Oracle just told every AI company on earth the same thing. Your models are worthless. Not the technology, talent or the billions spent training them. But the data they were trained on. Larry Ellison, the man who built Oracle into the backbone of global enterprise just dropped a bombshell.... He said ChatGPT, Gemini, Grok, and Llama, all of them are training on the exact same data.​ The entire public internet, every Wikipedia page, Reddit thread and every news article. That means they're all converging essentially becoming the same product with different logos.​ Ellison's word for it is commodities. But here's where it gets dangerous. He says the real gold isn't public data, It's private data.​ The medical records in hospital systems, the financial data in bank vaults. The supply chain secrets of every Fortune 500 and guess where most of that data already lives. Not Google, Amazon or Microsoft but inside Oracle.​ Oracle databases hold most of the world's high value private enterprise data. So Oracle just launched something called AI Database 26ai.​ It lets the top AI models, ChatGPT, Gemini, Grok, Llama reason directly over a company's private data, without that data ever leaving the vault.​ They're using a technique called RAG, Retrieval Augmented Generation. The AI doesn't train on your data, it searches it in real time.​ Think about what that means. A bank could ask AI to analyze every loan it's ever made without exposing a single customer record. A hospital could have AI diagnose patients using its full medical history without violating HIPAA.​ A defense contractor could let AI reason across classified operations without data leaving a secure environment.​ Ellison is betting this is bigger than the training market. Bigger than the GPU boom. Bigger than the data center buildout.​ He called it the largest and fastest growing market in history.​ The numbers back the ambition. Oracle's remaining performance obligations just hit $523 billion. That's contracted revenue not yet delivered and $300 billion of it comes from OpenAI alone.​ Cloud revenue hit $8 billion in a single quarter, OCI grew 66 percent and GPU revenue surged 177 percent.​ But here's the part nobody's talking about. If private data becomes the real AI moat, then whoever controls the database controls the future of AI.​ And that's a level of power that should make everyone uncomfortable.show more

When you're in the hammer business, every problem looks like a nail.

😂😂😂😂😂

Bro wrote a whole geopolitical thriller just to describe Oracle inventing a new way to audit your enterprise licensing and charge you 400% more for database API calls

As I was saying: AI hardware is the endgame. AI software is worthless medium term. AIs can make AIs better. All they need is compute, aka AI hardware.

Larry plans on watching all of us.

Are there not HIPAA laws protecting our private data for medical records?

But this is the work around that

Counterintuitive follow-on: if private data is the moat, open-source models win. Why would any enterprise hand their crown jewels to OpenAI's cloud when they can run Llama locally? Ellison accidentally made the case for self-hosted AI.

You didn't touch on this though...

All this nonsense dribble and no mere mention of the superior model, Claude.

Claude is my favorite

@UneekSolutions Hardly

@_Investinq You clearly know nothing

If the government or affiliated labs integrate large datasets, they could reidentify you, surveil you, deny you travel, jobs, insurance... quite literally anything. AND they can legally do it without violating HIPAA bc they are only linking datasets. This is why you need to contact your representative immediately, I know it is a pain and not cool, but what's more uncouth is being controlled in every aspect of your life by the government just because you had a marker in your dna. Here's what needs to be changed: Ban genomic re-identification (stops name reconstruction via AI) Extend HIPAA to biological material itself (closes the de-identification loophole) Require consent for secondary usestops “you gave blood once, we own it forever” (Genetic FOIA transparency) Private right of action (this is essential, it gives ability to sue) Right now, none of these are guaranteed.

Models don’t train on the exact same data. There’s overlap, yes. But curation, filtering, synthetic data, reinforcement learning, and architecture still create meaningful performance gaps.

So they launched a RAG product Woah

RAG isn't new or unique to Oracle. It's been standard in enterprise AI for years and was popularized by Meta back in 2020. Every major cloud AWS, Azure, Google Cloud etc. supports secure, private RAG deployments. Hence, this is not some breakthrough architecture. Controlling a database doesn't automatically mean controlling AI. The modern AI stack is modular and multi cloud.

Seems more like an invasion of privacy being that Ai can go through all of that personal information. It’s like saying it’s ok to violate privacy as long as you do it in this do called vault. The information is still obtained by Ai and could potentially be re-coged for any particular reason

Misleading. If you have your data in Oracle databases in your own data center, Oracle does not have access to your data unless you allow it.

