Any enterprise that will not be building and compounding its own specialized AI as it operates itself, it will get commoditized, out-innovated by its competitors or disrupted by the likes of Harvey/Anthropic that will learn the intelligence powering their business better than them.
Specialized intelligence is the only robust moat is the AI new era. It is existential, not optional.
Enterprises using Opus 4.8 to do classification, entity extraction, document analysis or pretty much 90% of their AI use cases....
Wildly wasteful at enterprise scale.
Η startup του @Koukoumidis βοήθησε τους New York Times να εντοπίσουν τα τυφλά σημεία των AI Overviews της Google. Ήταν πολλά περισσότερα απ’ότι φανταζόμαστε.
Όμως το μεγαλύτερο στοίχημα της Oumi βρίσκεται αλλού: στην αυτοματοποίηση της ίδιας της μηχανικής της τεχνητής νοημοσύνης με στόχο πιο ακριβή, πιο οικονομικά και πιο προσαρμοσμένα μοντέλα για κάθε οργανισμό.
Legendary stuff από έν��ν από τους κορυφαίους έλληνες στο ΑΙ σήμερα.
https://t.co/EEWAJz555T
Prompts for a generic model that everyone shares are not a moat.
The moat is specialized intelligence:
- trained on your workflows
- adapted to your edge cases
- continuously improving from production usage
- fully owned and controlled by you
OpenAI announced that it is deprecating fine-tuning, taking away the only true way their customers had to build their moat. Take your data and bring it to Oumi. In just hours you can build, evaluate and deploy your specialized model.
The future enterprise AI stack is:
your business → your intelligence → your competitive advantage
This is why we built Oumi to make enterprise-owned intelligence operational in hours instead of months.
I just met @AndrewYNg at AI Dev—and something about the interaction stuck with me.
Despite everything he’s achieved, he was humble and helpful connecting me with his team in the same pleasant, calm, and soothing voice he is also known for.
Being here at AI Dev, you can feel that shift. The conversations aren’t just hype—they’re getting more practical, more grounded.
If you’re around, come by booth #511—we’ve been demoing Oumi’s VibeML and the response has been great.
Also, tomorrow at 5pm, Stefan and I are presenting:
“VibeML: Build your specialized AI model from a prompt – in hours, not months”
If every commuter drove a semi-truck instead of a sedan, we’d trigger a fuel crisis almost overnight. 🤯
And each commuter would be burning far more money than necessary just to get to work. 💸
That’s exactly what’s happening with compute and LLMs.
Enterprises are defaulting to large, general-purpose models for tasks that could be handled by smaller, specialized ones a fraction of the size. The result? An artificial GPU shortage, and a hidden tax on every company just trying to get work done.
Off-the-shelf frontier models can be 10-100x less efficient than a purpose-built, open source model for a specific task. So while it feels like the compute capacity issue, it’s more likely driven by how enterprises are choosing to use AI.
The fix isn’t just more GPUs, better prompt engineering, or even another data center (hopefully). It’s smaller, specialized models, built for what you’re actually doing. Until recently, that was easier said than done because custom model building meant extensive ML engineering effort and experience.
That’s why at Oumi, we pioneered VibeML - the agentic building (evaluation, data synthesis, fine-tuning) of specialized LLMs from just a prompt. It is now 100x faster and easier for enterprises to build their own custom AI; models they fully own, tuned to their exact use case, with better quality and lower cost than any off-the-shelf alternative.
The solution to the compute shortage isn’t more compute, more data centers, better infrastructure. It’s creating smaller, sustainable models. 🥬🌎
@dylfreed@emollick +1 to what @dylanFreedan said.
Manos and @stefan_webb from @Oumi_PBC here that did the analysis with Dylan and the rest of the NYT team.
Here to help if there are any questions.
Hot take: AI engineers have been some of the least AI-augmented people in tech, but this is about to change forever.
We gave superpowers to:
• Developers (Cursor)
• SRE
• Marketing
• HR
…and many more
But building custom AI models?
Still slow. Still painful. Still “expert-only.”
That makes no sense.
So we built Oumi -- the “Cursor for AI development” 🚀
Launched last Tuesday.
One week later:
• Users already shipping real use cases
• 1st place out of 60 startups at Seattle Startup Pitch 🏆 (perfect 10/10)
The shift is coming fast.
AI won’t just automate everything else.
It will automate AI development itself.
If you’re at HumanX, come say hi 👋 booth #513
🚨 The era of general-purpose AI is over.
Today we're launching Oumi. 🚀
The platform that lets any team build custom AI models — in hours, not months.
Just describe what you need. Oumi builds it. #VibeML
Higher quality. Lower cost. Fully yours.