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The headlong rush to build and deploy machine learning (ML) based artificial intelligence into devices and systems creates its own Mars – Venus clash of cultures. semiengineering.com/a-bridge-from-…

While most fixed-function NN accelerators cannot run Vision Transformers at all, Quadric not only runs transformers, but is poised to continue to deliver large increases in performance. semiengineering.com/compiler-drive…

Quadric's Chimera GPNPU processor core runs ConvNext - the latest and greatest new convolutional neural network. Most other IP vendors cannot run it, or haven't finished their tedious hand-crafted porting. Check out the blog: quadric.io/2024/07/19/con…

NPU IP market shake out accelerates. Imagination abandons NPU effort. Belatedly recognizing that bolting together a hardwired accelerator plus a legacy core is a terrible idea - because it's impossible for the end user to program. CEO's quote sums it up: "Migrating and

No one can predict the next big "breakthrough" that disrupts the leading edge of machine learning models. Could KANs be that next thing? If you are designing SoCs for device/edge applications, you need to be certain your AI accelerator can handle whatever breakthrough comes

AI’s Role In Chip Design Widens, Drawing In New Startups Focus is on letting engineers do much more with the same or fewer resources — & less drudgery semiengineering.com/ais-role-in-ch… #semiEDA #AI Quadric PrimisAI Silimate ChipStack Siemens Synopsys GitHub Copilot

NPU architectures that combine "accelerators" with legacy programmable DSPs or CPU all share a common fatal flaw - a reliance on "fallback" to the legacy core. See why Fallback Fails. quadric.io/2024/05/29/fai…

Good overview article on the need for more flexible, programmable silicon solutions for the automotive market. semiengineering.com/balancing-prog…

The Quadric team will be at #CES2025. We hope to see you there! invt.io/1txb66cxx5c

Question for silicon vendors: Who should be porting new AI models to your chips in the year 2030: Your customer - without needing any hand-holding? You - with an expensive team of support engineers doing the work? Or your IP Vendor - who can't possibly scale up a big enough team

Even one of the luminaries of embedded AI/ML (Pete Warden) finds it hard to get good performance out of a complicated heterogeneous NPU built from (Legacy Core + Accelerator)! Might we suggest to chip designers - including you Qualcomm - that there is a much better

Find out what Goldilocks can teach us about AI/ML inference solutions in state-of-the-art consumer devices. quadric.io/2024/10/22/in-…

SDVs and increased software content shake up the automotive electronics value chain. (SemiWiki) semiwiki.com/artificial-int…

SemiWiki says the predictable thinning of the herd of NPU architectures is upon us. Will 2025 be the year that the 100+ choices of NPUs/GPNPUs coalesces into a handful of viable long-term solutions? semiwiki.com/artificial-int…

Who knew that Hamlet could teach us much ado about AI/ML? semiengineering.com/to-batch-or-no…

70 TOPS is nearly not enough. Need to pack 400 TOPS for robotics at that price point. Check out Quadric is cheaper, and more flexible Gc Cooke

quadric.io/press-release/… Winner winner!! Many thanks to the Edge AI & Vision Alliance for selecting Quadric's Chimera processor family as Product of the Year!

Another new customer joins the family of Quadric Chimera processor users! Thank you, Kyocera for relying upon Quadric to power your future SoC design! quadric.io/press-release/…

The Edge NPU architecture shakeout is accelerating. A handful of winners/survivors will emerge, while dozens will disappear. It's a movie we've all seen before. semiengineering.com/the-coming-npu…

Our growing success is getting noticed! Quadric is pleased to have been included for a second straight year in the EETimes Silicon 100 list. Silicon 100: Startups to Watch in 2025 eetimes.com/silicon-100-20…