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APRIL 2022 I SMT007 MAGAZINE 73 so embarrassed that I didn't know what SAC solder meant. I look at the jar of solder paste every day." "Wow, that was the only thing I knew: S = tin (from Sn), A = silver (from Ag), C = copper (from Cu)," Andy said. "But I looked at the rest of the test and I only knew a thing or two." "I was a bit of a goof-off in high school and now I see the importance of learning," Sue responded. "It's obvious that math and sci- ence are important, but it seems that writing and speaking are, too. Look at what a good speaker Maggie is, and she is clearly a mover and shaker. Aer thinking about it, I'm going to take advantage of all the education that Ivy Benson will support." "I'll bet I was more of a goof-off than you were," Andy told Sue. "But I hear what you are saying. Aer looking at Maggie, John, Frank, and some of the other bosses, I want to do better." Andy reached for her hand. "How about we discuss this more over some pizza aer watch- ing the new Spiderman movie tonight," Andy teased. "Okay, Romeo, but no PDA at work, okay?" Sue teased back. Stay tuned to see how Andy and Sue's plans for more education work out. SMT007 Ronald C. Lasky is an instruc- tional professor of engineer- ing for the Thayer School of Engineering at Dartmouth Col- lege, and senior technologist at Indium Corporation. To read past columns, or contact Lasky, click here. Download The Printed Circuit Assem- bler's Guide to… Solder Defects by Christopher Nash and Dr. Ronald C. Lasky. You can also view other titles in our full I-007e Book library here. Cutting-edge AI is tackling the world's big- gest challenges — but to do so, it needs the most advanced data centers, with thousands of hardware and software components working in perfect har- mony. At GTC, NVIDIA is showcasing the latest data center technologies to accelerate next-genera- tion applications in business, research and art. To keep up with the growing demand for computing these applications, optimization is needed across the entire computing stack, as well as innovation at the level of distributed algorithms, software and systems. Performance growth at the bottom of the com- puting stack, based on Moore's law, can't keep pace with the requirements of these applications. Moore's law, which predicted a 2X growth in com- puting performance every other year, has yielded to Huang's law—that GPUs will double AI perfor- mance every year. Advancements across the entire computing stack, from silicon to application-level software, have contributed to an unprecedented million- x speedup in accelerated computing in the last decade. It's not just about faster GPUs, DPUs and CPUs. Computing based on neural network models, advanced network technologies and distributed software algorithms all contribute to the data center innovation needed to keep pace with the demands of ever-growing AI models. (Source: NVIDIA) Video below: The lighthearted video celebrates the ability of NVIDIA data center solutions to orchestrate unprecedented AI performance. NVIDIA Data Center Grooves to Tune of Million-fold Speedups

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