11–20 of 512 posts
Gemini in search is answering so many of my search questions wrong. If I ask natural language yes/no questions, Gemini sometimes tells me outright lies with confidence. It also presents information as authoritative - locations, science facts, corporate ownership, geography - even when it's pure hallucination. Right at the top of Google search. edit: I can't find the most obnoxious offending queries, but here was one…
Gemini in search is answering so many of my search questions wrong. If I ask natural language yes/no questions, Gemini sometimes tells me outright lies with confidence. It also presents information as authoritative - locations, science facts, corporate ownership, geography - even when it's pure hallucination. Right at the top of Google search. edit: I can't find the most obnoxious offending queries, but here was one…
I also miss that it’s not yet really as context aware as ChatGPTo4. Even just asking a follow-up question, confuses Gemini 1.5.
Hope Gemini 2.0 will improve that!
Beats Gemini 1.5 Pro at all but two of the listed benchmarks. Google DeepMind is starting to get their bearings in the LLM era. These are the minds behind AlphaGo/Zero/Fold. They control their own hardware destiny with TPUs. Bullish.
Beats Gemini 1.5 Pro at all but two of the listed benchmarks. Google DeepMind is starting to get their bearings in the LLM era. These are the minds behind AlphaGo/Zero/Fold. They control their own hardware destiny with TPUs. Bullish.
However their on device TPUs lag behind the competition and Google still seem to struggle to move significant parts of Gemini to run on device as a result.
Of course, Gemini is provided as a subscription service as well so perhaps they’re not incentivized to move things locally.
I am curious if they’ll introduce something like Apple’s private cloud compute.
But, once they do get moving in the right direction the can achieve things that smaller companies can't. Google has an insane amount of talent in this space, and seems to be getting the right results from that now.
Remains to be seen how well they will be able to productize and market, but hard to deny that their LLM models aren't really, really good though.
Most of these things seem to just be a system prompt and a tool that get invoked as part of a pipeline. They’re hardly “agents”.
They’re modules.
The Gemini 2 models support native audio and image generation but the latter won't be generally available till January. Really excited for that as well as 4o's image generation (whenever that comes out). Steerability has lagged behind aesthetics in image generation for a while now and it's be great to see a big advance in that. Also a whole lot of computer vision tasks (via LLMs) could be unlocked with this. Think In…
Beats Gemini 1.5 Pro at all but two of the listed benchmarks. Google DeepMind is starting to get their bearings in the LLM era. These are the minds behind AlphaGo/Zero/Fold. They control their own hardware destiny with TPUs. Bullish.
Regarding TPU’s, sure for the stuff that’s running on the cloud. However their on device TPUs lag behind the competition and Google still seem to struggle to move significant parts of Gemini to run on device as a result. Of course, Gemini is provided as a subscription service as well so perhaps they’re not incentivized to move things locally. I am curious if they’ll introduce something like Apple’s private cloud comp…
we need to separate inference and training - the real winners are those who have the training compute. you can always have other companies help with inference