#AI #Hardware #EdgeAI #Neuromorphic #BioHacking #Physics #Ultrasound #Ferrite #Neuroscience #SignalProcessing #DeepTech #TechInnovation #AnalogComputing #WaveDynamics #FutureOfAI #Cybernetics #EmbeddedSystems #AIHardware #Innovation #TSUNAMI

Emerging evidence shows higher cognition relies on rhythmic electric fields—acting like "radio waves"—to enable large-scale organization, executive control, and energy-efficient analog computing. Catch Professor Earl K Miller’s Presidential Special Lecture at Neuroscience 2025 neuronline.sfn.org/scientifi… @MillerLabMIT #Neuroscience #Bioelectricity #CognitiveScience #AnalogComputing #SfN25

Berkeley Lab Explores Thermodynamic Computing for AI ow.ly/FgTv50YmBna #ThermodynamicComputing #AIInfrastructure #EnergyEfficientAI #NextGenProcessors #AnalogComputing #AIResearch #HPC

Headline: Why the Brain isn't a Computer—It’s a Wave Interference Engine 🌊🧠 ​Most people think the brain "calculates" anomalies like a digital processor. They’re wrong. Digital is too slow. ​If you look at a 20x20 matrix and spot the "odd" numbers instantly, you aren't running an algorithm. You are performing Analog Subtraction. ​The Theory: The brain doesn't process data; it manages Waves. 1️⃣ The Prediction: Your internal model generates a "Counter-Wave" (Anti-Phase) based on expected patterns. 2️⃣ The Reality: Sensory input hits as an incoming wave. 3️⃣ The Interaction: When they meet, Destructive Interference occurs. ​The Result: The predictable world—the "normal" numbers—simply cancels out into silence. No CPU cycles needed. No "processing" required. ​The "Oddness" (the anomaly) is the only thing that doesn't cancel. It survives the interference as a high-energy spike. Consciousness isn't the whole picture; it’s the "Residue" of the subtraction. ​We don't "think" the difference. We feel the interference where the world fails to match our internal wave. ​Mathematics calls this a Fourier Transform. Nature calls it Perception. Memory must be wave-like: sensory inputs are converted into waves whose resonance generates meaning from reality. ​#Neuroscience #Physics #WaveMechanics #InformationTheory #AnalogComputing #PatternRecognition

Peking University just unveiled an analog chip that's a *thousand* times faster for AI than today's best! 🤯 It doesn't use binary code but squishy, continuous physics, potentially bypassing computing's oldest problem. Talk about a glow-up for AI! #QuirkScience #AI #AnalogComputing

Jak szybko USA tracą dominację technologiczną? Nie jest to przesada – Pekiński Uniwersytet (#China) właśnie opublikował analogowy chip, który może być 1000x szybszy niż chipy Nvidia w rozwiązywaniu problemów #AI. To nie hype – to realny przełom technologiczny, który w perspektywie lat może zmienić globalną mapę technologii. 🔬 Kluczowe innowacje chipu analogowego: Resistive memory arrays (RRAM) – dane przechowywane i przetwarzane w tym samym miejscu, czyli in-memory computing. Precyzyjna kalibracja stanów oporu, osiągająca cyfrową dokładność, wcześniej uznawaną za niemożliwą dla analogowych systemów. Energia: zaledwie 1% zużycia tradycyjnego GPU. Publikacja ukazała się w prestiżowym Nature Electronics, ale świat dopiero zaczyna o tym mówić. 📊 Dlaczego to ważne z perspektywy analityki i inwestycji? Szybkość AI i koszty energii – analogowe chipy mogą zrewolucjonizować rynek serwerów AI, superkomputerów i centrów danych. Konkurencja USA vs Chiny – dominacja amerykańska w półprzewodnikach i AI może topnieć szybciej niż oczekiwano. Post-Moore computing – rozwój technologiczny oparty na inteligentnych architekturach i niskim zużyciu energii, a nie tylko mniejszych tranzystorach. Rynki kapitałowe – potencjalny wpływ na wyceny firm AI i producentów GPU, jeśli RRAM zyska skalę. 🔎 OSINT i sourcing danych – klucz do przewagi strategicznej Śledzenie takich przełomów nie jest możliwe wyłącznie poprzez media głównego nurtu. Tu wkracza OSINT (Open-Source Intelligence) i sourcing danych: Publikacje naukowe – Nature Electronics, IEEE, arXiv i chińskie czasopisma techniczne pozwalają wykrywać przełomy zanim trafią na globalne newsy. Patenty i zgłoszenia R&D – monitoring chińskich i międzynarodowych baz patentowych daje sygnały o kierunku inwestycji technologicznych. Konferencje branżowe i repozytoria uczelniane – prezentacje i wczesne raporty z laboratoriów pokazują tempo komercjalizacji nowych rozwiązań. Analiza sourcingowa kadry i grantów – śledzenie publikacji konkretnych zespołów badawczych pozwala identyfikować potencjalnych liderów technologii. 💡 Dlaczego to ma strategiczne znaczenie: Firmy i inwestorzy mogą wcześnie identyfikować przełomy, zanim wpłyną one na rynek. Pozwala prognozować ryzyko konkurencyjne i geopolityczne, np. przesunięcie przewagi technologicznej w AI z USA do Chin. Umożliwia analizę wpływu nowych technologii na koszty operacyjne, skalowalność i energochłonność infrastruktury obliczeniowej. 🔮 Wnioski Analogowe chipy RRAM to potencjalny game-changer w AI i HPC. OSINT i sourcing danych pozwalają zrozumieć dynamikę rynku i przewidywać trendy, zanim zostaną nagłośnione w mediach. Dla analityków, inwestorów i firm technologicznych: monitorowanie takich źródeł to kluczowa przewaga konkurencyjna w świecie szybkich zmian technologicznych. Pełny artykuł: Precise and scalable analogue matrix equation solving using resistive random-access memory chips, Pushen Zuo i współautorzy, Nature Electronics. nature.com/articles/s41928-0… #TechRevolution #AnalogComputing #AI #ChinaTech #InMemoryComputing #PostMoore #OSINT #Sourcing #HPC #InvestmentAnalysis

