Open Money, Open Intelligence
SF
Joined August 2007
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- Following1.6K
- Followers26.1K
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Steve Lee retweeted
excited for this one. we put a @cashapp tag in a bandana
first one we've built into fabric and first one we've made with a partner, LA luxury streetwear brand NAHMIAS
tie it, wear it, style it however you want. it still pays with a tap
available to order nov 17
Steve Lee retweeted
Yes, there is Mesh LLM
github.com/Mesh-LLM/mesh-llm
Steve Lee retweeted
I agree dependencies are a big target and create massive distribution of vulnerabilities so there is good reason to do this.
Something I haven’t figured out yet and interested for your thoughts on is how we avoid the forking tax.
Teams working on libraries evolve them, introduce new features, address issues, and make performance improvements.
If we vendor a generated version of every dep, the project owning team (and their agents) become responsible for all this ongoing work and it costs attention and tokens for upkeep.
Steve Lee retweeted
There is often a knee-jerk reaction against data centers in space, but the more you dig into it the more the numbers look like they work if a number of difficult, but not impossible, engineering challenges are solved.
Many people list cooling as a major blocker to space data centers, but this is already solved by using large radiators.
Additionally, there are technologies like the liquid droplet radiator that could reduce radiator mass by up to 7x (see diagram for design variants). The general idea is that you simply yeet the coolant into space and catch it again once it has cooled off, using the surface of the liquid itself to radiate heat instead of a heavy network of pipes and metal. A droplet of coolant with a diameter of 1 μm can theoretically go from 227 C to -21 C in two seconds given the proper conditions.
A major open challenge with liquid droplet radiators is preventing coolant loss.
Not sure if @elonmusk 's team is working on this, but would be curious to know if anyone else is.
Steve Lee retweeted
join me and us at @blocks builderlab event in SF next tuesday nov 10th! builderlabstudio.rsvpify.com
Steve Lee retweeted
SV2 Apps add Bitcoin Core v32 support and block submission over IPC, and continue addressing @ProjectLoupe findings across Pool, JDS, JDC and Translator Proxy.
Protocol library highlights include hardening of buffer_sv2, codec_sv2 and framing_sv2, message field renames to match the spec, and support for application-supplied jobs in channels_sv2. All changed published crates introduce breaking changes except noise_sv2, so downstream consumers should review the release notes when upgrading.
SV2 UI adds experimental Telegram notifications, multiple custom pools, clearer fallback pool status, and improvements to onboarding, logs and recovery. Setup now supports Bitcoin Core v32.
Findings from @ProjectLoupe continue to guide security improvements across the stack. Thank you to the Loupe team and everyone helping turn those findings into fixes!
This milestone introduces our SV2 interoperability project, a new effort to test protocol compatibility across different SV2 implementations. The goal is to catch interoperability issues early, make it easier for implementers to validate their software against the spec, and help ensure different SV2 implementations work reliably together. Contributions and feedback are welcome!
Steve Lee retweeted
Bitcoin payments don’t have a technology problem. They have a reason-to-use-them problem. Last week, we asked the community how to change that. Find our summary here: spiralxyz.substack.com/p/val…
Steve Lee retweeted
I'm building a new programming language, Zed (once it's released I'll be posting about it at @ZedLang).
I have been working on this language for over 20 years, but never got it built, because the scope of it is so ambitious. It's an entirely new type of language based on category theory, with core design objectives of precise automatic parallelization up to the Amdahl limit; automatic memory management, with no GC and no need for manual malloc/free; and pervasive use of partial evaluation to increase the power of the language, among other very unique features, such as units (`accel = 5 with units("m s^-2")`) as part of the type system.
I gave Opus 200 pages of design notes that I have been compiling over the last 20 years, and the code I had already written, and asked Opus to compile everything I have created so far into a single cohesive and detailed plan. Then I went through many rounds of cross-review between Claude, ChatGPT and Gemini, having them all do critical reviews, then meta-critique each other's critiques, then collaborate on combining their critiques into an improvement plan, until convergence. I also had the agents cross-check every part of the spec with every other part of the spec (all-pairs comparison) to check for inconsistencies, gaps in the spec, etc. Then I had the agents turn the spec into a long series of tiny incremental steps (a topological ordering of what has to be built before what), as well as the DAG-structuring of dependencies underlying the topological ordering.
