AI video with Pika 1.0 made by @Diesol
— Pika (@pika_labs) 6 décembre 2023
pic.twitter.com/kv4Y60UXNM
AI video with Pika 1.0 made by @Diesol

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AI video with Pika 1.0 made by @Diesol
— Pika (@pika_labs) 6 décembre 2023
pic.twitter.com/kv4Y60UXNM
AI video with Pika 1.0 made by @Diesol
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Gemini Pro is available right now and you can check it out in Bard. That version, according to Google, is slightly better than GPT-3.5, so in other words Gemini in production is about a year behind OpenAI's capabilities. 3/4
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It remains to be seen if they can close that gap in the upcoming months, as I'm sure @OpenAI has also been working diligently on their next generation model. Read the full blog post announcement here: https://
blog.google/products/bard/
google-bard-try-gemini-ai/
… #AI #ArtificialIntelligence #GenerativeAI #GenAI 4/4

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The benchmarks that Google shared for Gemini Ultra look really impressive, and seem to be generally beating GPT-4 in almost all categories. However, as of right now, Gemini Ultra is still not available, and will not be available until some time early next year. 1/4
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Here I am trying to figure out how I can get MTEB scores for Titan and PaLM embeddings and doing GPU hour math and I'm not cool enough to get a technical report for a Big Boy Model from Google.
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Still reading through the model card/report on Gemini (which I did not make the pre-brief cut for this one, alas) so issue will be coming later due to getting called in for jury duty yesterday!
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(Also very much a missed opportunity for Google to rename hallucinations here, which is a terrible name for it.)

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Data quality > data quantity, as we've been talking about since september :). Fun part here, it includes examples where Gemini intentionally throws up its hands (like another model out there). You'd be surprised how useful people think this is. https://
supervised.news/p/ai-in-septem
ber-reasoning-engines
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Tell a story in any style with Gen-2.https://t.co/ekldoIshdw pic.twitter.com/iq6IuWHlkz
— Runway (@runwayml) 6 décembre 2023
Tell a story in any style with Gen-2. http://
runwayml.com

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And Google now running with Meta's approach of training smaller models with massive data sets. If you're curious about size, the open source RedPajamas open data set is 30T tokens. We can prob safely assume Google has access to much more.