AI feeds on the open knowledge commons, monetizes it, and starves the ecosystem that built it. Each new model trains on the degraded remains — more confident, less grounded. The better it works, the faster it destroys the conditions for working well. It’s the business model.

EVERY database is going to be a vector database for RAG together with metadata. EVERY store of record SaaS vendor will need to vectorize their data. AI agents can’t rely on keyword search based API endpoints as that will become the weakest link. A good chunking strategy is different to every (sub)dataset. A one size fits all strategy doesn’t cut it. But Oracle does not have a unique moat here. It is their clients data and the concept of vector databases and RAG is not unique to Oracle.

verifiable private data 🦭

This sounds like a database company justifying why they matter more than the models. Fact is that Frontier AI models can already work with your data, securely, and at scale through a wide range of means, from any data platform. The best solutions today are the best models with access to your data in your environment.

Ellison is right about commoditization. Wrong about the moat. Private data isn’t the advantage. Most companies can’t even query their own databases without a consultant and a prayer. The real moat is knowing what questions to ask. Oracle sells the vault. Nobody’s selling the map.

AI is really just a process for organizing data What matters is the data And too many AI companies are willing to put bad data in On top of this, the real future of AI is niche focused AI which will require much higher quality and detailed data

Larry really just told the whole class their homework is great but their sources are trash. Spoken like a true database king.

ellison is right that private data is the real moat - which is exactly why it needs encryption by default. RAG without e2e encryption just means the AI company becomes the new gatekeeper.

Oh yeah, what could possibly go wrong?

oracle telling everyone data is the moat while sitting on the worlds largest enterprise database. convenient lol

He might want to look into Oracle's ruinous data center commitments if he actually believes this.

Not sure how this is news. Any company of any size is already leveraging some level of a secure on prem AI solution to tap into their proprietary data.

I don’t agree with this, I think intelligence can reach levels that we can not understand. We are in the singularity. All these boomers trying to guess don’t know what’s coming

These types of bulk searches on personal and private data by the government is exactly what Anthropic was concerned about. 🤔

This post was written with AI and so are most of the top few replies I've read so far.

Grok is training on synthetic data…

Ellison is essentially pitching the privatization of the "Logic Moat." The divide in 2026 is clear: Commodity AI is for broad tasks, but Private Data Assets are for enterprise survival. Training on proprietary customer personas creates a unique intelligence that generic LLMs can’t replicate. However, the "Oracle Trap" remains a massive Platform Risk. When your most sensitive data assets reside in a single vault, you’re trading sovereignty for convenience. The real question isn't whether Private AI is better—it is—but whether we can trust the "Vault Keeper" to remain a neutral auditor. Data centralization is the ultimate anti-pattern to true AI independence.

Access to the corporate private data remains the exclusive right of the data custodian or owner — not the database technology provider. The provider’s role is to deliver the interface, optimization, and security necessary for efficient data access. While Oracle is undoubtedly one of the leading database technology providers and plays a significant role in facilitating access to corporate private data, characterizing them as having full control over AI future would be an overstatement. The core service of interest to enterprises here is AI, which encompasses numerous components and sub-services. Oracle’s database infrastructure is one piece of that broader ecosystem — and should they fail to deliver their part effectively, they risk ceding market share to competitors.

Nah I don’t agree. Yes there might be overlap between the data of which these models are learning, but from a user point of view, each model interprets and represents it in a different way. What does that mean? It means all models are not the same and have a unique personality. Now let’s talk about the oracle product, everyone knows that oracle has always been a data company, and the fear is, that if all data becomes public (slowly), then that would be left for oracle to feed on. There second business of data centers too is at a massive risk because they have invested billions on these data centers and the speed at which Ai infrastructure is being upgraded, the need for such large data centers might not exist, or if it does exist, then that would contain a much different infrastructure that it does data because the storage capacity. Meaning - chipsets by nvidia can now hold 100x more data on 1 set alone! Therefore we do understand what oracle is trying to achieve here, but we do not agree

the model was always the commodity. the data was always the moat. took larry ellison saying it out loud for silicon valley to believe what database admins have known for 30 years