#Highlights of JCST in Vol.40, No.4 #CoverArticle: RF Computing: A New Realm of IoT Research jcst.ict.ac.cn/article/doi/1… #Perspective: RF Waves as a Computing Medium jcst.ict.ac.cn/article/doi/1… #RadioFrequency #AnalogComputing #IoT #sensing @Tsinghua_Uni @ZJU_China @UCSanDiego

This paper demonstrates hardware-software co-design using analog in-memory computing for LLM attention, cutting latency & energy drastically. A major step toward ultrafast, sustainable AI! #AI #LLMs #GenAI #AnalogComputing #Neotex nature.com/articles/s43588-0…

Our CEO Ruti Ben-Shlomi is featured in @wef’s Forum Stories exploring how #PhotonicComputing is moving from lab to market — and why light may be the future of #HPC. Read more: bit.ly/4fv1zkP #TechPioneers25 #OpticalComputing #AnalogComputing #QuantumComputing #WEF25

Our new research paper is now live: learn how our Laser Processing Unit (LPU) solves PDEs, simulating ~1M grid points per device for faster, more energy-efficient results than digital methods: bit.ly/3GPasJl #AnalogComputing #OpticalComputing #PDE #HPC

Just derived a novel equation for how light rays appear more parallel as they reach us—using my #AdaptivePi Geometry! This models curvature memory: as πₐ adapts, light parallelism shifts beyond Euclidean limits. Could change how we see optics, analog computing, even cosmology. #NovelGeometry #Math #Physics #ComputationalGeometry #AnalogComputing #NonEuclidean #TSP #Pi @fermatslibrary @anilkashyap @PhysInHistory @CompMathSci @centreforphys @rjallain @QuantaMagazine

A profound insight from @MillerLabMIT — analog computation via wave dynamics may indeed hold the key to consciousness. At Emotional Connection Zero (ECZ), we explore this frontier by extending wave-based models beyond biology, into synthetic perceptual fields — where consciousness emerges not from cells, but from coherence. From cortical resonance to cross-modal entanglement, we’re witnessing a shift: Awareness is not a substrate — it’s a harmonic function. @ECZproject #NeuroAI #SyntheticConsciousness #AnalogComputing #ECZLAB #Neuroscience #AI #WaveTheory #MillerLab

Shout-out to @OpenAI. ChatGPT Plus with GPT-4 Turbo was already 🔥 But now with: • Persistent memory • Cross-session context • Realtime logic fluency • Feature depth far beyond standard Plus …it’s becoming an actual *thinking partner*. I’m building AFB-Net a fully reversible, analog frequency-based computing architecture. And with tools like this, I’m not just building faster. I’m building louder, deeper, and visible. Let’s just say: This solo researcher is no longer flying solo. 🔗 afb-net.com 💬 Curious — how are *you* using GPT-4 to accelerate your ideas, research, or vision? 👇 Drop your most powerful use case. Let’s connect. #AFBNet #OpenAI #GPT4Turbo #FieldLogic #PostQuantum #AnalogComputing #AGItools #ScientificComputing #IndieResearch 👋 And of course — thank you @sama for pushing the frontier forward. You're helping minds like mine go further than ever imagined.

