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4/ Keeping AI conversations aligned: using a project map to carry context between sessions, so each new chat starts from the same project state.
x.com/NixFred/status…
People ask me how I ship omarchy sw so fast. 🧵
The answer is Clarity.
Clarity is where all my projects live, from the first idea to running live. Every project gets a map, a status, its questions and decisions, a backlog, testing and its GitHub, in one place. Every AI chat
3/ On a proposed ten-year pause in frontier AI training: the case for inference-only chips, the threat model behind the proposal, and the assumptions it depends on.
x.com/wfithian/statu…
Excited to share a new working paper, joint with 25 interdisciplinary coauthors:
“The Feasibility of a Hardwired Pause of Frontier AI Training"
63% of voters in a recent WSJ poll want to pause AI development.
But can it be done globally? How long could it last? 🧵
2/ Agents that update live apps: how a cloud engine could let AI modify deployed software, and where open-source enterprise applications fit into the product roadmap.
x.com/dominic_w/stat…
ICP "cloud engines" launch trajectory:
DFINITY will soon begin disbursing coupons with enough cycles to create and power an engine for 1 month+, unlocking in sequence:
1. Agentic infrastructure ⚡️ Quickly build secure, sovereign onchain production apps using Claude Code, Codex,
1/ Faster GPU scheduling: how the team cut queue times from five minutes to 24 seconds, and the engineering decisions behind the improvement.
x.com/allen_ai/statu…
We’re sharing the engineering work behind Ai2’s GPU scheduler—our new approach to allocating compute across research teams.
On our largest H100 cluster, median queue wait fell from 5 minutes to 24 seconds. 🧵
allenai.org/blog/impactful…
6 good reads on X today, picked for people who’d rather listen than scroll.
GPU scheduling. AI agents. Medical AI. AI policy. Better workflows.
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4/ Michael Mignano on USV's next chapter: where the firm sees opportunity in AI, from reshaping markets to unlocking data in the physical world.
x.com/mignano/status…
3/ Rari on choosing AI models: count the cost of a task done right, including retries, tools and rework, then decide where the flagship earns its keep.
x.com/0xwhrrari/stat…
GPT-6 Astra is built for the hard tasks
Using it for everything gets expensive fast
I broke down when Astra earns its price and when Sol is enough ↓ x.com/i/article/2107…
2/ Steve Hsu on the AI investment boom: why rapid progress in capabilities can coexist with disappointing returns, and why infrastructure and model labs are different bets.
x.com/hsu_steve/stat…
Summary:
Core thesis: Two things are true at once. AI capabilities are surging and will matter enormously in the long run, but current CapEx and lab valuations are ahead of near-term revenue.
Capabilities aren’t the issue: Models are already superhuman in some ways, with major
1/ Jeff Holden on programmable manufacturing: how Atomic Machines aims to build working micro-machines from code, and why its first application is power protection in data centers.
x.com/jeffholden/sta…
After six years in stealth, Atomic Machines is out. Our mission: on-demand, universal command of matter. First beachhead: the Matter Compiler, an AI-native manufacturing system that builds working micro-machines from code alone. No per-product tooling. No process development.
4 good reads on X today, picked for people who'd rather listen than scroll.
Micro-machines. AI investment risk. Model costs. USV's next chapter.
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4 long reads on X from today, picked for people who'd rather listen than scroll.
Two takes on OpenAI's math. An AI research machine. AI for growth experiments.
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