A recent study by MIT’s Project NANDA highlighted a sobering statistic: Roughly 95% of AI projects fail to deliver ...
Channels, >2,800 Programmable Operations-Scalable to >50,000 Operations on Each Dataset Arriving Every 25 ns with Zero Data Loss at a fraction of the cost of FPGA ...
3. Timeliness and currency: Outdated information undermines AI performance. In fast-changing fields, models that rely on ...
The shift from volume to value requires more than enthusiasm. It requires engineering discipline, business ownership and the ...
1. Risk: AI Monoculture (Shared Blind Spots). This is the most critical and overlooked systemic vulnerability. Building your ...
Is software architecture art, science, engineering, or something new? This debate has long been central to the community.
Memory swizzling is the quiet tax that every hierarchical-memory accelerator pays. It is fundamental to how GPUs, TPUs, NPUs, ...
AlphaFold didn't accelerate biology by running faster experiments. It changed the engineering assumptions behind protein structure prediction.
Left-shifting DFT, scalable tests from manufacturing to the field, enabling system-level tests for in-field debug.
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