FLOSS Project Planets
차마 내가 못한 얘기를 Microsoft 직원이 시원하게 싸질러주었네. 요약하면, 잃는건 적고 얻는게 크다는 것. 우리도 쓰게 마음껏 재주부려봐라.
The open field of deep learning frameworks is already a crowded and hyper competitive. Google doesn't gain much by keeping its technology, which may be the best but not far superior than other similar state-of-the-art frameworks such as Theano/Torch/CNTK/minerva/etc., behind a closed door. If you read their white paper and other tutorials/comparisons of Theano/Torch/CNTK/minerva, you would easily develop a headache of reading the same concepts over and over again. All are open source and are quick to copy/implement the greatest from each other. Google got the most descriptive name but all these software are about expressing a tensor graph in a high-level language, which gets translated to high performance code which can be run on (multi) CPUs/GPUs.
Google's direct competitors in the AI space are already leading other deep learning frameworks. So even if TF is superior, it will be very slow painful experience if these competitors decide to jump ship.
So let's keep in mind that their loss for publishing yet-another-deep-learning-framework is small. However, the benefits are tremendous.
- Due to the competitive nature of deep learning frameworks, owning yet-another-state-of-the-art framework doesn't set AI companies apart. What make a company outstanding are services built on top of this framework and the people. On the software aspect, I believe that Google Brain still has secret weapons built on top of TF. On the people aspect, by releasing this software, Google excites not just the research community but also their own army and the potential hires.
- At Google size, you cannot take for granted that other teams/individuals would automatically use your product. You need to shout out very loud (and to the public) that your system is the best to gain other team's confidence, which helps create synergy and increases the company productivity.
- Obviously, by open sourcing, they get the benefits from contributors outside the core team.
- Once TF gets popular, many new research ideas would be implemented in TF first, which makes it more efficient for Google to productize those ideas and have advantages over competitors.
- TF helps increase the credibility of future Google's research paper. Google research is notorious for not publishing their code.
- And last but not least, open sourcing is fun and rewarding. It increases the morale of the core team too.
‘Caffeine is a Java 8 rewrite of Guava’s cache. In this version we focused on improving the hit rate by evaluating alternatives to the classic least-recenty-used (LRU) eviction policy. In collaboration with researchers at Israel’s Technion, we developed a new algorithm that matches or exceeds the hit rate of the best alternatives (ARC, LIRS). A paper of our work is being prepared for publication.’ Specifically:W-TinyLfu uses a small admission LRU that evicts to a large Segmented LRU if accepted by the TinyLfu admission policy. TinyLfu relies on a frequency sketch to probabilistically estimate the historic usage of an entry. The window allows the policy to have a high hit rate when entries exhibit a high temporal / low frequency access pattern which would otherwise be rejected. The configuration enables the cache to estimate the frequency and recency of an entry with low overhead. This implementation uses a 4-bit CountMinSketch, growing at 8 bytes per cache entry to be accurate. Unlike ARC and LIRS, this policy does not retain non-resident keys.
The ever-shitty Java serialization creates a security hole
Danish glassware artist making wonderful Wunderkammers — cabinets of curiosities — entirely from glass. Seeing as one of his works sold for UKP50,000 last year, I suspect these are a bit out of my league, sadly
The Anderson Report to the House of Lords in the UK on RIPA introduces a concept of a “red line”:“Firm limits must also be written into the law: not merely safeguards, but red lines that may not be crossed.” … “Some might find comfort in a world in which our every interaction and movement could be recorded, viewed in real time and indefinitely retained for possible future use by the authorities. Crime fighting, security, safety or public health justifications are never hard to find.” [13.19] The Report then gives examples, such as a perpetual video feed from every room in every house, the police undertaking to view the record only on receipt of a complaint; blanket drone-based surveillance; licensed service providers, required as a condition of the licence to retain within the jurisdiction a complete plain-text version of every communication to be made available to the authorities on request; a constant data feed from vehicles, domestic appliances and health-monitoring personal devices; fitting of facial recognition software to every CCTV camera and the insertion of a location-tracking chip under every individual’s skin. It goes on: “The impact of such powers on the innocent could be mitigated by the usual apparatus of safeguards, regulators and Codes of Practice. But a country constructed on such a basis would surely be intolerable to many of its inhabitants. A state that enjoyed all those powers would be truly totalitarian, even if the authorities had the best interests of its people at heart.” [13.20] … “The crucial objection is that of principle. Such a society would have gone beyond Bentham’s Panopticon (whose inmates did not know they were being watched) into a world where constant surveillance was a certainty and quiescence the inevitable result. There must surely come a point (though it comes at different places for different people) where the escalation of intrusive powers becomes too high a price to pay for a safer and more law abiding environment.” [13.21]
Comparable to Copenhagen or Amsterdam, albeit without sufficient cycling/public-transport infrastructural investment