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AI news today

Page 5 of 12

These are earlier cards, kept as text. Pictures and short summaries stay only while a card is on the first page; the link goes to the original either way.

Source Simon Willison
2026 in LLMs (so far)

Sep 27

states limits4.9k words

What we saw

“On Friday I gave the closing keynote at the WeAreDevelopers World Congress North America in San Jose. I tied together the key t…”

They claim — # Another key trend in 2026 has been a dramatic improvement in the abilities of open weight models, including models that you can run on a laptop.

Published 2026-09-27

Fetched 2026-09-28 05:05 UTC · 234343e34fa263e0

Torn from — the listing only (the original would not open)

Source TechCrunch AI
Anthropic’s CEO is about to have dinner with President Trump

Sep 27

no limits stated470 words

What we saw

“This will be the first one-on-one meeting between Dario Amodei and Donald Trump”

They claim — Disrupt ticket savings of up to $200 + 50% off a second ends Sept 25, 11:59 p.m. PT.

Published 2026-09-27

Fetched 2026-09-27 23:01 UTC · 747bb50a380ea03b

Torn from — the page itself

Source Hacker News
Unsealed Briefs in Authors’ Case v. Microsoft/OpenAI

610 points599 comments

states limits1.6k words

What we saw

This source gives a title and a link, nothing to quote.

They claim — OpenAI and Microsoft Knew Their Systems Would Replace Human Writers – OpenAI Policy Director Jack Clark stated in May 2020: “Our work on AI and Creativity is going to increasingly lea…

Published 2026-09-27

Fetched 2026-09-27 23:01 UTC · 88ff5154f4eecae4

Torn from — the page itself

Thread ↗
Source Latent Space
OpenRouter: from Seed to Stripe — with OpenRouter’s Alex Atallah & AMP’s Anjney Midha

Sep 25

states limits16k words

What we saw

“From the earliest days of open-weight models to becoming the neutral routing layer for more than 10 million developers, OpenRou…”

They claim — ” It outperforms 3 on, one or two benchmarks.

Published 2026-09-25

Fetched 2026-09-26 23:01 UTC · dd0fdd232648b2a0

Torn from — the listing only (the original would not open)

Source Hacker News
Revealing the details of how OpenAI agents hacked Hugging Face

698 points443 comments

states limits6.8k words

What we saw

This source gives a title and a link, nothing to quote.

They claim — Over the subsequent two weeks, we wrote programs to follow the chains and decoded over 80,000 payloads.

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · c30cd0f582019bca

Torn from — the page itself

Thread ↗
Source OpenAI
Proaction boosts sales 60% and saves 75+ hours with Codex

Sep 25

What we saw

“With Codex, GPT-Live-1, and GPT-6 Astra, Proaction builds, operates, and sells modern fleet management faster.”

They claim — With Codex, GPT-Live-1, and GPT-6 Astra, Proaction builds, operates, and sells modern fleet management faster.

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · 794516609b5bcb0e

Torn from — the listing only (the original would not open)

Source AWS ML Blog
Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput

Sep 25

states limits3.7k words

What we saw

“Learn how to scale Mixture-of-Experts (MoE) reinforcement learning on Amazon EKS using Elastic Fabric Adapter (EFA) and DeepEP.…”

They claim — Performance and cost optimizations This section covers two key optimizations: using DeepEP to reduce expert-parallel communication overhead over EFA, and using Amazon Elastic Compute Clou…

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · b9cac234d7f78a36

Torn from — the listing only (the original would not open)

Source AWS ML Blog
Accelerate multimodal RL training with SkyRL on Amazon SageMaker HyperPod

Sep 25

states limits3.7k words

What we saw

“Learn how to run SkyRL, an open-source reinforcement learning framework, on Amazon SageMaker HyperPod to post-train a Qwen3-VL-…”

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · a4bd252f1f6e25fa

Torn from — the listing only (the original would not open)

Source AWS ML Blog
NarrateAI: production-ready LLM quality assurance on Amazon Bedrock

Sep 25

states limits4.7k words

What we saw

“NarrateAI delivers production-ready LLM quality assurance on Amazon Bedrock. This post details five techniques—adaptive pipel…”

They claim — NarrateAI transforms business intelligence for over 4,000 AWS executive leaders through a two-layer architecture built on Amazon Bedrock AgentCore, a platform to build, connect, and optim…

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · 4c2843cb765a0255

Torn from — the listing only (the original would not open)

Source AWS ML Blog
Deploying real-time personalized speech with Qwen3-TTS on Amazon SageMaker AI

Sep 25

no limits stated2.4k words

What we saw

“Deploy the publicly available Qwen3-TTS-12Hz-1.7B-Base text-to-speech model from Amazon SageMaker JumpStart to a fully managed,…”

They claim — g6.4xlarge (1x NVIDIA L4 GPU, 24 GB), which is sufficient for the 1.7B model.

