@Jayyanginspires@Jayyanginspires thks for your post!
How to know when to stop?
Maybe until you are hit by reallity?
Is a portafolio the way to avoid collapse when you go all in with just one road?
Thks again
There's a shocking fact about AI that nobody tells you: You can catch up to the public AI research frontier in just 2 weeks. Yes, really.
I've built a $150M annual revenue startup over the last 8 years and If I were to start a company today, I’d drop everything and go all-in on AI.
But like many busy software builders, I felt lost—overwhelmed by the noisy, crowded and fast-moving modern AI landscape. And I wasn’t alone.
So I spent my entire holiday diving deep into AI research—reading 30+ papers, watching hours of lectures, analyzing trends, and catching up to the research frontier.
✨ Here’s what I learned:
- You don’t need months (or years) to catch up.
- You don’t need a PhD or decades of ML experience.
- You need fewer than 20 papers and 2 weeks to understand the major breakthroughs shaping AI today.
It's because the technology is extremely nascent and most techniques that came before are no longer relevant:
- ChatGPT is barely 2 years old and Transformers are only 7 years old.
- Most game-changing discoveries happened within the last 4 years, driven by a few breakthrough ideas, scaling laws, and efficient matrix multiplication.
The biggest secret?
Many groundbreaking AI papers with thousands of citations are surprisingly simple and applied, like adding "let's think step by step" to the prompt, or simply asking the LLM over and over again to improve its answer (Self-Refine).
I realized there are tons of founders and builders in the same boat—wanting to dive deeper into AI but unsure where to start.
I've created an essential AI Guide that helped me catch up, in just 2 weeks, to the frontier of public AI research to figure out where the next opportunities and gaps were:
- Curated list of only the most important papers
- Simple explanations of key concepts
- Clear pathway to understanding the frontier of modern AI
It’s perfect for:
- Founders expanding into AI
- Builders wanting to innovate at the frontier of AI
- Investors looking to separate the signal from the noise
👇 Want the full guide?
- Like and Share this post
- Comment "AI Guide"
- I'll send you the complete guide
(ps, I’m also teaming up with @VishalVasishth, co-founder of @obviousvc with @ev (focused on large-scale societal impact companies like Twitter, Medium, Beyond Meat), to host a small meetup to discuss what's working and needs to be solved in the AI stack in SF. Message me if you're interested)
Don't miss out on a chance to win the latest DJI Neo 2 Fly More Combo (Drone Only) 🎉
🏆 How to Enter:
1️⃣ Follow @DJIGlobal
2️⃣ Like and share this post 🔁
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#DJI #djineo2 #ASMR #Unboxing #Cameradrone #giveaway
In the last 5 months, I’ve scaled my Pinterest to $10K/month.
Now, I’ve cracked the most efficient workflow for automating complete Pinterest process.
Here’s my step-by-step system for compounding traffic and revenue: ↓
Most search models need the cloud.
II-Search-4B doesn’t.
4B model tuned for reasoning with search tools, built for local use.
Performance of models 10x its size.
Search that is small, smart, and open.
@OpenForest_@OpenForest_ It would be great if we could show which would be the steps to get to a fractional ownership by using OFP's tools. A simple step by step onboarding guide.
STAY STRONG!!!
Let me explain my real concern with how people use AI to write more online. It's more than em dashes, it's when their tone and voice starts disappearing
Lately, I see longer writing littered with negative-positive or rhetorical contrasting (eg "AI won’t replace humans. But it will replace the ones who refuse to adapt")
Intuitively, it makes sense. LLMs are trained heavily on Internet text that feels thought leadership-y (tweets, essays, blog posts). And since this style gets high engagement, it shows up more, and models seem to be replicating it more
While I am happy that more people are writing online (and creating) with AI, I think this hints at a dangerous behavior you can fall into
I use LLMs to refine my own thinking and explore my mind. When I want to write something, I start prompting to crystalize the intent of what I'm writing. I also ask LLMs for edits while preserving my tone. The more I write, the more I define what my tone is
I believe every great story, thought, product...has one clear message. It's your "why"
The one thing that the creator wants you to walk away with. Everything else is upside. But the intent to create starts with that goal. It's the truest motivation to persist through the pain of creation
At the beginning of the creative process, that intent is fuzzy. As you explore, you get your hands on that "why" and you mold it, shape it, feel it
By the end, it may look different. But going through that process is part of the journey. Struggling is a form of necessary suffering in acts of creation
When I see people using AI the wrong way...I realize they are sometimes outsourcing the task of finding your intention. This is the wrong kind of automation, it eliminates a necessary form of suffering.
Algorithmic feeds are slow to disincentivize this behavior. So creators will be rewarded for this automation in the early days. You're putting out more content, your content is written to engage, you get more engagement, rinse and repeat. Even more, you start training yourself to sound more like AI. The simulation picks up
But I believe eventually, the convergence point is choosing necessary suffering. It's the balance between knowing what to automate for leverage and what to struggle with. I believe you have to think deeply and wrestle with something to arrive at a good place.
You can use AI to get there faster, but you cannot use AI to bypass it altogether
Wanted to do a quick intro post.
(some context before I start tweeting more)
I’m Christian, co-founder and Chief Investment Officer at @regen_network
- been in crypto since 2015 (yes, sold BTC on eBay & traded in cafes)
- lived in a bamboo hut in Thailand (ran one of Asia’s best-known permaculture centers there)
- raised $12.5M as CEO during the last bull
- helped launch one of the first on-chain environmental asset protocols
- retired 1M+ ecocredits tied to real-world restoration
- not a dev, but now managing treasury + delta-neutral fund at Regen
- part-time investor, full-time father of 2
- fascinated by AI, Buddhist philosophy, and why meme coins still get funded
what i believe?
Most of Web3 is still noise.
But somewhere in the mess, there’s a path to real-world impact like what we’re doing at @regen_network.
If you're on that path too, say hi 👋