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aleccoHNSource author
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The best and latest Gemini Pro model is not SOTA

The best and latest Gemini Pro model is not SOTA. The only good things it has are the huge context and the low API price. But I had to stop using it because it kept contradicting itself in the walls of text it produces. (My paid account was forced to pay for AI with a price hike so I tried for a couple of months to see if I could make it work with prompt engineering, no luck). Google researchers are great, but Engineering is dropping like a stone, and management is a complete disaster. Starting with their Indian McKinsey CEO moving core engineering teams to India. https://www.cnbc.com/2024/05/01/google-cuts-hundreds-of-core...

Original discussionGitHub is no longer independent at Microsoft after CEO resignation1,121 source comments · at import
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theptipHN

> Google has world-class research teams that have produced unbelievable models, without any plan at all on how those make it into their products beyond forcing a chat window into Google Drive. NotebookLM is a genuinely novel AI-first product. YouTube gaining an “ask a question about this video” button, this is a perfect example of how to sprinkle AI on an existing product. Extremely slow, but the obvious incremental addition of Gemini to Docs is another example. I think folks sleep on Google around here. They are slow but they have so many compelling iterative AI usecases that even a BigTech org can manage it eventually. Apple and Microsoft are rightly getting panned, Apple in particular is inexcusable (but I think they will have a unique offering when they finally execute on the blindingly obvious strategic play that they are naturally positioned for).

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jemmywHN

There are problems with every model, none of them are perfect. I've found Gemini to be very good but occasionally gets stuck in loops: it does, however, seem to detect the loop and stop. It's more cost effective than the Claude models, and Gemini has regular preview releases. I would rate it between sonnet and opus except it's cheaper and faster than both. For whatever reason there are tasks that work better on one model compared to another, which can be quite perplexing.

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navigate8310HN

No amount of big context window can stop the model from context poisoning. So in a sense, it's a gimmick when you start having the feel of how bad the output is.

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