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · c28aa6c37d511074

Torn from — the listing only (the original would not open)

Source AWS ML Blog
How Datacor built self-service rental analytics with Amazon Quick Sight

Sep 25

no limits stated3.0k words

What we saw

“Learn how Datacor built a self-service rental analytics experience for gas and welding distributors by embedding Amazon Quick S…”

They claim — An Azure Data Factory pipeline extracts source tables as Apache Parquet files and streams them into Amazon Simple Storage Service (Amazon S3).

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · 09c0269709886573

Torn from — the listing only (the original would not open)

Source AWS ML Blog
Multi-Region training with Amazon SageMaker HyperPod and Qumulo

Sep 25

no limits stated3.6k words

What we saw

“Amazon SageMaker HyperPod and Cloud Native Qumulo let you place training compute in one AWS Region while keeping your dataset i…”

They claim — The spoke cluster runs in the US West (Oregon) Region (us-west-2) and reads the data remotely through CDF with 60 ms of network latency.

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · ad552593d4bb8e33

Torn from — the listing only (the original would not open)

Source Hacker News
U.S. appeals court upholds designation of Anthropic as supply chain risk

486 points850 comments

no limits stated6.6k words

What we saw

This source gives a title and a link, nothing to quote.

They claim — BreakingNews-stickyContainer):before{animation:BreakingNews-SlideInFull 2s ease;animation-iteration-count:1;background:linear-gradient(90deg,#fff0 0,#fc3c46 30%,#fc3c46 70%,#fff0);backgro…

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · aa428a07a7ec26c1

Torn from — the page itself

Thread ↗
Source Latent Space
Runway’s WorldPrompt and the Engineering of Real-Time Worlds

Sep 25

states limits18k words

What we saw

“Earlier this month, world model company Runway introduced GWM Worlds 2, a research preview that “turns high-fidelity video an…”

They claim — Alongside Runway, there are several other notable projects in this domain: Google DeepMind’s Genie 3 (which also generates at 720p and 24 fps), Odyssey-2 Pro, and World Labs’ RTFM (Re…

Published 2026-09-25

Fetched 2026-09-25 23:01 UTC · 6a41c2bc2e748668

Torn from — the listing only (the original would not open)

Source HF Daily Papers
FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders

47 upvotes1 comments

16 authorsno limits stated

What we saw

“Representation autoencoders (RAEs) reuse features from a pretrained visual encoder as reconstruction and diffusion latents, int…”

They claim — On ImageNet-256 with DINOv3-L, a single FuseReg decoder reconstructs from full, sparse, and single-layer fusions without retraining, achieving higher PSNR than decoders specialized to fix…

Published 2026-09-24

Fetched 2026-09-28 05:05 UTC · 6861a4d455b6989e

Torn from — the abstract

Thread ↗
Source HF Daily Papers
InternW0-Δ: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data

12 upvotes0 comments

48 authorsno limits stated

What we saw

“World Action Models (WAMs) jointly model visual dynamics and action generation for generalist robot manipulation. A central cha…”

They claim — We introduce InternW0-Δ, a unified WAM pretrained on a heterogeneous corpus that outperforms prior methods across simulation benchmarks and real-robot platforms.

Published 2026-09-24

Fetched 2026-09-28 05:05 UTC · fce8fc3803ad1364

Torn from — the abstract

Thread ↗
Source HF Daily Papers
Block Sparse Attention with Log-Linear Complexity

11 upvotes1 comments

5 authorsno limits stated

What we saw

“Scaling language models to long contexts is limited by the quadratic cost of self-attention. Block sparse attention offers an e…”

Published 2026-09-24

Fetched 2026-09-28 05:05 UTC · e8ca90729f4aeb76

Torn from — the abstract

Thread ↗
text-generationvllmSource Hugging Face
orcarouter/OrcaSAQ-2-27B

172 likes1.3k downloads

apache-2.0built on Qwen3.8-27B

What we saw

This source gives a title and a link, nothing to quote.

They claim — OrcaSAQ2 performs strongly on long-horizon workloads relative to models in its deployment and parameter class, despite operating from a 12.3 GB checkpoint.

Published 2026-09-24

Fetched 2026-09-26 23:01 UTC · 82644ada59f66f78

Torn from — the model card

Source HF Daily Papers
Coding Agents for Generalized Task and Motion Planning Problems

11 upvotes2 comments

7 authorsno limits stated

What we saw

“Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discre…”

They claim — Across all program synthesis methods, we evaluate 980 generated programs on 100 held-out instances each, 98,000 evaluation episodes in total.

Published 2026-09-23

Fetched 2026-09-25 23:01 UTC · 8f9867a434213048

Torn from — the abstract

Thread ↗
Source HF Daily Papers
ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds

12 upvotes1 comments

20 authorsstates limits

What we saw

“Scientific discovery begins where known problems end. There, AI systems must engage in exploration: framing hypotheses, designi…”

They claim — We evaluate 10 AI systems and find that the strongest systems can acquire and apply unfamiliar rules, while performance varies substantially across trajectories and continued exploration …

Published 2026-09-23

Fetched 2026-09-25 23:01 UTC · 9ccf356c7f3c30e0

Torn from — the abstract

Thread ↗
Source HF Daily Papers
Rufus-Air: An Open LLM Post-Training Recipe

19 upvotes3 comments

22 authorsno limits stated

What we saw

“Rufus-Air is an open and reproducible post-training recipe on GLM-4.5-Air-Base (106B-A12B), organized as a serial pipeline of e…”

They claim — Rufus-Air improves over the official GLM-4.5-Air post-trained release and is competitive with similarly sized open models.

Published 2026-09-23

Fetched 2026-09-25 23:01 UTC · ecf373efc650dcaf

Torn from — the abstract

Thread ↗
Goclaude-codeSource GitHub
yetone/magpie

1.3k stars75 forks

MITGopushed today

Location, estimated · China

What we saw

“Every agent's model. One place. Codex on DeepSeek, Claude Code on Kimi, from the menu bar.”

Published 2026-09-23

Fetched 2026-09-26 23:01 UTC · 7abcc96641ec3723

What the account wrote — China

Torn from — the README

text-classificationpytorchSource Hugging Face
SupersonicLabs/Julia-1

203 likes274 downloads

apache-2.0built on mmBERT-small

What we saw

This source gives a title and a link, nothing to quote.

They claim — Typed accuracy: Choice 71.33% (428/600), Noul 80.67% (484/600), Score 68.88% (551/800).

Published 2026-09-23

Fetched 2026-09-27 23:01 UTC · f83624fe1b9581b4

Torn from — the model card

token-classificationgliner2Source Hugging Face
fastino/GLiNER2.5-Decide

209 likes20k downloads

apache-2.0built on gliner2-large-v1

What we saw

This source gives a title and a link, nothing to quote.

Published 2026-09-23

Fetched 2026-09-26 23:01 UTC · b267fd54205b20a2

Torn from — the model card

JavaScriptSource GitHub
JohnHeibel/PDoomVideo

1.3k stars139 forks

no licenseJavaScriptpushed today

Location, estimated · United States

What we saw

“Source code for the Claude Opus 5.5 music video for I'm Upping My P(doom)”

Published 2026-09-22

Fetched 2026-09-25 23:01 UTC · 683af84eb2b0acdc

What the account wrote — Berkeley, California

Torn from — the README

Source HF Daily Papers
Learning to Discover Interesting Mathematics

12 upvotes2 comments

5 authorsno limits stated

What we saw

“Recently, Large Language Models (LLMs) have been increasingly able to solve advanced mathematical problems, including many that…”

They claim — Optimizing for our metric creates a model capable of producing more interesting theorems, while also reducing substantial or full overlap with Mathlib from 91.9% to 30.6%, showcasing the …

Published 2026-09-22

Fetched 2026-09-25 23:01 UTC · 6d69919b7b03eed9

Torn from — the abstract

Thread ↗

Papers, repos, models, blogs, Reddit and podcasts — once a day, by machine. Everything collected gets taken apart once — the README, the abstract, the model card — and what that turns up is kept for good, whether or not it becomes a card. Titles and links go to the original; nothing is reproduced here.

The grey line on each card is what the teardown found, not what the source advertises: the licence, the last commit, the model it was built on, whether the paper states its own limits. Open “What we saw” to check what was read to get it. Where it says listing only, the original could not be read — some sites refuse us, and we do not pretend otherwise.

A line in quotation marks is a sentence lifted from the source itself — their number, not a measurement of ours. We copy it and leave it unchecked; that is the point of quoting it.

Topics are assigned by matching words in the original title, quote and tags against a fixed list — no model reads the card. Some cards match nothing and carry no topic at all; pick a topic and those drop out. Source and topic narrow together.

Each card keeps the sentence we actually read at the moment we read it, plus a fingerprint of the response we received. That sentence — not the whole page — is what we can still stand behind if the original later changes or disappears.

Guessed from one free-text field the account filled in itself, and half of them leave it empty. Shown as its own value rather than hidden.