InfoSources.md

1. https://lwn.net/Articles/250967/

2. https://lwn.net/Articles/252125/

3. https://lwn.net/Articles/253361/

4. https://lwn.net/Articles/254445/

5. https://lwn.net/Articles/255364/

6. https://lwn.net/Articles/256433/

7. https://lwn.net/Articles/257209/

8. https://lwn.net/Articles/258154/

9. layering in html ,https://github.com/layerJS/layerJS

10. serverless postgres https://neon.tech/blog/hello-world/ , https://github.com/neondatabase/neon/tree/main/pageserver/src

11. intelligent css lady , https://twitter.com/5t3ph/status/1482547945841086465

12. https://github.com/ilonakozak/CoffeeHouse-responsive-website-pure-html-and-css/blob/main/css/style.css, greast css only website

13. https://github.com/shoelace-style/shoelace

14. easy css, https://www.cssbed.com/, water.css

15. https://www.the-paper-trail.org/

16. https://eliot.readthedocs.io/en/stable/ , tells why error happened

17. https://www.misp-project.org/features.html

18. https://jimangel.io/post/auto-gitops-isitstillrunning.com/

19. https://www.cs.cmu.edu/afs/cs/academic/class/15462-f11/www/lec_slides/lec19.pdf

20. https://papers.labml.ai/papers/monthly

21. https://github.com/appsecco/breaking-and-pwning-apps-and-servers-aws-azure-training

22. https://github.com/Yara-Rules/rules

23. https://fivebooks.com/ , https://fs.blog/reading-2018/ , http://libgen.rs/search.php?req=Representation+and+Mind&column=series , https://www.goodreads.com/shelf/show/cognitive-neuroscience , https://fivebooks.com/best-books/consciousness-susan-blackmore/ , https://fivebooks.com/best-books/dick-passingham-cognitive-neuroscience/ , https://fivebooks.com/best-books/consciousness-susan-blackmore/

24. https://dashdash.io/2/waitpid , https://longbets.org/1/

25. https://platform.sh/blog/2020/the-container-is-a-lie/

26. Detect Random Hash, password, git , https://github.com/adobe/stringlifier ,

27. Pytorch Resources, dl , ml , http://www.arxiv-sanity.com/toptwtr?timefilter=month , https://atcold.github.io/pytorch-Deep-Learning/ ,https://github.com/ritchieng/deep-learning-wizard , https://github.com/ritchieng/the-incredible-pytorch , https://github.com/lutzroeder/netron , https://github.com/tirthajyoti/Papers-Literature-ML-DL-RL-AI , https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap , https://github.com/eugeneyan/ml-surveys , https://github.com/terryum/awesome-deep-learning-papers , https://github.com/mhagiwara/100-nlp-papers , https://github.com/huggingface/awesome-papers , https://github.com/HuaizhengZhang/Awesome-System-for-Machine-Learning , https://deeplizard.com/learn/video/Bs1mdHZiAS8 , https://github.com/Machine-Learning-Tokyo/AI_Curriculum

28. git-secrets, https://www.digitalocean.com/community/tutorials/how-to-use-git-hooks-to-automate-development-and-deployment-tasks

29. Decent , https://vapor.network/ , https://www.ravenprotocol.com/ , algorand , https://cs251crypto.stanford.edu/18au-cs251/ , Ocean Protocol , https://medium.com/ravenprotocol/hello-world-raven-protocol-f749bf5fc8cf , https://cryptoweekly.co/ , https://web.archive.org/web/20201007230739/https%3A%2F%2Fcs251crypto.stanford.edu%2F18au-cs251%2Fsyllabus.html , safemoon , https://docs.thetatoken.org/docs/whitepapers

30. Awesome db resource, scalability, cockroach , https://wiki.crdb.io/wiki/spaces/CRDB/pages/16646155/Database+Background , https://web.archive.org/web/20201007205814/https://wiki.crdb.io/wiki/spaces/CRDB/pages/16646155/Database+Background , https://gist.github.com/rava-dosa/6910a00edb00f11968b3b03523d364df

31. Debugging issues, https://about.gitlab.com/blog/2018/11/14/how-we-spent-two-weeks-hunting-an-nfs-bug/ , http://www.be9.io/2015/09/21/memory-leak/ , https://snyk.io/blog/nodejs-how-even-quick-async-functions-can-block-the-event-loop-starve-io/

32. Nfs , https://engineering.salesforce.com/deep-dive-into-cephs-kernel-client-edea75787528 , https://events.static.linuxfound.org/sites/events/files/slides/Collab14_nfsGanesha.pdf , https://www.kernel.org/doc/ols/2006/ols2006v2-pages-59-72.pdf , http://etutorials.org/Linux+systems/unix+internet+security/Part+III+Network+and+Internet+Security/Chapter+15.+Network+Filesystems/15.1+Understanding+NFS/ , http://www.scs.stanford.edu/nyu/02fa/notes/l3.pdf ,

