For the first time, Google has measured how much energy AI really uses in production.

Spoiler: the gap vs. all previous estimates is huge... 🧵 Despite AI transforming healthcare, education, and research, we've been flying blind on its environmental footprint.

Every estimate was based on lab benchmarks, not real-world production systems serving billions of users.

Google decided to measure what actually happens.

Meta just won the world's biggest brain competition by building an AI that can READ YOUR MIND while you watch movies.

1st place out of 263 teams.

This is the most insane paper I've ever read: 🧵

(hint: mind reading is here) For context, the Algonauts competition challenged teams to build AI that predicts brain activity from videos.

263 teams competed.

Meta crushed it with the biggest 1st-2nd place gap ever.

Let me break down how:

China built a computer with 2 billion neurons mimicking a monkey's brain.

If Moore's Law is still valid, we will have human-level brain computers with 86 billion neurons by 2033.

We are closer to duplicating humans.

Thread China's progress is insane:

2020: Darwin Mouse (120 million neurons)
2025: Darwin Monkey (2 billion neurons)
2027: 4 billion neurons
2030: 16 billion neurons
2033: 86 billion neurons ← Human brain level

China went from mouse to monkey in 5 years.

NVIDIA just dropped paper exposing a $57 billion AI industry mistake.

While Big Tech keeps pushing expensive LLMs like ChatGPT & Claude...

Small language models handle 70% of AI agent work at 1/30th the cost.

Here's why this changes everything:

(hint: less is more) → The $57 billion mistake ↓

The AI industry invested massively in centralized LLM infrastructure in 2024.

But the actual market for LLM API services is only $5.6 billion.

That's a 10x gap between investment and revenue no one wants to admit.

BREAKING: Scientists just analyzed 740,000 hours of human speech across YouTube and podcasts.

Turns out, ChatGPT is rewiring how humans speak to each other.

Here's what they discovered:

(hint: the first AI to successfully colonize our brains) This shook me up first:

The changes showed up in SPONTANEOUS conversations, not scripts or prepared thoughts.

Random people chatting on podcasts started using ChatGPT's favorite words without realizing it.

The way scientists proved this was ingenious ↓

Years before ChatGPT existed, Sam Altman saw one YC startup that he believed would be bigger than all the others combined.

He put millions of his own money. Became chairman. Later took it public himself.

Today it's up 500% with ZERO revenue.

Here's the wild story of Oklo: Years ago, Sam realized there couldn't be abundant AI without abundant energy.

Now that ChatGPT exists and data centers are exploding from 5% to 12% of US power demand, tech giants will pay ANY price for clean energy.

Sam was right.

BREAKING: Stanford just surveyed 1,500 workers and AI experts about which jobs AI will actually replace and automate.

Turns out, we've been building AI for all the WRONG jobs.

Here's what they discovered:

(hint: the "AI takeover" is happening backwards) → Workers don't want full automation. They want partnership.

46.1% of tasks got positive automation ratings, but here's the kicker:

Workers prefer "H3 equal partnership" with AI over full replacement.

The world's leading AI research center completed the most comprehensive study ever on kids and AI.

They surveyed 1,800+ children, parents, and teachers in UK.

Here's what they found:

(spoiler: children are outsmarting adults on AI) The Alan Turing Institute surveyed 780 children aged 8-12 and 1,001 teachers across UK schools.

Plus, they ran workshops where kids directly tested generative AI tools like ChatGPT and DALL-E.

The results reveal how AI is already reshaping childhood:

BREAKING: Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all.

They just memorize patterns really well.

Here's what Apple discovered:

(hint: we're not as close to AGI as the hype suggests) Instead of using the same old math tests that AI companies love to brag about, Apple created fresh puzzle games.

They tested Claude Thinking, DeepSeek-R1, and o3-mini on problems these models had never seen before.

The result ↓

AI is killing entry-level jobs faster than LinkedIn can post them.

Anthropic's CEO predicts 50% of entry-level white-collar jobs will be gone in 5 years.

If you're under 30, here's what you should do: First, context:

• Big Tech hired 25% fewer new grads in 2024
• Entry-level tech ads down 37% year-over-year
• Legal review roles down 45%

The question is why it's getting so much worse? Let me explain ↓

Most ChatGPT answers are "yes-man."

