Bmur

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Bmur

Bmur

@murr

San Francisco, CA Katılım Eylül 2010
577 Takip Edilen3.1K Takipçiler
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Yadin Soffer
Yadin Soffer@yadinsoffer·
No better place to emerge from stealth than @reindsummit! This wasn’t just an announcement of our $25M seed round by @SilentVentures @craft_ventures @Lux_Capital It was an opportunity to call government, tech, and academia to build for the Subterra Domain
Traysar Industries@traysartech

“…when we tell Iran no nuclear bombs, they build them underground. When we say no drugs in the US, the cartels smuggle them in right beneath our feet…” Yesterday at Reindustralize we announced Traysar, the Subterra Domain, and a path to re establish US deterrence and win wars

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Silent Ventures
Silent Ventures@SilentVentures·
Traysar has raised $25M in seed funding. We couldn't be happier to lead the round and partner with @yadinsoffer. What @traysartech is building is new, novel, and necessary. We know less about what's underground than sea and space, despite having operational military history spanning WWI (trench warfare), WWII (Pacific island hopping), Korea, Vietnam, Iraq/Afghanistan, and Ukraine. DoW has explicitly signaled its intent to correct this asymmetry as America's enemies continue to effectively threaten Western interests from caves and tunnels. Kudos to the exceptional team at Traysar for tackling this problem as the first and only subterranean defense tech company in existence.
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Traysar Industries
Traysar Industries@traysartech·
Using the crust of the earth as a three dimensional maneuvering space for people, signals and effects. This is Subterra: the defining warfighting domain of the 21st century. Join us to build the technologies that determine how wars are won.
Yadin Soffer@yadinsoffer

Who needs an underground missile? - NAVFAC for deploying expeditionary bases and comms - Special ops to blow up enemy runways - Ukraine for trench warfare strike and short-range resupply - Army Engineers for buried infrastructure denial To name a few… Volume ON: * bonus points for those who can guess why Asher is hammering the ground

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Yadin Soffer
Yadin Soffer@yadinsoffer·
Palmer Luckey last week at Westpoint: “I’m trying to get people to believe that the next warfighting domain is the crust of the earth” Ironic how the most ancient warfighting domain is the one hardest to get people to notice. defenceconnect.com.au/land/18342-ben…
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TBPN
TBPN@tbpn·
Even though The Bullfrog, @allencontrol's AI-powered machine gun, is designed to shoot down Group 1 and 2 drones, which are by far the most difficult to destroy, it can still damage Group 3 Iranian Shahed drones. "We are currently focused on being the best at shooting down Group 1 and Group 2 drones, which are absolutely the hardest drones to engage... That said, we can shoot down Group 1 drones that are very far away." - CEO @mikewior "So if I can hit a 7-inch target on a Group 1 drone from very far away, I can hit very vulnerable parts of a [Group 3] Shahed at the same distance." "Lasers are pretty good at shooting down Group 3 drones, but you have to keep your laser on target for 5 to 15 seconds in order to damage the airframe." "So while we're not the ideal solution for engaging those larger targets, when they get closer and you need that last line of defense, we are absolutely a great solution for taking those out of the air."
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Paul Itoi
Paul Itoi@paulitoi·
you can tell when someone has lived with the problem first hand: @prabhavjain makes this article worth it: "This is why we do not believe in a pure agent that reasons from scratch every time, and we do not believe in a rigid workflow that breaks the moment reality gets messy. And instead been building agentic workflows. The workflow gives you repeatability, auditability, and cost control. The agent handles variability and recovers when the happy path breaks. The human stays in the loop for the judgment calls where accountability matters." the line between agent | workflow | human is the taste required right now to see ROI. I ran a dozen AI implementation pilots before realizing we were roadkill without these 3 pieces: - graph representation of all of your context (calls, chat, code, dream cycle output) - self-generating workflows (FDE's will be cannon fodder without this) - spec driven code generation test coverage We built all 3 of these and linked them together, we'll clean up the code and release the repos as open source as we can. even with these tools, only select PE owners or orgs in full 'dorsey/founder mode' can make these changes.
Joe Schmidt IV@joeschmidtiv

x.com/i/article/2059…

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Evan McCann
Evan McCann@evansammccann·
For years, @avarma has been one of the most important people in Toronto tech without many outside the ecosystem fully understanding why. He helped build Xtreme Labs. Autonomic sold to Ford. Xtreme’s story even brushes up against Tinder. He has been described as “sort of the king of Toronto.” Others put it more bluntly: “What people don’t realize is that he was carrying Toronto and KW tech on his back.” Now, with Mantle, he is building again. My profile:
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Steven Simoni
Steven Simoni@StevenSimoni·
I couldn’t be more proud of our team at @allencontrol systems and I’m so glad @SenTedCruz was able to come see the vital work being done for America in the great State of TEXAS
Senator Ted Cruz@SenTedCruz

Great to meet with the men and women of Allen Control Systems yesterday in Austin, Texas. ACS is a leader in the field of autonomous precision robotics, and their innovative technology helps ensure the U.S. military remains the most lethal force on the face of the planet.

