601–610 of 692 posts
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Yeah, Google chose a misleading title for the blog post.
> Today, we’re introducing Gemini 3.5, our latest family of models combining frontier intelligence with action. This represents a major leap forward in building more capable, intelligent agents. We’re kicking off the series by releasing 3.5 Flash.
For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know. We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute c…
A nice estimate! Since „you can compress knowledge, but not factual knowledge” https://x.com/bojie_li/status/2049314403208896521 , it is likely we can actualy measure its size.
It seems to be a huge overshot, vide Hy3 model, which this model claims to be 2.4T, while it is 295B.
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Can you try with a more complex story such as "three little pigs"? I tried but it created a storybook instead of the SVG animation. I am looking to partially imitate Godogen [1][2] which is really great, even for animations. [1] https://github.com/htdt/godogen [2] https://drive.google.com/file/d/1ozZmWcSwieZQG0muYjbj7Xjhhlz...
I think it's unreasonable to expect models generate complex stories in single prompt since they trained to be concise, but I tried. This is prompt on top of story with no control buttons request: Now think, plan how to tell this story in a cartoon, make scene outline and then generate SVG animation story for "Three Little Pigs" in self contained HTML page. Just single animation no control buttons. Full prompt in gist…
For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know. We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute c…
If two things hold up - 1) this is actually a 2-300B parameter model and 2) this is actually competitive with frontier OpenAI and Anthropic models (and not just benchmaxing), the implications are pretty big. It would mean you could run "frontier level" performance in one box at home. 300B models at least fit in a single maxed out Mac Studio or a small stack of DGX Sparks or AMD Strix Halo boxes. For comparison, DeepS…
That wouldn't surprise me at all actually, models like Qwen3.6-35B are comparable to frontier level models from a year ago and I wouldn't be surprised if we had self-hostable open weight models matching Opus 4.7 in a year. Assuming that Google has one year of advance against Chinese lab isn't far fetched given how much resources they have compared to their Chinese competitors.
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Yeap it russian, but the whole russian sentence doesn't make any sense, just messed words with no meaning at all :)
But the voice and pauses sounds so much real, it's hard to say "it was ai", sounds like a real human
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Wow that's terrible. Any idea why?
Did you see the other ones? This is very good by comparison.
I played the audio readout of the page, what is the last 30 secs in the readout?
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We've been really impressed with the performance of ~30B parameter class models and how close they are to the frontier from ~6-12 months ago, which begs the question, are the frontier labs really serving 10T parameter models? Seems unlikely. If these Gemini 3.5 numbers are accurate, then I'd wager GPT 5.5 and Opus 4.7 are a lot smaller than people have speculated, too. It's not that frontier labs can't create a 5T+ p…
Elon says Opus is 5T (and I would expect he'd know) > It's not that frontier labs can't create a 5T+ parameter model, but they don't have the data to optimize a model of that size. The have plenty if data. They use very large amounts of verifiable synthetic data in (lots in coding and math) cover the gap. Also the frontier labs are paying people to do tasks, tracking the trajectories and training on that. Most of the…
So where does humanity cap out? The statement more or less implies that there's a ceiling of our ability to train models which might be below what LLMs are capable of (e.g. not AGI but how good coding agents they might ever become, for example).
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If two things hold up - 1) this is actually a 2-300B parameter model and 2) this is actually competitive with frontier OpenAI and Anthropic models (and not just benchmaxing), the implications are pretty big. It would mean you could run "frontier level" performance in one box at home. 300B models at least fit in a single maxed out Mac Studio or a small stack of DGX Sparks or AMD Strix Halo boxes. For comparison, DeepS…
> the implications are pretty big. It would mean you could run "frontier level" performance in one box at home. That wouldn't surprise me at all actually, models like Qwen3.6-35B are comparable to frontier level models from a year ago and I wouldn't be surprised if we had self-hostable open weight models matching Opus 4.7 in a year. Assuming that Google has one year of advance against Chinese lab isn't far fetched gi…
It's not yet obvious to me that you can achieve the breakthrough performance of say Opus 4.1/4.5 in a number of parameters you can swing at home.
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We've been really impressed with the performance of ~30B parameter class models and how close they are to the frontier from ~6-12 months ago, which begs the question, are the frontier labs really serving 10T parameter models? Seems unlikely. If these Gemini 3.5 numbers are accurate, then I'd wager GPT 5.5 and Opus 4.7 are a lot smaller than people have speculated, too. It's not that frontier labs can't create a 5T+ p…
Elon says Opus is 5T (and I would expect he'd know) > It's not that frontier labs can't create a 5T+ parameter model, but they don't have the data to optimize a model of that size. The have plenty if data. They use very large amounts of verifiable synthetic data in (lots in coding and math) cover the gap. Also the frontier labs are paying people to do tasks, tracking the trajectories and training on that. Most of the…
Even if he knew, why would anyone expect Elon not to lie about anything?
> The have plenty if data.
I don't think data is the problem either, but compute is: if you want to train your 5T params model like modern small models are being trained (with a thousands time more training tokens than params), that's an enormous training run.