After I began using the RPT prompt technique, ChatGPT cut its wrong answers by 40% and gave me much better results.

Here's what the RPT technique is and how to use it:

(my exact prompt + example) To prompt better, first understand why AI is so agreeable.

AI gets trained by human feedback (Reinforcement Learning from Human Feedback)

When we give thumbs up to answers that sound good, the AI learns to say what makes us happy.

It's pleasing us, not checking facts.

AI is eating up consulting.

I used 3 prompts on ChatGPT to mimic a $600/hour consultant, achieving in 4 hours what takes weeks for teams.

Here's how to make ChatGPT your pocket-sized McKinsey consultant:

(my exact prompt + examples) There are 3 main tasks that a consultant does:

1. Research
2. Making slide decks
3. Reading reports

I'll show you how to automate all 3 in a way that makes one person do the work of an entire team.

BREAKING: a new Chinese model is out.

And no. This is NOT DeepSeek.

Meet Qwen-2.5, from the giant Alibaba:

1. It can code, write text, search the web.
2. It can generate images, like Dall-E.
3. It can even generate videos.

Here's everything you need to know: 1. Omni-modal mastery:

☑Handles document parsing (tables, charts, handwriting)

☑ Object grounding (JSON coordinates)

☑Long video (hours-long footage with second-level event localization)

☑ Generates structured outputs for invoices, forms & spatial reasoning tasks

https://x.com/Alibaba_Qwen/status/1884263165984399486

BREAKING: DeepSeek released R1.

And it's already better than ChatGPT o1.

1. It's open-source.
2. API is 96.4% cheaper than chatgpt.
3. I run my tests below. A quick thread: test #1 → act as an indie hacker to promote my SaaS business.

DeepSeek is so fast. It's insane.

It gave me an entire strategy in 7 actionable steps. So I asked for more:

DeepSeek is shaking up the AI industry.

1. It's open-source.
2. It's multimodal (images, PDFs...).
3. API is 94.81% cheaper than chatgpt.

I run my own tests below:
#1 → write an SEO-optimized article #1. Search the web + write an SEO article

> DeepSeek provided 50 sources.
> chatgpt provided roughly 20 sources.

The article is even better than chatgpt.

DeepSeek won. Next test:

I manage my employee's Linkedin.

We went from 0 to 3,836,555 impressions in exactly 178 days of daily posting.

The trick is... I didn't write any posts.

I do this instead: Step 1: Pinterest

1. I go to Pinterest. I pick a viral quote.
2. Copy-paste it on ChatGPT.
3. Ask it to extract the quote.

I took over someone's Linkedin, and grew it to 6.3M+ views & 6,000+ followers.

AI did everything, from copies to videos.

Here's exactly how: Eitan branding is all about the humans behind AI, through interviews.

→ He shares only video clips.
→ He finds them on YouTube, X, or reddit.

Then he edits it with Opus Clip:

Google put together a prompt library.

I've tested all of them.

Here's my top 5 prompts you can try ↓

#1. Blog Post Creator You can write a blog post from a picture.

I uploaded a picture of AI tools & gemini generated an explanation of each tool.

It's not perfect but it's a good first draft.

Now, second prompt:

Anthropic just released new interactive prompt engineering courses.

9-course links & academic papers.

Here's the link + a summary of each:

#1 → basic prompt structure Anthropic shared a course on the basic structure of prompts used for AI models.

They explain the importance of the following parameters:
> model
> max_tokens
> system prompts

The system prompt is optional but a good way to provide context & instructions.

Prompt Chaining is the best way to prompt — according to academic papers.

But I want to run a test to be sure:
→ prompt chaining vs. stepwise prompt.

I made this quick benchmark below: First, what is prompt chaining?

Prompt chaining links multiple prompts together, using each response as input for the next, to create complex results.

It uses 3 separate prompts for drafting, critiquing & refining.

So step 1:

Yesterday, I ran some tests comparing gemini 1.5 pro exp vs. gpt-4o.

Google beat OpenAI, every-single-time.

But now, is gemini better than claude?

I run the same tests:
test #1 → write a viral twitter thread #1. Generate a Twitter thread

Left: gemini 1.5 pro
Right: claude 3.5 sonnet

I provided a tweet and asked for a thread.

→ gemini suggested a better 1st tweet.

It even gave me an explanation of choices based on my prompt.

gemini won. Next test: