05

Newly out

Official announcements that companies such as OpenAI, Google, Hugging Face and AWS posted on their own blogs — new features, new services, how to use their products.

A company writing about its own product tends to lead with the good parts. Posts like these carry no vote counts, so the card shows only the date.

What turned up in the last three days — collected by machine, published by hand.

What gets picked here ends up in What I took apart →

Collected 2026-10-15 23:01 UTC · 44 kept from 418

Source Hugging Face BlogNew
Granite Switch 4.1: Chat, Decisions, and Speech from One Endpoint

Oct 15

no limits stated829 words

What we saw

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

They claim — In a “Race” between Granite-Switch-4.1-30B (frozen base Granite + 4 specialized aLoRAs) and Jev-27B (frozen base Qwen model + 1 generic decision LoRA), Granite-Switch-4.1-30B was able…

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · 58422c23d696b293

Torn from — the page itself

Source OpenAINew
Bringing GPT-Rosalind to academic research labs

Oct 15

What we saw

“Introducing the Rosalind Academic Plan, offering eligible academic labs sponsored access to GPT-Rosalind and tools to advance l…”

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · 6d9d156035ebcbb1

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

Source AWS ML BlogNew
Meta’s Muse Spark Open now available in Amazon SageMaker JumpStart

Oct 15

no limits stated1.9k words

What we saw

“Muse Spark Open, Meta's coding-optimized open-weight model, is now available in Amazon SageMaker JumpStart. Deploy it to a Sage…”

They claim — p6-b300.48xlarge modelid = "meta-vlm-muse-spark-open-816b-a42b-nvfp4" jumpstartconfig = JumpStartConfig( modelid=modelid, accepteula=True, # Confirms that you accept Meta's license terms …

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · bfa295e4cfe2ab36

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

Source AWS ML BlogNew
Trust in Depth: Giving agents more autonomy without losing control

Oct 15

states limits2.7k words

What we saw

“Enterprise leaders want AI agents to take on more work but don't fully trust them to act correctly every time. Trust in Depth i…”

They claim — AWS has run automated reasoning in production for more than a decade, from Identity and Access Management (IAM) at more than 2.1 billion requests per second to critical systems like the A…

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · 5b5b08e75438e6a6

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

Source OpenAINew
Teaching students to think and learn through questions

Oct 15

What we saw

“Celebrate Teachers’ Day with AI for Educators in Brazilian Portuguese and see how Study Mode can help teachers support active…”

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · 1fffc348f7c5ce20

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

Source Google DeepMindNew
TIME has named Google SynthID one of the Best Inventions of 2026.

Oct 15

no limits stated241 words

What we saw

“TIME named Google SynthID a Best Invention of 2026 for its groundbreaking approach to AI watermarking and verification.”

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · 2e69e97ed9d7a04e

Torn from — the page itself

Source Hugging Face BlogNew
Apertus 1.5 Release Notes

Oct 15

no limits stated2.3k words

What we saw

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

They claim — Our latest release, Apertus 1.5, extends the 8B and 70B Apertus 1.0 models with image/audio understanding, an optional thinking mode, a four times longer context window, improved instruct…

Published 2026-10-15

Fetched 2026-10-15 23:01 UTC · 17694eda65b0ffea

Torn from — the page itself

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.