Meta's new Llama-4 is Full of Controversies...
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Top Comments (10)
"Since it's open source everyone can fix it" > illegal to use in the EU
It feels like there's a secret sauce to make models better at coding. I have a small piece of JavaScript (originally created by an older LLM and faulty), that I use to measure LLM bug fix performance. There have been a lot of open weight models since around beginning last year, that manage to create the fixed code just fine, but they're usually 8B or above and not fully open source. I even tested some 12B-14B reasoning models and they mostly failed spectacularly after thousands of tokens. Either these models have never seen a piece of JavaScript, are overtrained on Python or there is a secret training set, the open source community doesn't have.
thank you for briefly explaining the difference between dense and moe as well as active parameters. from all these ai channels, i think you might be the best one. love your content and explainations!
Llama-4 is already asking for vacation days?
1.5B model outperforming 109B is funny
Visualize your AI content creation workflow now with poppy AI https://start.getpoppy.ai/bycloud and use the coupon code “BYCLOUD” for $25 off any plans!
I agree it is odd. And where are there smaller models? What's going on?
Maybe we reached the peak usecases of transformer? Maybe newer improved algorithms like MAMBA??
I've found all of the Llama models/generations to be generally really underwhelming tbf, so not surprised by this.
You've been the best in AI news and overviews for years now and with great humor. glad I came across you
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Top Comments (10)
"Since it's open source everyone can fix it" > illegal to use in the EU
It feels like there's a secret sauce to make models better at coding. I have a small piece of JavaScript (originally created by an older LLM and faulty), that I use to measure LLM bug fix performance. There have been a lot of open weight models since around beginning last year, that manage to create the fixed code just fine, but they're usually 8B or above and not fully open source. I even tested some 12B-14B reasoning models and they mostly failed spectacularly after thousands of tokens. Either these models have never seen a piece of JavaScript, are overtrained on Python or there is a secret training set, the open source community doesn't have.
thank you for briefly explaining the difference between dense and moe as well as active parameters. from all these ai channels, i think you might be the best one. love your content and explainations!
Llama-4 is already asking for vacation days?
1.5B model outperforming 109B is funny
Visualize your AI content creation workflow now with poppy AI https://start.getpoppy.ai/bycloud and use the coupon code “BYCLOUD” for $25 off any plans!
I agree it is odd. And where are there smaller models? What's going on?
Maybe we reached the peak usecases of transformer? Maybe newer improved algorithms like MAMBA??
I've found all of the Llama models/generations to be generally really underwhelming tbf, so not surprised by this.
You've been the best in AI news and overviews for years now and with great humor. glad I came across you