Robot Fireflies: How Ornithopter Drones Fly! https://
youtu.be/VTqycrSEPi0?si
=xoztrEN7tC5LCJBg
… via @YouTube #robot #robotics #drone #technology #TechInnovation #dronetec @AlbertoEMachado @Eli_Krumova @postoff25 @Khulood_Almani @anand_narang @NutritiousMind @baski_LA @TanyaSinha_ @devaang @AlAmadi1
AI HARDWARE
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Ornithopter Drones: Revolutionary Robot Fireflies Flight Technology
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MEMS Edge Processing Reduces Hardware for Bearing Fault Detection
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Analog piezo accelerometers: sensor + data conditioner + processing + algorithms.
— Lucian Fogoros (@fogoros) 8 avril 2026
MEMS with edge processing: sensor + algorithms.
Same bearing fault detection, half the hardware.
Partner content with Tronics. #tronics_ai #HM26 pic.twitter.com/xhE6MTCGPEAnalog piezo accelerometers: sensor + data conditioner + processing + algorithms.
MEMS with edge processing: sensor + algorithms.
Same bearing fault detection, half the hardware.
Partner content with Tronics. #tronics_ai #HM26 -
MEMS Technology Enables Standardized Digital Data Processing
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The MEMS approach delivers pre-processed digital data that works with standard processing methods.
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Top AI Stories: Anthropic, Open Source, Tools and Compute
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Top stories in AI today: – Anthropic’s Project Glasswing shows off Mythos AI
– Open-source AI pushes forward with Z AI’s GLM-5.1
– Get to inbox zero with this Claude prompt
– Anthropic continues to rise, locks in 3.5GW compute
– 4 new AI tools, community workflows, and more -
AI Q: The Humanoid Robot That Reads Emotions
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AI Q: The Emotion-Reading Humanoid #Robot That Reacts Like a Real Being
— Ronald van Loon (@Ronald_vanLoon) 8 avril 2026
via @XRoboHub
#Robots #ArtificialIntelligence #Innovation #Technology #Tech pic.twitter.com/qbSfuVU1yLAI Q: The Emotion-Reading Humanoid #Robot That Reacts Like a Real Being
via @XRoboHub #Robots #ArtificialIntelligence #Innovation #Technology #Tech [Translated from EN to English]→ View original post on X — @ronald_vanloon, 2026-04-08 07:27 UTC
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Can it run Gemma4: AI model runs on Nintendo Switch
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Can it run doom was yesterday.
— Chubby♨️ (@kimmonismus) 8 avril 2026
Today is "can it run Gemma4".
It even runs on a Nintendo Switch 1 @ 1.5 t/sec https://t.co/9KQPFXM3uM pic.twitter.com/PLZ9WoBLTwCan it run doom was yesterday. Today is "can it run Gemma4". It even runs on a Nintendo Switch 1 @ 1.5 t/sec Maddie D. Reese (@maddiedreese) Gemma 4 running locally on a Nintendo Switch 🙂 1.5 tokens per second haha, but it runs! @googlegemma @googleaidevs @GoogleDeepMind — https://nitter.net/maddiedreese/status/2041677327604838685#m
→ View original post on X — @kimmonismus, 2026-04-08 07:10 UTC
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Axelera integrates YOLO deployment on specialized AI hardware
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We're looking forward to joining @ultralytics and Innowise today to share a more efficient way to deploy YOLO models. Our new integration allows for deployment on Axelera AIPUs using only a single command. We will be hosting a live demo and may have discounts available for those
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Tensor Parallelism multiplies bandwidth for faster tokens in stacked GPUs
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Tensor Parallelism is a bandwidth multiplier btw That’s why stacking Mac Studios / DGX Sparks / GPUs increases tokens/second (The rate at which the bandwidth is multiplied is what differentiates Unified Memory from VRAM as well)
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Best entry point local LLMs punch above weight low hardware
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To clarify, I never said they were equal (I also believe that local will eventually get there, but that’s different story) These 2 models are the current best entry point for people interested in local LLMs, they punch above their weight w/ relatively low hardware requirements.
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SpaceX AI Colossus 2 Trains Seven Large Language Models
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SpaceXAI Colossus 2 now has 7 models in training: – Imagine V2
– 2 variants of 1T
– 2 variants of 1.5T
– 6T
– 10T Some catching up to do.