Matthew Zeiler

AnySignal just dropped a Series A that feels less like a broadcast to anyone building in space, defense, or the increasingly loud intersection of both. A $24M raise led by Upfront Ventures is not casual capital. It is a signal that the market sees what John Malsbury, Jeffrey R Osborne, and Ricardo Medina have been assembling since 2022: a vertically integrated RF powerhouse that can pull mission-critical data out of the most unforgiving environments and make it look routine. When a team stacks SpaceX DSP leadership, Kepler strategy firepower, and #cloudinfrastructure mastery under one roof, you stop calling it a startup and start calling it a force multiplier. What catches my attention is how quickly AnySignal turned credibility into momentum. 4 missions already in orbit. 12+ booked for 2026 across #LEO, #GEO, and #lunar routes. A customer backlog thick enough to push their El Segundo production line past its limit, forcing them to scale from ~100 radios a year to a target of 1,000–2,000 once they move into a larger LA facility. That kind of demand is not a marketing win. It is a physics problem, and AnySignal is solving it with the kind of discipline usually reserved for legacy aerospace giants, except faster and with far fewer meetings. The Iris platform is where the story gets even more interesting. It blends #comms, #RFsensing, #radar, #navigation, and adaptive DSP into a single system that behaves less like a device and more like a mission partner. The AnyLink network layers on top, turning cross-network chaos into unified, intelligent #connectivity. In a sector full of promises about "interoperability," AnySignal is one of the rare teams actually delivering it. When your hardware and software can traverse #satellites, ground stations, and edge systems without throwing a tantrum, customers notice. What makes this raise feel inevitable is the way the founders' backgrounds slot together. John Malsbury brings years of DSP and FPGA leadership across Dragon, Starship, Starlink, and national security programs. Jeffrey Osborne adds the strategic instincts of someone who has already built a #spacecomms company from zero. Ricardo Medina ensures the cloud backbone does not buckle when missions scale. Add investors like BlueYard Capital, First In Ventures, LLC, Also Capital, Acequia Capital, Balerion Space Ventures, and Caffeinated Capital, and you get a syndicate that knows real dual-use infrastructure when they see it. If you are building #spacecraft, #nationalsecurity systems, #climatesensing missions, or autonomous platforms that cannot afford static when the stakes spike, this company is worth more than a follow. AnySignal is not getting louder by accident. It is getting louder because the market keeps leaning in. #Startups #StartupFunding #VentureCapital #SeriesA #Aerospace #Defense #DefenseTech #Space #SpaceTech #DeepTech #Data #DataDriven #Infrastructure #Cloud #CloudComputing #Technology #Innovation #TechEcosystem #StartupEcosystem

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Yann LeCun just raised $1.03B. Not for LLMs. For what comes after them. My first thought wasn't "wow." It was: how many founders are about to miss this? Most of us are sprinting to build on top of GPT or Claude architecture. LeCun just bet a billion dollars that architecture is wrong. World models don't predict text. They understand causality. Physics. How things actually work. Not just the next token. It has happened to me over and over again. Every time I got comfortable with the current stack, the stack moved. This is the stack moving again. The founders who win the next decade are already asking different questions. Not "how do I build faster on this?" "What comes after this?" $1.03B says the AI era isn't settled. It's barely started.

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Some recent, exciting news on compressed tokenizers and how individual tokens modify images in encoder-decoder models. I hope this opens up a new avenue of research with smaller models across frameworks (perhaps JEPA?). https://lnkd.in/evFw8WBu

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LLMs for Engineering Finds that when RL is used, a 7B parameter model outperforms both SoTA foundation models and human experts at high-powered rocketry design.

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Big news out of Ai2, the Allen Institute for AI: CEO Ali Farhadi is stepping down. Farhadi called it "a true privilege" to lead Ai2, citing the release of more than 300 models with 33 million downloads. Peter Clark will serve as interim CEO. Board chair Bill H. told me that Farhadi wants to pursue frontier-scale AI research beyond what a nonprofit can support with philanthropic funding. Hilf noted that all programs planned for 2026 are fully funded and that Farhadi wanted to ensure that stability before stepping down. Ai2 will continue its initiatives including its OLMo open-source model development and its applied AI efforts in areas such as climate, conservation, and health. Peter Clark will serve as interim CEO while the board searches for a replacement. Full story on GeekWire: https://lnkd.in/ghRMn4ag

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"LLMs aren’t the only kind of AI", "One of the biggest, most important one is physical AI. AIs that understand the laws of nature" Not me, but Jensen Huang at CES26. The switch from being able to calculate language and simulate talking about things to understanding how things do things will unlock vast value. Matrix multiplication and reinforcement learning is transforming how knowledge work is done. The next step will impact how work is done at all. For the builders who figure it out and the investors who get it, LLMs will be the warm-up act.

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Biological Chaos Entropy: What Deepfakes Can Never Imitate The newly introduced Chaos-D-ID SDK represents a fundamental departure from conventional liveness-detection technologies that rely primarily on visual facial pattern analysis. Built upon HSKG Labs’ core patented technology, Bio D-ID, this system leverages biological chaos entropy—a class of signals that are inherently unpredictable and non-deterministic. Through standard camera sensors, Chaos-D-ID continuously extracts microscopic blood-flow fluctuations (remote photoplethysmography, rPPG) and heart rate variability (HRV) in real time. These signals are not static biometric markers; they are dynamic, stochastic physiological phenomena governed by complex nonlinear biological systems. Crucially, such signals cannot be replicated by AI-generated deepfakes, synthetic avatars, or even high-fidelity 3D masks. No matter how visually convincing a synthetic face may appear, it lacks the irreducible physical entropy produced by a living human body. Chaos-D-ID therefore establishes a new verification paradigm—one that does not ask “Does this face look real?” but instead proves “Is this entity biologically alive, right now?”

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