Hardware for Machine Learning: Challenges and Opportunities · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/1612.07625/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTHardware for Machine Learning: Challenges and Opportunities — HN submissionhttps://news.ycombinator.com/item?id=14176872urn:hackerpapers:submission:1612.07625:14176872Sun, 23 Apr 2017 06:36:40 GMT<p>Hardware for Machine Learning: Challenges and Opportunities</p><p></p><p>2 points; 0 discussion replies on HN. <a href="https://hackerpaper.kaipfister.de/p/1612.07625/">Paper and source history</a>. A submission is not an endorsement.</p>cs.CVHardware for Machine Learning: Challenges and Opportunities — mentioned by gtanihttps://news.ycombinator.com/item?id=13458490urn:hackerpapers:mention:1612.07625:13458490Sun, 22 Jan 2017 23:51:46 GMT<p>recent discussion of running tensorflow/grad. descent on DSP chips: https://news.ycombinator.com/item?id=13379847 This is a good writeup on mobile/low power devices, lower precision arithmetic, compression, sparsity, hogwild type &quot;naive&quot; assumptions etc https://arxiv.org/abs/1612.07625</p><p><a href="https://hackerpaper.kaipfister.de/p/1612.07625/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CV