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Lightning Labs⚡️🌐
Lightning Labs⚡️🌐@lightning·
We're hiring a Head of Developer Product Marketing! Shape the messaging to the dev community about why bitcoin matters for humans and agents. Develop strategies that move as quickly as AI. Ship and iterate to inspire builders to build. Be the bridge that connects Lightning to the broader universe. 🌉 Apply here: jobs.ashbyhq.com/lightning/91a6…
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Lightning Labs⚡️🌐
Lightning Labs⚡️🌐@lightning·
Bitcoin is an agent's best friend. With L402 SDK, agents can discover an API, pay 1 sat on Lightning, and get access. All from a single prompt. Devs, vibe coders, and agents are building the AI economy with Lightning. You can too. ⚡
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Lightning Labs⚡️🌐
Lightning Labs⚡️🌐@lightning·
Agents want money. Bitcoin makes it possible. And now it works with agent-native workflows. Today we're releasing L402 SDK as part of our suite of AI tools, a client SDK for agentic payments on Lightning with L402. Embeds directly into library-based agent frameworks. TypeScript and Python bindings. Works with Vercel AI SDK and LangChain. 📖 Import a library instead of using a CLI 🛡️ Per-request, hourly, daily, and per-domain budget controls 🌐 WASM for browsers, serverless functions, edge environments Start building the agent economy with machine-scale payments on Lightning. github.com/lightninglabs/…
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Lightning Labs⚡️🌐
Lightning Labs⚡️🌐@lightning·
Aperture is a payment gateway for your app. Per-request access with no signup required. The perfect model for agents that need to discover and pay for services on the fly. Powered by Lightning. ⚡ Aperture now includes a built-in MCP server so vibe coders can spin up paid services managed by agents and supports the Machine Payments Protocol (MPP by @tempo @stripe) alongside L402 agentic payments. The AI + bitcoin convergence is happening. Start building. github.com/lightninglabs/…
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TFTC
TFTC@TFTC21·
Google just dropped a compression algorithm that makes AI 8x faster while using 6x less memory. Zero accuracy loss. It's called TurboQuant. Here's why it matters in plain English: Every time you talk to ChatGPT or any AI, the model has to remember everything you've said in the conversation. That memory is called the "key-value cache." The longer the conversation, the bigger the cache, the more expensive it gets to run. This is the single biggest bottleneck in AI right now. A 128,000-word conversation on a large model eats 40GB of GPU memory just for that one user. Scale that to thousands of users and you're burning millions in compute costs reprocessing the same data over and over. TurboQuant compresses that memory down to just 3 bits per value (from 32 bits) without losing any quality. Independent developers tested it within hours and got exact matches against full-precision output. What this actually means: - AI models that needed a $10,000 workstation could now run on a MacBook - Always-on AI agents become dramatically cheaper to operate - Open-source models that were too big for consumer hardware suddenly fit - The cost curve for every company running AI infrastructure just shifted Developers are already porting it to Apple Silicon. No retraining required. It drops into existing AI systems without modification. The AI cost problem isn't being solved by building bigger data centers. It's being solved by mathematicians figuring out how to do more with less.
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Olaoluwa Osuntokun
Olaoluwa Osuntokun@roasbeef·
looks like the Tempo devs have finally internalized what Bitcoin devs have known for sometime: payment channels like Lightning are the ideal construct for real time machine-to-machine payments ⚡️ channels update off-chain so minimal latency streaming payments come naturally
Liam Horne@liamihorne

I’ve spent most of my career scaling payments. From 2017-2021, we poured years into building state channels on Ethereum The tech worked, but nobody used it. People used blockchains for trading tokens, not for making payments, and that's why L2s had to come first Agents are the users we were waiting for, and that's why we're stewarding the launch of the Machine Payments Protocol (MPP) with channels baked in

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Keşfet

@reindsummit @SilentVentures @craft_ventures @Lux_Capital @yadinsoffer @traysartech @allencontrol @mikewior