Extremely curious that PaLM-E, PaLI, and GPT-4 were trained to be multimodal (accept non-text inputs, such as images) but the released API's are text-only. In GCP's case, here, they've released PaLM-2 which is not multimodal like PaLM-E and PaLI. This prevents using it for visual reasoning[0].<p>I'm just wondering why multiple parties seem reluctant to allow the public to use this.<p>0: <a href="https://visualqa.org" rel="nofollow">https://visualqa.org</a>
We are waiting to launch a new iOS app that has text generation using vertex AI for GA. So we will go live next live.<p>We started with GPT API but switched to Vertex AI due to speed. We will still use GPT API as backup still though.
I've been demoing it and have found it struggles to reliably output structured JSON at the moment. I'm curious if folks have had different experiences and if so what their prompts were.
Interesting statement and would be keen to see if businesses would trust Google to try out these capabilities, or other smaller recent services as the preferred choice given their flexibility of integration with existing cloud choices.<p>It seems we may find companies on all major cloud providers in the near future to guarantee access to unique proprietary services that cloud providers are starting to differentiate themselves with from their competitors
I really really wonder how the price of vertex.so compares - in practice - to the openai api for use by a startup with unpredictable and non-sustained usage??? The multitenancy assumptions that are part of the openai api cost structure might make it much cheaper. Has anybody modeled this? I realize the LLM’s aren’t equivalent today, but longterm they could be.
i didn't try it as this requires you to give payment information for a free trial and i got sidetracked<p>what i did learn, is that somehow, google has all of my credit cards despite me never sharing it on the account i was using.