[D] Startup team demonstrates differentiable Swift compiler outrunning TensorFlow by 322X

Autonomous systems startup, PassiveLogic, assembled a differentiable computing team, to build a fast systems language with native performance differentiability. Their latest benchmark trains networks two orders of magnitude faster than PyTorch and Tensorflow. See: [LinkedIn Post](https://www.linkedin.com/feed/update/urn:li:activity:7117911978106355712/?commentUrn=urn%3Ali%3Acomment%3A(activity%3A7117911978106355712%2C7118052434916110337)&dashCommentUrn=urn%3Ali%3Afsd_comment%3A(7118052434916110337%2Curn%3Ali%3Aactivity%3A7117911978106355712))

It's a collaborative effort with the Swift community and Apple's compiler team, using the Swift language as a strongly typed embedded language that performs ahead of time compilation of graph neural nets. The focus is on fusing systems programming and AI engineering into a …

ai engineering apple collaborative community compilation compiler development embedded engineering focus graph graph neural nets inference language machinelearning neural nets performance programming swift systems team training