This is probably the first time we got such clear verification about whether major companies are way more advanced with their internal AI systems compared to what they release publicly. I’ve been wondering about this for months now. Do you think this means the gap between what these big tech companies have internally versus what we can actually use is smaller than most people assume? It seems like there’s always been speculation that organizations like OpenAI, Google, and others keep their best models locked away for internal use only. But if an actual employee is saying the public versions are close to their latest work, that changes everything. What are your thoughts on this? Does this make you more confident about the current state of publicly available AI tools, or do you think there might still be some significant differences we don’t know about?
This revelation actually makes perfect sense when you consider the training costs and infrastructure required for these models. Companies invest billions in developing AI systems, and the only way to recoup those investments is through widespread adoption and usage. Keeping superior models locked away would essentially mean burning money without generating returns. The verification also explains why we’ve seen such rapid improvements in publicly available tools over the past year. If there were truly massive gaps between internal and public versions, we wouldn’t expect to see the consistent performance increases that have been delivered to users. What’s probably happening is that any internal advantages are measured in weeks or months rather than years, reflecting the time needed for safety testing and deployment preparation rather than intentional withholding of capabilities.
tbh, i kinda get what ur saying. it’s risky to keep top models internal when they can profit off public ones. but still, i wonder if we’ll ever really kno how much more advanced the internals r.
Having worked in tech for several years, I think the verification actually aligns with what we should expect from a business perspective. Companies like OpenAI are essentially research organizations that need to demonstrate their capabilities to attract funding and partnerships. Keeping their most advanced models completely internal would contradict their core revenue strategy. The gap people imagine probably stems from misconceptions about how AI development actually works. Most improvements come from incremental advances rather than revolutionary breakthroughs that would justify withholding entire model generations. What likely differs between internal and public versions are operational aspects like computational efficiency, specific safety implementations, or access to proprietary datasets rather than fundamental capability differences. The employee confirmation suggests these companies are more transparent about their technological state than the conspiracy theories would have us believe.
honestly this kinda blows my mind if true. always thought they were holding back the good stuff but maybe we’re closer to the cutting edge than expected. still feels weird tho - why would they give us nearly their best work?
From what I understand about how these companies operate, it makes sense that public releases would be close to their internal capabilities. The business model essentially relies on monetizing their best technology rather than hoarding it. However, I suspect there might still be subtle differences in implementation details, safety guardrails, or specialized fine-tuning that we don’t see in consumer versions. The real advantage for these companies probably isn’t keeping superior models hidden, but rather their infrastructure, data pipelines, and ability to iterate quickly. When you consider the competitive landscape, releasing subpar versions while competitors advance would be commercial suicide. That said, verification from an actual employee does provide more credibility than the usual speculation we see online.