 @FadiQGaza]

No child deserves to suffer like this😭😭

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that
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DONATE FOR MY FAMILY
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I desperately need milk for my baby.🍼

https://t.co/jAxtrdgWIp

[Pak Views @Ij422]

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♥️ I LOVE ALLAH♥️