News World

Artificial Intelligence
Vol. I · Issue September 11, 2026 4 minutes

News World AI

Hello,

This issue is built around one question: can you assemble a news pipeline run by machines, from collection to editing? Five layers, six real tools, one hole at the second, and the bill that comes with it.

Releases

GPT-6 Astra

$10 per million input tokens, $50 per million output tokens. Rolling out across ChatGPT Plus, Pro, Business, Enterprise and the OpenAI API.

What it's for Programming, cybersecurity, scientific research, computer control. It is the first model to cross the "critical" threshold of OpenAI's preparedness framework in cybersecurity, meaning it can attack as well as defend. A fast mode doubles the speed, and doubles the price.

The limit The rollout is not finished, not everyone has it yet. And it is a model you cannot host yourself: output runs at $50 per million tokens, where Google's Flash range sits at $3.75.

openai.com/​index/​gpt-6-astra

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Repos

msitarzewski/agency-agents · 150,281 stars · MIT · last commit 5 September 2026

A library of role cards for coding assistants. Each card is a text file describing a specialist (security, testing, SEO, finance) that you drop into your tool. The repo announces more than 230 agents. Our own count after cloning, on 6 September 2026, gives 273 cards. What it does not do: no code runs, these are written instructions only. The cost is whatever the model reading them charges. The project itself documents that some tools only register part of the cards and silently drop the rest.

github.com/​msitarzewski/​…

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In brief

TWO COMMITMENTS ANNOUNCED THIS WEEK, IN DOLLARS
NVIDIA buys Hugging Face
12.9 billion
OpenAI for cyberdefence
1 billion

NVIDIA acquires Hugging Face for $12.9 billion. The main repository for open models passes under the control of the leading GPU supplier. Jensen Huang pledges to keep the platform open: neutrality will depend on what comes next. blogs.nvidia.com/​blog/​…

OpenAI commits one billion dollars to cyberdefence for critical services. The Daybreak programme opens subsidised access to its cyber models and products for operators of critical infrastructure, local government and open-source maintainers, with training and support, starting with the United States. openai.com/​index/​…

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The problem of the week

Building a newsroom run by machines

You want a continuous information flow: collect sources, check what is true, summarise, turn it into video, and coordinate the whole thing. Five layers. Here is what exists at each one, what it costs, and where it breaks.

Layer 1: collect. ScrapeGraphAI (30,601 stars, MIT) reads a web page and hands back structured data. You give it an address and a sentence, it figures it out. But it does not read RSS feeds or X: for those two sources, you have to write or plug in your own collection. The hosted service costs from $20 a month, the library alone is free but the model calls are on you.

github.com/​ScrapeGraphAI/​…

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Worth reading

THREE READS, AND WHAT EACH ONE GIVES YOU
Latent Space on GPT-6 Astra20 billion tokens spent
Funes, by Hugging Facean agent memory you host
Project HydraFusion, by GitHubseveral models on one agent

GPT-6 Astra: an automated AI engineer for under $6 an hour · Latent Space spent over 20 billion tokens exploring Astra in depth. The article details the real gains per task, the cases where the model fails, and why it costs more per token but less per result. latent.space/​p/​astra

Give your coding agents a memory you own · Hugging Face introduces Funes, a persistent memory system for coding agents that you host and control. huggingface.co/​blog/​funes

Project HydraFusion: frontier quality through multi-model orchestration · GitHub shows how to have several models work on the same agent to reach big-model quality while cutting cost. github.blog/​ai-and-ml/​…

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The security reflex

LITELLM, THE FLAW AT A GLANCE
IdentifierCVE-2026-59822
Severity8.8 out of 10
Fixed in version1.84.0
CISA catalogueadded 2 September 2026
What the attacker reachesthe tools your agents expose

LiteLLM is a proxy that many teams place between their agents and their model providers, to route requests to the right place. An authentication flaw (CVE-2026-59822, severity 8.8 out of 10) lets a stranger present a token made up out of thin air: the check fails, and instead of refusing, the proxy lets the request through with an empty identity. The attacker then reaches the tools your agents expose, with no key at all. The flaw is actively exploited, CISA added it to its catalogue on 2 September. The technical detail, the severity and the fixing version come from the project's own security advisory: github.com/​BerriAI/​litellm/​…

The right move. Move LiteLLM to version 1.84.0 or later today, that is the version that fixes the flaw. If you cannot update immediately, cut inbound network access to the proxy and rotate every API key registered there.

cisa.gov/​news-events/​alerts/​2026/​…

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