33. Db, https://www.youtube.com/playlist?list=PLSE8ODhjZXjakeQR57ZdN5slUu2oPUr1Y , https://github.com/wiredtiger/wiredtiger/wiki/LevelDB-Benchmark , Run wiredtiger over Raft , https://github.com/cockroachdb/pebble ,

34. Deep Entity Classification system Facebook , Fighting abuse, https://atscaleconference.com/videos-articles/

35. https://medium.com/@rakyll/things-i-wished-more-developers-knew-about-databases-2d0178464f78

36. Ai in compression, https://heartbeat.fritz.ai/a-2019-guide-to-deep-learning-based-image-compression-2f5253b4d811 , https://bair.berkeley.edu/blog/2019/09/19/bit-swap/ , https://arxiv.org/pdf/1904.03567.pdf

37. Agi,https://goertzel.org/agi-curriculum/ , https://cis.temple.edu/~pwang/AGI-Curriculum.html, https://www.kurzweilai.net/the-real-reasons-we-dont-have-agi-yet, https://www.reddit.com/r/agi, https://github.com/fairy-tale-agi-solutions/awesome-artificial-general-intelligence/ , http://www.scholarpedia.org/article/Artificial_General_Intelligence , https://www.reddit.com/r/agi/comments/e1d9tg/have_there_been_any_architectures_to/ , https://www.reddit.com/r/agi/comments/9xheug/the_genius_neuroscientist_who_might_hold_the_key/, https://www.reddit.com/r/agi/comments/9r88t6/agi_research_will_take_a_revolutionary_turn_once/ , https://www.reddit.com/r/agi/comments/eockiq/ray_kurtzeils_pattern_theory_of_mind_and_agi/, https://www.quantamagazine.org/to-build-truly-intelligent-machines-teach-them-cause-and-effect-20180515, https://medium.com/@thoszymkowiak/deepmind-just-published-a-mind-blowing-paper-pathnet-f72b1ed38d46#.snztv4qb9, https://www.reddit.com/r/agi/comments/5yj0bg/deepmind_just_published_a_mind_blowing_paper/, https://www.reddit.com/r/agi/comments/f8c5ar/on_intelligence_by_jeff_hawkins/, https://www.reddit.com/r/agi/comments/b4v030/which_agi_researcher_hutter_goertzel_wang_etc_do/, https://github.com/boris-kz/CogAlg , https://www.reddit.com/r/agi/comments/f3k5pf/n_kaggle_competition_based_on_chollets/ , https://www.reddit.com/r/agi/comments/9sc4ym/is_this_a_good_list_of_approaches_towards_agi_any/ , https://www.reddit.com/r/agi/comments/fkmd4v/reading_list_of_agi/ , chaos theory , https://web.archive.org/web/20100509210614/http://www.markan.net:80/agilinks.html , https://www.reddit.com/r/agi/comments/eisvvu/eli5_data_compression_as_a_key_to_agi/ , https://www.reddit.com/r/artificial/comments/2f8c56/what_is_this_subreddit_about/ck88z9w/ , https://www.reddit.com/r/artificial/wiki/getting-started

38. https://jepsen.io/analyses/yugabyte-db-1.3.1 , db testing , https://asatarin.github.io/testing-distributed-systems/#chaos-engineering , rqlite, resqlite , https://www.scs.stanford.edu/17au-cs244b/labs/projects/muindi_stern.pdf , https://github.com/asatarin/testing-distributed-systems

39. Networking stack, https://blog.packagecloud.io/eng/2016/06/22/monitoring-tuning-linux-networking-stack-receiving-data/ , https://blog.cloudflare.com/why-we-use-the-linux-kernels-tcp-stack/ , https://jvns.ca/blog/2016/06/30/why-do-we-use-the-linux-kernels-tcp-stack/ , https://blog.packagecloud.io/eng/2017/04/21/deconstruct-2017-all-programmers-must-learn-c-and-assembly/ , https://blog.packagecloud.io/eng/2017/03/08/system-calls-are-much-slower-on-ec2/ , https://blog.packagecloud.io/eng/2017/02/21/set-environment-variable-save-thousands-of-system-calls/ , https://blog.packagecloud.io/eng/2017/03/06/micro-optimizations-matter/

40. Anomaly detection , https://arxiv.org/pdf/2009.11732v2.pdf

xgithub_repo.md

1. JAX is Autograd and XLA, brought together for high-performance machine learning research. , https://github.com/google/jax
2. Glow is a machine learning compiler and execution engine for hardware accelerators. It is designed to be used as a backend for high-level machine learning frameworks. , https://github.com/pytorch/glow
3. LocalStack provides an easy-to-use test/mocking framework for developing Cloud applications , https://github.com/localstack/localstack
4. AI layer over databases, https://github.com/mindsdb/mindsdb_native