aub3bhat

Soon there will be Lemonade style app driven per hospitalization insurance on top of normal health insurance where for elective procedures you will be able to protect yourself from surprises like balance billing etc.

Translation for those not proficient in Academese: Serverless computing a novel paradigm enabled by a large cloud provider, does not matches our past research, thus we argue why it's not the right thing.

This is classic "if theory does not matches practice lets change the practice" approach, which is far too common in academic systems research.

I trust AWS with knowing what its customers truly want (in terms of performance and cost) and what it can provide,Since AWS has real financial stakes in its success.

A decade ago the same researchers would have mourned emergence of cloud computing as a wrong thing and instead asked for P2P computing since that's what they had spent the decade before doing research on.

Scientists/Academics treat prestige as primary currency, and most would view lack of access to information just as a sign of not being in prestigious enough institution.

You are being naive if you think academia is filled with do-gooders it’s just a race but of another kind.

Unless there is a direct impact of doing something more openly e.g. accessible code base that thousands of researchers can use to publish and cite your work quickly or significant risk of getting scooped. There is very little to motivate any change.

Also if you think journals/review system is bad, just get a glimpse of “grant review” system by NSF/NIH or “tenure committees” etc. They make the worst stack ranking performance review etc. seem light hearted fun.

I think you are overegenralizing applicability of Neural Architecture Search etc. and cherry picking individual examples. There is an enormous gap between what gets published in academia with what’s actually useful.

E.g. Compute wars have only intensified with TPUs and FPGA. sure for training you might be okay with few 1080ti but good luck building any reliable, cheap and low latency service that uses DNNs. Similarly big data for academia is few terabytes but real Big data is Petabytes of street level imagery, Videos/Audio etc.

Without any human assessment or blind testing, claiming one method outperforms another using an ex post facto unsupervised metric is not scientific.

Hwang lets you perform "efficient random access" across the video by building a GOP/Segment aware index. This comes in handy in a lot of applications where you want to access particular frame or set of frames but do not wish to decode and store all frames. Most tools such as ffmpeg (command line application not library) are optimized for sequential decode use case.