Practical AI: Don’t Work Harder; Work Smarter

<img width="300" height="300" src="https://www.eejournal.com/wp-content/uploads/2026/08/max-0507-image-for-home-page-blaize-300x300.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="" style="display: block; margin-bottom: 5px; clear:both;max-width: 100%;" link_thumbnail="" decoding="async" fetchpriority="high" srcset="https://www.eejournal.com/wp-content/uploads/2026/08/max-0507-image-for-home-page-blaize-300x300.jpg 300w, https://www.eejournal.com/wp-content/uploads/2026/08/max-0507-image-for-home-page-blaize-150x150.jpg 150w, https://www.eejournal.com/wp-content/uploads/2026/08/max-0507-image-for-home-page-blaize.jpg 500w" sizes="(max-width: 300px) 85vw, 300px" />For the past three years, almost every discussion I&#8217;ve had about AI processors and accelerators has eventually devolved into someone jumping up and down (metaphorically speaking) waving around bigger and bigger numbers: more parameters, more memory bandwidth, more TOPS, more&#8230; well&#8230; you name it, and they&#8217;ve got more of it. After a while, it begins &#8230; <a href="https://www.eejournal.com/article/practical-ai-dont-work-harder-work-smarter/" class="more-link">Read More &#8594;<span class="screen-reader-text"> "Practical AI: Don’t Work Harder; Work Smarter"</span></a>