<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>fatso784</author><text>Looks a bit like snakeoil to me. A lot of companies now spinning up simple demos with opaque backends, making huge claims they’ve solved X hard problem for&amp;#x2F;with AI, then saying “trust us” and “join our waitlist” without hard details or facts to show for it. If you could detect hallucinations&amp;#x2F;biases etc that easily, don’t you think OpenAI would’ve worked on something like this?</text><parent_chain></parent_chain></comment><story><title>SafeGPT: New tool to detect LLMs&apos; hallucinations, biases and privacy issues</title><url>https://www.giskard.ai/safegpt</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>anonzzzies</author><text>How does this work? Does anyone know?&lt;p&gt;And for a large swats of things, how &lt;i&gt;can&lt;/i&gt; it possibly work? It’s not possible to say if or if not it is hallucinating code for almost all code and apis, for instance. And I see similar issues with many fields outside pure facts. With privacy issues as well.</text><parent_chain></parent_chain></comment><story><title>SafeGPT: New tool to detect LLMs&apos; hallucinations, biases and privacy issues</title><url>https://www.giskard.ai/safegpt</url></story>