🙋♂️
Stop using your laptop / Mac mini / VPS
Introducing instabox.sh, cloud computers for AI agents:
- 4 vCPU, 8 GB RAM spun up in <1s
- Built-in computer use
- Snapshots for easy cloning
- Persistent files, packages, config
- Public URLs for local ports
We're launching today through an invite-only beta program.
Early access includes 20 vCPU, 40GB RAM for free.
If you want to try, comment or DM me.
ΞΘX retweeted
We're going beyond text and are releasing a new version of GPT-6 to all users in ChatGPT. Lots of model and infra improvements coming together here to scale it to 1.2B users!
ΞΘX retweeted
Codex 🤝 Tailscale
Codex Cloud can now securely connect to resources on your tailnet with Tailscale.
Useful tools should be easy to build with, combine, and turn into something even more useful.
See how it works →
buff.ly/yFcldrC
health is wealth🤨
Doing a bit of a self-experiment.
Goal: use my personal health and travel data to provide personalized diet and exercise recommendations for me, using frontier models but in a way that avoids leaking to them any private information.
Strategy: use a local model (Qwen 3.8 Flash Next) to orchestrate, and use powerful remote models as a tool call to benefit from higher-level thinking and knowledge that the local model does not have.
Three-layer approach to privacy:
Avoid leaking personally identifiable information, or leaking my identity through writing style -> local model writes the queries to the frontier model, not me
Avoid leaking who I am through the payment channel -> zkAPI
Avoid leaking who I am through networking / IP -> Tor
You need all three (and finally we have all three, at least to some extent)
A skill file teaches the local model when and how to construct minimally-data-revealing requests to remote models. Use zkAPI-wrapped-with-Tor as a CLI tool.
And everything works! I got the recommendations back, info from frontier models helped to improve them.
Main deficiencies:
* Tor is really not optimized for request-by-request de-linking, which is the only form of network-layer privacy that really makes sense in today's world (long-running identifiers are too fragile). Probably not private enough, and latency 10-100x higher than it could be, at the same time.
* The skill file's request construction strategies are definitely far from optimal.
* Qwen 3.8 Flash Next is still too slow for comfort. It's comfortably running at 20-30 TPS, but it would only really start to feel fast at 100+
* There is a tradeoff: the more careful you are about what data you give to a remote model, the less it can help you
github.com/ethereum/zkapi/pu…
hermes➕openai ChatGPT sub
We've partnered with @OpenAI to bring the new Sign in with ChatGPT experience to Nous Portal.
Log into Nous Portal with ChatGPT to use your plan in Hermes Agent, with full visibility and controls in ChatGPT settings.
ΞΘX retweeted
终端听劝式更新,多会话、TUI等等全都有
UU远程终端功能更新,广泛听取大家的建议。现已支持多会话、会话继承、TUI、语音输入、Mac自动解锁等多项新功能。欢迎大家在体验后给我们提出改进建议~
ΞΘX retweeted
A note on recursive STARK mempools (EIP-8288) eips.ethereum.org/EIPS/eip-8…
This is an EIP that I am hoping we can get included in I-star (the fork after Hegota) that you can think of as the next step after Frames, that would unlock extreme amounts of power. Particularly:
* Ultra-cheap quantum-safe signatures (SPHINCS-). Much of the cost savings comes from the fact that the signature data (~3 kB) does not have to go onchain
* Ultra-cheap quantum-safe privacy protocols. Status quo minimum cost for private txs is ~300k if you engineer very well (no one does), status quo quantum-safe is ~10M gas, this could reduce it to low tens of thousands.
* Universal support for your favorite new signature or proof scheme without needing EVM changes. Whatever you use (Falcon, ML-DSA, some other lattice-based thing, something code-based or isogeny-based or even more esoteric), you can just wrap it client-side in a STARK, onchain gas cost low tens of thousands just like privacy protocols. Hopefully, Ethereum will never need "please support my favorite cryptographic algo" politics again.
* Private account abstraction: keep your account logic private, and in a private location onchain. Then you can make one transaction to change the ownership of all your onchain state - accounts, defi positions, privacy protocol notes, everything - without revealing which objects' ownership you're changing.
Here's how it works.
Your transaction can include a type of frame that we call a "dependency frame". The frame is a list of statements, asserting claims like "message hash M was signed by SPHINCS- public key P" and "data hash D was proven to satisfy a statement defined by verification key V".