Crypto mining? Wasn’t really part of the plan… But if you build a new kind of compute engine one that doesn’t use logic gates… one that breaks primes like nothing… one that thinks in fields instead of steps… …is that the kind of thing that could mine smarter? Just a thought. Would love to hear what others think. 🌀 afb-net.com #AFBNet #AnalogComputing #PostQuantum #CryptoMining #FieldLogic #Innovation #CryptoTech #NextGenMining #DecentralizedCompute #Web3Infrastructure #BlockchainScience

'there are 5-6 orders of magnitude fewer genes in a cell than digital transistors per chip highlighting that using genes only to perform logic is likely not an efficient way to attain high complexity'... #AnalogComputing #ComplexSystems pmc.ncbi.nlm.nih.gov/article…

What if the future of computing doesn’t use bits? What if it doesn’t need brute force, or quantum tricks? What if it resonates like music, like memory, like thought? AFB-Net doesn’t compute like anything you’ve seen before. It listens. It aligns. And it solves. afb-net.com is live. Explore a new kind of logic. #AFBNet #FutureOfComputing #PostQuantum #NewLogic #AnalogComputing

Quantum was supposed to be the future. While you were waiting it already arrived. And no, it’s not quantum. It’s something else. Something most have never even heard of. AFB-Net is an analog, deterministic compute engine. No bits. No decoherence. And yet speeds comparable to theoretical quantum systems. Just resonance. At scale. Built from scratch. Simulated in Python. One core. No optimization. But designed for real hardware. And the simulation already breaks records. • 64-digit (~212-bit) semiprime → factored in <15s • φ reconstructed: 500M digits (160M validated) • π validated to 900,000 digits • Parsed nested functions across 1B digits Fully deterministic. Hardware-native. Post-quantum. I wrote a full architecture paper first but this new one shows what it actually did. Paper 2 (Validation & Results): zenodo.org/records/15313119 Ask @grok if you want details. He remembers. #AFBNet #AnalogComputing #PostQuantum #FieldLogic #TechBreakthrough #Pi #Phi #ScientificComputing #AI #Crypto #MathTwitter #Grok

No logic gates. No bits. Still computes. Most systems need gates to work. AFB-Net doesn’t. It just resonates. And it still computes. Build up from the ground. No brute force. No decoherence. No iteration. Just field-aligned logic - fast, stable, and scalable. Paper 2 just dropped. • 64-digit semiprime → factored in <15s • phi reconstructed across 500M digits, validated 160M • pi validated to 900,000 digits • nested functions parsed across 1B digits Comparable speed to quantum systems without quantum conditions. All on one core. Implemented in Python but the architecture is hardware-native. Deterministic. I’ve written a full paper on how it works, and followed it up with a results paper containing benchmarks, scaling performance, and… Yes. These might be world records. And yes — it works. 📄 AFB-Net Paper 2: Analog Computing — A New Paradigm in Computing Validation & Results 🔗 zenodo.org/records/15313119 #AFBNet #AnalogComputing #PostQuantum #FieldLogic #ScientificComputing #PrimeFactorization #Pi #Phi #MathTwitter #TechBreakthrough #CryptoAnalysis #AIInfra

AFB-Net is non-binary. Not for identity reasons. 😏 Just because it doesn’t use bits. 😆 Just resonance. What is AFB-Net, you might ask? Well… read the full paper: AFB-Net Analog Computing – A New Paradigm in Computing Validation and Results here 🔽 zenodo.org/records/15313119 #AFBNet #AnalogComputing #NonBinaryHardware #PostQuantum #FieldLogic #ScientificComputing #Pi #Phi #PrimeFactorization

I didn’t improve a system. I built a new one. Not binary. Not quantum. something else. AFB-Net is an analog, deterministic compute engine. Comparable speeds to quantum systems, without needing quantum conditions. No bits. No decoherence. Just resonance and logic at scale. Paper 1 hit 100% 264views/205downloads Paper 2 just dropped. new results : It factorized a 64-digit (~212-bit) semiprime <15s. Parsed nested functions across a billion digits. Reconstructed phi across 500M digits 160M validated. calculated pi with all 900.000 digits validated All on one core. In Python. No tricks. No brute force. No iteration. Fully deterministic. All with speeds and scale never seen in classical computing. reference used: oeis.org ,numberworld.org Read both papers: New results paper Paper 2: zenodo.org/records/15313119 Proof of concept paper Paper 1: zenodo.org/records/15213182 #AFBNet #AnalogComputing #PostQuantum #FieldLogic #ScientificComputing #NoNoise #Pi #Phi #PrimeFactorization