Gunawan L G

Stay curious. Keep learning. Have fun.

[Gunawan L G @gunawanlgm]

What would you do if all jobs paid the same?

[Andrew Ng @AndrewYNg]

Fifteen years ago, @Coursera and online courses changed education. It worked better than almost anyone expected, expanding access by opening up where you can learn. But how you learn remains largely the same as it has for centuries: it is still one-size-fits-all, taught the same way to each person who shows up.

We now have an opportunity to change how learning happens. With advances in AI, we can now build a custom learning guide for each person. We will turn learning from one‑to‑many to one‑to‑one. I'm starting LearnVector to invent this next generation of learning. We are starting with a $100M investment from Coursera, and plan to collaborate closely with Coursera and Udemy.

Good learning needs much more than just a chatbot. Research shows that chatbots without guardrails harm learning. They help complete tasks and enable students to do better on homework. But cognitive offloading to a chatbot results in them being less skilled. And, you cannot always trust what a chatbot tells you.

In contrast, LearnVector will plan a path with you, adapt to how you learn, and patiently stay with you until you’ve mastered new skills.

One thing has not changed in all this time. People want learning they can trust: material that is accurate, relevant, and worth the effort you put into it. Anything less wastes the most valuable thing a learner has: time. Coursera has a trusted library of materials from authoritative sources. LearnVector plans to work with Coursera to bring this trustworthy learning to everyone. I'm grateful to Greg Hart and the entire Coursera team for supporting LearnVector.

I look forward to working with our talented team to change how we learn, and accelerate human development.

https://t.co/TqFUDFd1hb

[levent @__alpoge__]

hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final

((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)

[alphaXiv @askalphaxiv]

Introducing autoresearch for arXiv papers

Change 'arxiv' to 'autoarxiv' in any paper URL

An agent deploys to resolve setup issues on the codebase, run a minimal reproduction, and estimate full replication cost. Read more below

[Anthropic @AnthropicAI]

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.

The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.

Access to all other Claude models is not affected.

We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.

Read our full statement: https://t.co/bwn0sximKZ

[elie @eliebakouch]

mythos will be bad ON PURPOSE on ai "frontier llm research" tasks, this is very very sad for the research community

also the fact that this is un purpose not visible to the user is crazy

[MTS @MTSlive]

SITUATION DETECTED: Google DeepMind’s AI agent autonomously solved 9 of 353 open Erdos problems in mathematics, at a cost of a few hundred dollars per problem.

[🤠 @heavensbvnny]

Neurodivergents texting back (unfiltered):
"Hey! So sorry I didn't text you back for nearly a week (again), my nervous system wouldn't let me open your text until I knew I had time to devote to answering you thoughtfully and thoroughly! But I promise I *thought* about texting you, saw the unopened text, and felt guilty every hour of every day until I finally forced myself...even though now none of this is thoughtful like I planned because it's all an apology instead! Anyways, how are you??"

[Akiyoshi Kitaoka @AkiyoshiKitaoka]

色立体視と薄氷ドリフト錯視

[dino kecepit @ripbotttt]

: itu pandji kenapa?
: dia diserang sana sini
: ampe dr tompi jg?
: iya
: emg dr tompi ngomong apa?
: stup tup tidu daw daw tat tad di da daw barap tidad ti tad daw daw Sing di diw di diw di diw papap

[Kangwook Lee @Kangwook_Lee]

A more serious thread on the DeepSeek-OCR hype / serious misinterpretation going on.

1.
On token reduction via representing text in images, researchers from Cambridge have previously shown that 500x prompt token compression is possible (ACL'25, Li, Su, and Collier).

Without using the idea of converting text to images.

2.
We shouldn't attribute the success of DeepSeek OCR to the power of image representation.

At the same time, there's nothing fundamentally wrong with text representation with whatever tokenizer.

In fact, you can do the opposite of what DeepSeek-OCR did, i.e., you can represent images as a sequence of text tokens (each representing their RGB values), and things will just work fine. (See the LIFT paper.)

3.
The only correct takeaway is that the current embedding spaces used by LLMs are just enormous and maybe even very wasteful.

And importantly, we’re not making full use of them yet.

4.
There is much recent evidence supporting the same message.

For instance, it is shown that if you provide in context demonstrations from multiple tasks but mixed in a single context, then your model can solve multiple ICL prediction tasks simultaneously. (See the EVERYTHING EVERYWHERE ALL AT ONCE paper.)

5.
tldr;
- DeepSeek-OCR is cool
- but you can achieve a higher token reduction rate by just finetuning LLMs on squeezed text tokens
- there is more evidence that LLMs are not fully utilizing the large embedding space and the huge amount of compute that goes in at inference time
- and that's the only real take away you should take away

[vLLM @vllm_project]

🚀 DeepSeek-OCR — the new frontier of OCR from @deepseek_ai , exploring optical context compression for LLMs, is running blazingly fast on vLLM ⚡ (~2500 tokens/s on A100-40G) — powered by vllm==0.8.5 for day-0 model support.

🧠 Compresses visual contexts up to 20× while keeping 97% OCR accuracy at <10×.
📄 Outperforms GOT-OCR2.0 & MinerU2.0 on OmniDocBench using fewer vision tokens.

🤝 The vLLM team is working with DeepSeek to bring official DeepSeek-OCR support into the next vLLM release — making multimodal inference even faster and easier to scale.

🔗 https://t.co/rnBG9VUuMy
#vLLM #DeepSeek #OCR #LLM #VisionAI #DeepLearning

[François Chollet @fchollet]

The 3rd edition of my book Deep Learning with Python is being printed right now, and will be in bookstores within 2 weeks. You can order it now from Amazon or from Manning.

This time, we're also releasing the whole thing as a 100% free website.

I don't care if it reduces book sales, I think it's the best deep learning intro around, and more people should be able to read it.

[gitaputrid @gitaputrid]

Kalau ada aksi penjarahan rumah/usaha lagi tinggal tunggu waktu penetapan tembak di tempat. Lanjut pemberlakuan darurat militer terus mendadak sidang umum MPR amandemen konstitusi dibongkar semua balik ke UUD'45 pra amandemen.

Indonesia, you've been warned.
#ResetIndonesia

[Vlynetta_112 @112Vlynetta]

@WidasSatyo

[Gunawan L G @gunawanlgm]

Belum setahun loh ini astaga.

[Illia @Zieeett]

Nano Banana: Make Image Daytime and Isometric (Building Only)

[Sukjun (June) Hwang @sukjun_hwang]

Tokenization has been the final barrier to truly end-to-end language models.

We developed the H-Net: a hierarchical network that replaces tokenization with a dynamic chunking process directly inside the model, automatically discovering and operating over meaningful units of data

[blue @bluewmist]

we have normalised overconsumption. listening to a podcast while we walk, scrolling reels in the toilet, listening to music while we cook, watching a show on Netflix while we eat. it’s as if there is NO breathing space for your mind. you’re constantly trying to fill the void, the stillness and yet here you’re complaining about feeling groggy and demotivated.

[Gunawan L G @gunawanlgm]

@hadijahlarasti @zhafirarianar @gitaptrn Serem ey tiba2 ada banyak kaki lima 👀