You can’t be part of the *permanent* underclass if AI leads to human extinction. pic.twitter.com/k2MGp28shn
— Bojan Tunguz (@tunguz) 1 juin 2026
You can’t be part of the *permanent* underclass if AI leads to human extinction.
AI
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AI extinction makes permanent underclass irrelevant
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The Trend Towards Small and Specialized AI Models
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All roads lead to small and specialized models btw
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Summoning AI help via sag.sh when distracted
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I told codex to use http://
sag.sh whenever I'm distracted and it needs my help to be unblocked, and ever once it a while I hear it talking to me, and it's the coolest thing ever. (e.g. for releases, that needs npm and is 1Password-gated) -
Codex() starts local app-server, no new Node process per input
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no, it does not spawn a new Node process per input. Codex() starts a local Codex app-server process and the SDK talks to it over stdio/JSON-RPC for threads and turns.
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Resume restores persisted conversation history but not live processes
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Resume restores the persisted thread: conversation/run history plus thread settings/config that are saved with it. It does not resurrect live tool/process state. So if Codex changed files, those filesystem changes are still there. But open shell processes, transient handles,
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Become a pro user and explore Hugging Face’s new blog for exciting updates!
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You have to be a pro user and then https://
huggingface.co/blog/new! -
Codex now supports Amazon Bedrock with GPT-5.4 and GPT-5.5
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PSA: Codex now works with Amazon Bedrock! To configure, set: model_provider = "amazon-bedrock" and Codex can run local CLI, desktop, and IDE workflows against OpenAI models on Bedrock, using AWS-native auth/IAM. Both GPT-5.4 and GPT-5.5 are supported. Big unlock for teams
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Codex Python SDK Released for Embedding in Python Apps
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We just released the Codex Python SDK You can now embed Codex directly into your Python apps and workflows! > Start threads
> Run turns > Stream progress > Resume sessions
> Pass images > Control sandbox access All whilst reusing your existing Codex auth. pip install -
Optimizing Unified Memory with Speculative Decoding on Apple Hardware
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You’re optimizing the right things for Unified Memory There are some shortcomings to Speculative Decoding (especially in more creative / less coding workflows) but the pros far outweigh the cons giving the Unified Memory limitations Gonna try this on my Apple hardware tonight
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Abacus AI Supercomputer: Build Cloud Services & Host LLMs with a Single Prompt
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🚨 INTRODUCING THE ABACUS AI SUPERCOMPUTER
— Abacus.AI (@abacusai) 1 juin 2026
– literally build ANY cloud service with a prompt
– host open-source LLMs & always-on agents
– bring your own Codex, Claude or Anti-gravity
– multi-agent architectures with Opus 4.8 and GPT 5.5
– run 3D games or any other server at… pic.twitter.com/Rs8lA4G0vaINTRODUCING THE ABACUS AI SUPERCOMPUTER – Literally build ANY cloud service with a prompt
– Host open-source LLMs & always-on agents
– Bring your own Codex, Claude or Anti-gravity
– Multi-agent architectures with Opus 4.8 and GPT 5.5
– Run 3D games or any other server at