I then had Opus build a visualizer that shows me all the tasks in the DAG as my coding agents are working on each task, with realtime update as tasks change status (in progress / completed), which I highly recommend when you ask Opus to do some mammoth complex task, because you can see exactly what it's doing and when.
It is absolutely magic to see this coming together before my eyes, and to see how Opus is handling this massive DAG of complex tasks and their interdependencies.
It is crazy to me that Opus is now simply building what I have dreamed of and wished would exist for over 20 years, but never had enough waking hours to implement! I now have an army working for me, completing what I couldn't due to the bandwidth limitations of having just one brain, and 24 hours in a day.
What a day of miracles we live in.
Steve Lee retweeted
🚨 We are receiving reports of hot wallets on BTCPay Servers being swept by unauthorized attackers.
If you're running an instance, please shut it down (./btcpay-down.sh) until we complete the investigation.
Steve Lee retweeted
Integrate and control maps right into your Buzz conversations using plugins.
For sales teams, competitive analysis, market research or just to explore the world we live in.
Another example of the power and flexibility of buzz plugins.
@buzzdotxyz + @Mapbox + @SerpApi
Steve Lee retweeted
Anthropic rewrote its Messages API in Rust. Zero Rust devs on the team.
Claude wrote the code. Humans wrote the plan and checked old vs new matched on real traffic. CPU dropped 40-50%.
Pretty sure "never do the big rewrite" is dead advice.
@katelyn_lesse on @latentspacepod
Steve Lee retweeted
Integrating Lightning payments into @signalapp has been our dream since day one, and it's amazing to see a demo of this in action!
Props to @matbalez @Mesh_LLM @moneyball for the cool demo!
An agent inside Signal using decentralized compute paid for with bitcoin
@moneyball demos a fork of Signal built by @matbalez using @Mesh_LLM and @lexeapp ↓
Timestamps:
0:00 - Demo: agent inside Signal
10:51 - The economics of decentralized compute
14:39 - Running inference at home
Steve Lee retweeted
If you're interested in moonshot ideas the community has imagined for bitcoin payments, we've collected the most interesting ones in our GitHub discussion: github.com/spiralxyz/bitcoin…. It's an ongoing conversation and new ideas are still coming in, so jump in, react to your favourites, and add your own.
.@jack thinks bitcoin payment adoption isn’t where it should be. We want your ideas on how @Blocks, Spiral, and you can increase adoption within 5 years. Our trajectory needs changing. Here’s more on our thinking. Now we want yours: github.com/spiralxyz/bitcoin… View article
Steve Lee retweeted
Builder Miami Recap from tonight.
@conorokus and I co-hosted a round table discussion with a room full of AI and bitcoin builders talking personal agents, open models and bitcoin payments, and the questions that matter, who your agent works for, what owning your AI means, and where bitcoin earns its place.
Until next time!
Special thanks to @coinward and @BitcoinGrove for the space!
buildermiami.ai
🤖 Made with AI
Steve Lee retweeted
PBJ: Binance hack unpacked, AI consolidation & pullback, Advancing bitcoin payments @dksf @moneyball @maxawebster nitter.gq/i/broadcasts/1AxRnZQYr…
Steve Lee retweeted
but what if the utilization of local compute was actually made much, much higher because we all shared a public network for distributed inference
no need to ask what if
meshllm.cloud/
sam: local inference is a terrible allocation of scarce resources
“a lot of people want local inference, and somehow they assume that the problem is solved now because we have open-source models, we're going to be able to run them on our computers, and so we're not going to need all the stuff in the data centre
but from a global allocation perspective, actually it's quite terrible to have everybody, like, have a bunch of the world's limited supply of DRAM sitting in their own computer and being used five percent of the time
you want maximum utilisation in the cloud if you're trying to deal with this very supply-constrained environment
somehow many people's intuition is the opposite of that”
Steve Lee retweeted
The @blksresearch team found a way to sign post-quantum transactions on a hardware wallet in about 3 seconds, down from over 20, with the hardware already in your hands.
blog.blockstream.com/hardwar…
