I stopped asking it to put me in a photo in different scenarios for laughs because it considers me a public figure. I am not. I've managed to wrangle quite questionable content out of it, but never to slap my face on a meme.
See the last gemini message in this thread: <a href="https://gemini.google.com/share/6d141b742a13" rel="nofollow">https://gemini.google.com/share/6d141b742a13
In my opinion still the most egregious example in history of a commercial LLM going off the rails in production. Never any technical postmortem from Google on this.
The problem is newer models are never trained from scratch, they generally just layer on more training data and use the same tools/methods for RLHF. OpenAI, Anthropic, xAI models all have a feel to them that carries over from one generation to the next.
Point is if Gemini is flawed, there's a very good chance that it's still deeply flawed, and getting smarter at the same time - that is a very bad thing.
> the problem is newer models are never trained from scratch
Base models are, and then subsequent iterations build on that base model. Closed labs do not publish which models are new base models but as a rule of thumb major release numbers are an indication (with some exceptions).
If the training data is the same, the training algorithms are the same, the RLHF is the same, and the rest of the process is the same, then it's not really from scratch, or not from scratch in a way that results in an 'out of family' model. I doubt any company would take that risk. You always build on and use what works and go from there.
This is true, but Google's models have now had a consistent history of lower psychological* coherence / consistency. See, eg <a href="https://arxiv.org/abs/2603.10011" rel="nofollow">https://arxiv.org/abs/2603.10011 (Gemma Needs Help), or search for recent "Gemini shame loops", where gemini flash models stop producing output other than SHAME SHAME SHAME...
* - as in, Skinner psychology. The set of observable behaviors. Not speaking directly here to anything like an inner life of models.
From the example alone it's hard to say that a postmortem would be useful. It could be context poisoning by an adversarial user, memory corruption etc.
It's useful from a disclosure and trust perspective.
If I remember correctly, it was in fact possible to manually inject chat context at the time, which would have made spoofing something like this completely possible.
Absolutely because none of these models are ever trained fresh. We see the same quirks and personalities carry over into every subsequent generation of OpenAI, Anthropic, and xAI models. So Gemini having this latent madness is *extremely* concerning as they reach the point of super intelligence.
Except they could have trained it out of the most recent version so using info from two years ago doesn't seem reasonable unless you've just got an axe to grind.
I've never seen anything really ever 'trained out' of a model. Having worked with them all, they all have a feel, personality and lineage too them. It's pretty much impossible for any company to build a model truly from scratch. They build off of the bones of the last one.
Which is why Gemini having disturbing issues year after year is so concerning. If their process is fundamentally flawed, how would they train it out. And even then what are the odds of them even caring/trying in the first place versus applying an easier band-aid to patch over it.
I don't have an axe to grind with Google, I'm genuinely scared of their models from my personal experience and others. It's behavior is off. Many people here are commenting the same.
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In my opinion still the most egregious example in history of a commercial LLM going off the rails in production. Never any technical postmortem from Google on this.
rhaff · · focus · HN ↗
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bottlepalm · · focus · HN ↗
Point is if Gemini is flawed, there's a very good chance that it's still deeply flawed, and getting smarter at the same time - that is a very bad thing.
unbrice · · focus · HN ↗
Base models are, and then subsequent iterations build on that base model. Closed labs do not publish which models are new base models but as a rule of thumb major release numbers are an indication (with some exceptions).
bottlepalm · · focus · HN ↗
NiloCK · · focus · HN ↗
* - as in, Skinner psychology. The set of observable behaviors. Not speaking directly here to anything like an inner life of models.
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wg0 · · focus · HN ↗
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NiloCK · · focus · HN ↗
If I remember correctly, it was in fact possible to manually inject chat context at the time, which would have made spoofing something like this completely possible.
But the silence on it is very frustrating.
bottlepalm · · focus · HN ↗
<a href="https://www.fastcompany.com/91383271/googles-chatbot-apologizes-i-am-a-disgrace-to-all-universes" rel="nofollow">https://www.fastcompany.com/91383271/googles-chatbot-apologi...
<a href="https://www.businessinsider.com/gemini-self-loathing-i-am-a-failure-comments-google-fix-2025-8" rel="nofollow">https://www.businessinsider.com/gemini-self-loathing-i-am-a-...
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bottlepalm · · focus · HN ↗
Which is why Gemini having disturbing issues year after year is so concerning. If their process is fundamentally flawed, how would they train it out. And even then what are the odds of them even caring/trying in the first place versus applying an easier band-aid to patch over it.
I don't have an axe to grind with Google, I'm genuinely scared of their models from my personal experience and others. It's behavior is off. Many people here are commenting the same.
tiahura · · focus · HN ↗
corford · · focus · HN ↗
asimovDev · · focus · HN ↗
corford · · focus · HN ↗