When you send your transaction, you send it in an envelope, which includes a signature or a STARK for each statement in a dependency frame.
Once the transaction reaches the mempool, nodes aggregate them. Each node runs a loop: wait one tick (eg. 500ms), aggregate all new envelopes (either single-tx or multi-tx) that you've seen, remove any transactions that are expired, generate a STARK recursively proving all dependencies, and send a new multi-tx envelope containing that STARK.
Hence, the bandwidth load is bounded: each node's outbound is one STARK (~100-300 kB) per tick, plus each transaction getting broadcasted through the network once (as happens already).
The block builder acts as "yet another mempool node", receiving envelopes from the mempool (plus any side channels), generates its own STARK covering the subset of transactions it intends to include in the block, and adds that STARK to the block.
Total onchain overhead: one STARK (100-300 kB), plus 96 bytes for each statement being proven.
This is what I've called before ( youtube.com/watch?v=TSLUpOps… ) "The Proof Singularity". Today, we have all the ingredients to actually implement it.
As a developer, this requires a somewhat different workflow than you are used to, but it is conceptually simple. Any signatures or STARKs, you put into a separate frame. Then the main logic that today is verifying a signature or STARK, you replace with checking for the existence of a frame that includes the correct statement as a dependency.
Examples of useful statements:
* [tx sighash] verifies against [the pubkey at sload(0)]
* there exists a secret and a merkle branch such that hashing secret+0 and applying the merkle branch outputs (public) root R, and hashing secret+1 outputs (public) nullifier N
* there exists a secret address A, salt S and signature Z such that sload(0) = hash(A, S) and a merkle proof of address A inside a recent ethereum state contains some pubkey D where [tx sighash] was signed by D [this is private account abstraction; all variables except [tx sighash] and sload(0) are private; you can also make D a STARK verification key]
* there exists an ML-DSA signature signing [tx sighash], that verifies against an ML-DSA pubkey whose hash is sload(0)
At the core, this is moving any compute and data other than bookkeeping "business logic" outside the core path of Ethereum execution, sharding and parallelizing it via the mempool.
Notice also that this requires agreeing on a _language_ (aka. an ISA) for the recursive STARKs to define statements in. The current leading candidate is RISC-V. So this would also de-facto be Ethereum adding RISC-V (or something else we decide on) as a canonical ISA - a big decision that should be done carefully, but that I think will be necessary to drive Ethereum forward.
We’re working with an independent advisory group of mathematicians to help OpenAI responsibly share advances in AI and mathematics.
The group will advise on how we assess and communicate new mathematical results, uphold academic and professional standards, and build tools that support mathematical research and learning.
Through this work, we want mathematicians to be at the center of shaping how AI supports mathematical understanding and how its benefits reach the wider community.
openai.com/index/advisory-gr…
DAO
Since many people are learning about effective altruism, it's worth learning about Mozi, the ancient Chinese philosopher who was surprisingly close to being a proto-effective-altruist (particularly the global-health-focused variety, not the AI-risk-focused variety).
He valued the twin goals of (i) universal love, loving everyone and not just yourself and people similar or close to you, and (ii) being efficient about how you use your limited resources to most effectively help people.
ctext.org/mozi
ΞΘX retweeted
Hermes Agent is open for business.
Nous Portal now lets you invite colleagues to a Hermes Business account: your team gets agents across channels while sharing one central balance with per-member caps and shared skills that compound into proprietary IP.
Hermes Enterprise brings the same capabilities to on-prem or the cloud of your choice: a complete, self-improving, sovereign AI stack already trusted by some of the world's largest companies. Contact us to join them.
portal.nousresearch.com/busi…
👏👏
Tailscale without Tailscale, by Tailscale. Meet tailcat.
tailcat is an open-source Go package and CLI that lets you use Tailscale’s data plane without the control plane. No accounts, logins, admins, or IPs to manage.
Learn more → buff.ly/MBqj8sF
ΞΘX retweeted
Heads-up for anyone maintaining L1 contracts:
→ The Glamsterdam upgrade will include gas repricings (EIP-8037, EIP-8038) that shift state creation and access costs.
→ Most contracts are unaffected, but a small set may break or degrade without updates. Affected contracts rely on assumptions the new schedule changes, such as hardcoded gas values.
Full context in the overview: blog.ethereum.org/2026/08/24…

























