🚨 New Paper Alert! 🚨
How does AI bias manifest in an incredibly diverse nation like Indonesia? 🇮🇩
If you think AI bias is complicated in the US, try looking at Indonesia.
With hundreds of ethnicities/languages and a multi-party democracy (yes we have like 10+ parties), i.e LLMs heavily favor massive majority groups (like Sundanese) while completely sidelining marginalized ones (like Korowai).
paper link: https://t.co/2sU0NT4UW0
Fable is an early look into the bureaucratic hell Anthropic wants to create in AI.
3 month delay to get released.
Randomly routed in biology, cyber and distillation.
Weird sociopathic quiet harmfulness in ml topics.
Goes away on June 22.
Have to apply to get access to 'real' Mythos.
What an exhausting tiresome dystopia.
Everybody is scared of Chinese models because it won’t let you criticize the CCP while Anthropic won’t let me use their models for live saving medical research ?
Who’s the real villain again?
One of the most overlooked forms of wealth is having complete ownership of your time.
Waking up and knowing nothing about your day will be decided by someone else is priceless.
d akun lamaku, ad mahasiswa dr ntb, dm aku cerita klo dia lolos lowker barista d outlet semarang stlh sblmny kerja di sppg..
akhirny ta intvw dadakan onlen, aku cm nanya 2 hal :
1. knp smrg?
2. knp out dr sppg?
akhrny dia cerita, slma krja d sppg dia feeling overwhelmed krn
Buka Instagram : hidup orang kok enak-enak banget ya jalan-jalan mulu mereka
Buka X : Tempat hidup orang-orang stress,ngeluh dan menghujat pemerintah 😂
As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development
"Any topic related to building pretraining pipelines, distributed training infrastructure, or ML accelerator design... may have limited effectiveness through Claude via methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning."
Not only do they get to decide what you use LLMs for in research, but this also enables them to silently intervene in your research without you knowing.
This sets a dangerous precedent. If a model refuses openly, users can understand the boundary. If a model falls back to another model, users can still evaluate the difference. But if a model silently modifies or weakens its own answers while still pretending to help, researchers lose the ability to know whether a failed result came from their own idea, their implementation, or an invisible intervention by the model provider.
That is not safety. Safety policies should be transparent, auditable, and user-visible.
On top of that, the people most harmed by this are not the largest labs with massive teams and proprietary infrastructure. It is the independent researchers, academic groups, startups, and open-source builders who rely on public tools to compete, innovate, and pioneer AI for everyone else.
As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development
"Any topic related to building pretraining pipelines, distributed training infrastructure, or ML accelerator design... may have limited effectiveness through Claude via methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning."
Not only do they get to decide what you use LLMs for in research, but this also enables them to silently intervene in your research without you knowing.
This sets a dangerous precedent. If a model refuses openly, users can understand the boundary. If a model falls back to another model, users can still evaluate the difference. But if a model silently modifies or weakens its own answers while still pretending to help, researchers lose the ability to know whether a failed result came from their own idea, their implementation, or an invisible intervention by the model provider.
That is not safety. Safety policies should be transparent, auditable, and user-visible.
On top of that, the people most harmed by this are not the largest labs with massive teams and proprietary infrastructure. It is the independent researchers, academic groups, startups, and open-source builders who rely on public tools to compete, innovate, and pioneer AI for everyone else.
mau balikin lagi jadi ORBA makannya fokusnya sekarang ke LGBT, dollar otw 20 ribu? apa itu? kriminalkan Gay yang party di club malam karena viral lebih penting!! bensin naik? harga pangan naik? ahh apaan? anak2 masih bisa MBG makanan basi kok, kita ini negara hebat🫡
This is the last completely Christian village in the Holy Land. This is what Israel just did to it. Are you going to do anything about it, Ambassador Huckabee? @USAmbIsrael
1- AI-generated code just creates more technical debt.
2- At the end of the day, you (the developer) are responsible for the code, not the LLM that generated it. So the less code you have, the easier it is for you to own it.
3- A good engineer knows what code to write, and equally importantly, what code not to write or to delete.
(BTW, this is what we old-school software engineers have been saying for a long time, and we've been called all sorts of names for it.)
Bayangin rakyat cari kerja harus ngelewatin psikotes, online assessment, interview HR, FGD, interview user, sampe direksi. Sementara yang jadi presiden ngitung 10 + 6 = 17 ☺️😇