aalquwayfili

security specialist @houseofhades

[polars data @DataPolars]

We just released Polars 2.0.

It removed many of our legacy decisions makes the streaming engine our default and promotes SQL to a first class citizen within Polars.

It comes with initial out-of-core (spill to disk) support, a new Map data type and a lot of performance improvements. In fact, we think Polars is now one of the fastest analytical SQL engines on a single node. See benchmarks in the post: https://t.co/ATc6UzJqby

[Larry Dial @classiclarryd]

New historic NanoGPT record at 39.9s (-27.7s) from @DevenPzak , obliterating the prior record of 67.6s!

This record introduces a new paradigm of thinking to NanoGPT: instead of optimizing matmuls or adding more expressive operations, optimize at the individual flop level with incredibly clever engineering and ML judgement. If a flop is low value on a particular step, skip it.
Specifically:
-(~8s) Sampled softmax. If a token doesn’t appear in a batch, skip its lm_head fwd/bwd some fraction of the time.
-Sparse values. Only run an optimizer step for ngram embeddings that occurred in the batch. Set beta1 to zero to enable this. Beta2 is applied retroactively when the row is later used.
-Sparse updates. Only update ngram and value embeddings once every 4 steps instead of once every 2.
-Sparse communication. Shard the n-gram table across GPUs, and only pass the rows receiving updates on each step.
-Sparse optimizer states. For the n-gram table, reduce from 2 floats in Adam optimizer per param, to 1 float per 768 params.
-Hand-rolled flash attention for 64 dim heads.

There are several additions that add accuracy too:
-(~4s) EMA during last 300 steps, combined with lifting final_lr to 0.3 instead of 0.15.
-(~1s) A new optimizer, Anvil2, which expands muon via a second tracked momentum buffer, improves the ortho coefficients, and modifies the cautious weight decay application.
-A couple additional dynamic skip connections in the network.

The most striking consequence of the ‘flop aware paradigm’ is you can grow parameters arbitrarily large,
only limited by the available memory, since you can selectively choose how to expend flops on those parameters on each step. NanoGPT has kept active parameters below 124M, but total is unbounded, and has grown to 640M through embedding sparsity over the last year. This PR takes that to its logical conclusion on the 8xH100, scaling up to 65B sparse embedding parameters, which accounts for 25% of the PR’s gains. At frontier scale, where one is not bounded by an 8xH100, one could imagine where this paradigm could lead.
https://t.co/Ycrzy6JFC3

As this was a very notable PR, I spoke with Deven for an hour to learn how he did it. Here’s his story on the changes: https://t.co/YEfM1VpOTi

[قافية @QafiyahX]

نشكر @forbiddenkeygen على رابع مساهمة: اكتشاف وإصلاح حيلة تتيح للمستخدم تجاوز حد معدل الطلبات (rate-limit bypass)
https://t.co/UqgtVrQuid

[aalquwayfili @forbiddenkeygen]

more at https://t.co/f5czRYq4TS

[aalquwayfili @forbiddenkeygen]

opus 5.5 built KAFD in LEGO with one prompt

[NVIDIA AI @NVIDIAAI]

When several people talk at once, a transcript can get messy fast.

Our new Nemotron 3 Diarization model tracks who spoke when, even when voices overlap. It handles up to eight speakers, has 100M parameters, and is now available on @huggingface 🤗

[ممدوح الظفيري @MamdouhAI]

ندور ناس معضلة!

قاعدين نكبر في https://t.co/FRMDczY6Rm بشكل كبير وندور ناس رهيبة تشاركنا الرحلة، ندور عن رهيبين بالمنتج والهندسة والمبيعات والعمليات وووو

راح اشارك معكم الايام الجاية اشياء اكثر عننا!!

https://t.co/KSGOx1YJRu

[Jeff Dean @JeffDean]

Announcing Discovery Loop!

I am very excited to announce that, along with my longtime friends and collaborators @Sanjay_Ghemawat, @OriolVinyalsML and @quocleix, we are founding Discovery Loop (@DiscoLoopAI), a Public Benefit Corporation whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress. The four of us have worked together for 14 to 30 years, and have helped build some of the world’s most used products, infrastructure and AI models, and we’re excited to turn our attention to this ambitious endeavor.

♾

Learn more at: https://t.co/Rv3LMdLluK

[Claude @claudeai]

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.

Its capabilities exceed those of any model we’ve ever made generally available.

[Charles 🎉 Frye @charles_irl]

eval for video models: generate an entire new Lord of the Rings movie from scratch

call that next-Tolkien prediction

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Harvard Saudi Students Association @HarvardSaudi]

تشرفنا باستضافة تركي بن زرعه @Turki_Z، الشريك المؤسس والرئيس التنفيذي للعمليات لشركة تمارا، في جلسة حوارية بالتعاون مع نادي الشرق الأوسط وشمال أفريقيا في هارڤارد، والتي أدارتها عضوتنا وطالبة الماجستير نورة الحسين. مع جزيل الشكر لضيفنا الكريم على مشاركته خبراته من إحدى أبرز شركات التقنية المالية في المنطقة، وللحضور على تفاعلهم.

[Claude @claudeai]

Claude now connects to the tools creative professionals already use.

With the new Blender connector, you can debug a scene, build new tools, or batch-apply changes across every object, directly from Claude.

[aalquwayfili @forbiddenkeygen]

@z41sh