Internet Archive Responds to Recording Industry Lawsuit Targeting Obsolete Media - Lemmy.zip

cross-posted from: https://lemmy.zip/post/1463699 [https://lemmy.zip/post/1463699] > Archived version: https://archive.ph/ORbLO [https://archive.ph/ORbLO] > Archived version: https://web.archive.org/web/20230815010318/https://blog.archive.org/2023/08/14/internet-archive-responds-to-recording-industry-lawsuit-targeting-obsolete-media/ [https://web.archive.org/web/20230815010318/https://blog.archive.org/2023/08/14/internet-archive-responds-to-recording-industry-lawsuit-targeting-obsolete-media/]

Scammers vs Impossible Password Game - programming.dev

Now, I know this isn’t quite a meme, given the bad UI here is being used to troll scammers, but this video relates to a popular post here from two months ago, and I thought folks would find this just as humorous in watching others struggle with the same password checker as we all did before: - The Password Game - https://programming.dev/post/259125 [https://programming.dev/post/259125]

Google is already pushing Web Environment Integrity into Chromium - Lemmy

Google pushing web DRM into chromium - Lemmy.zip

Found on hacker news [https://github.com/chromium/chromium/commit/6f47a22906b2899412e79a2727355efa9cc8f5bd].

WIP: Add REST API and OAuth2 Server

**This PR is being split to make reviews easier** * #815 * #817 * #883 * #950 * more on their way... I've started working on a basic REST API for kbin and I wanted to put it out there for feedback - there are still lots of items to implement and designs to discuss. This likely should be split into several issues / a milestone rather than just being a single pull request ### OAuth API requests which access restricted data or modify state must be authenticated by Bearer token, retrieved via OAuth2 `authorization_code` or `client_credentials` flow: #### authorization_code 1. Client makes a request to `GET /authorize?response_type=code&client_id={{oauth_client_id}}&redirect_uri={{uri}}&scope={{scopes}}&state={{oauth_state}}` 2. User is directed to login if not already logged in. 3. Once logged in, user is directed to the consent page that explains what permissions the app is asking for. 4. Permission is checked: - If the user denies the app permission, the user will be redirected to the given redirect URI (if it is one of the URIs your client was initially created with) with an error message explaining that the user denied the request. - If the user permits the app to use those permissions, the user will be redirected with the following request: - `GET {{uri}}/?code={{code}}&state={{oauth_state}}` 5. The client will need to verify the state is correct, then use the code to make a form-data POST request to retrieve the token: ``` POST /token grant_type=authorization_code client_id={{oauth_client_id}} client_secret={{oauth_client_secret}} code={{code}} redirect_uri={{uri}} ``` 6. The server will verify the information and return json with the following data: ``` { "token_type": "Bearer", "expires_in": 3600, "access_token": "{{token}}", "refresh_token": "{{refresh_token}}" } ``` 7. The client can save the access token and use it to authenticate against the API to enjoy a higher rate limit and write/moderate/admin permissions depending on grants requested and user permissions available. 8. When the access token expires, the client may use the refresh token to perform a refresh_token grant_type to avoid making the user log back in. #### client_credentials 1. The client will use its id and secret to make a form-data POST request to retrieve a token authorizing it to use a bot account created when the client was created. ``` POST /token grant_type=client_credentials client_id={{oauth_client_id}} client_secret={{oauth_client_secret}} scope=scope1 scope2 scope3 (etc...) ``` 2. The server will verify the information and return json with the following data: ``` { "token_type": "Bearer", "expires_in": 3600, "access_token": "{{token}}" } ``` 3. The client can save the token and use it to access the API as a user distinguished as a bot account. ### Todo List: - [ ] Add general usage APIs - [ ] Entries/Thread API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve entries by id - [x] Retrieve a list of entries from the instance - [x] Filterable by language(s) - [x] Create an entry in a specific magazine - [x] Upload images with entries - [x] Update single entry by id - [x] Delete entry by id - [x] Upvote entry - [x] Downvote entry - [x] Boost entry - [x] Report entry - [x] Retrieve a list of entries from a specific magazine - [x] Filterable by language(s) - [x] Filterable by preferred languages - [x] Retrieve a list of entries from subscribed magazines - [x] Retrieve a list of entries from moderated magazines - [ ] Entry Comments API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve comments of an entry - [x] Filterable by language(s) - [x] Filterable by preferred languages - [x] Add a comment to an entry - [x] Add a comment reply to another comment - [x] Upload images with comments - [x] Retrieve a comment by id - [x] Update comment by id - [x] Delete comment by id - [x] Upvote comment (Favourite) - [x] Downvote comment - [x] Boost comment - [x] Report comment - [ ] Posts/Microblog API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Create post - [x] Upload images with posts - [x] Retrieve post by id - [x] Retrieve posts from magazine - [x] Filterable by language(s) - [x] Filterable by preferred languages - [x] Update post by id - [x] Delete post by id - [x] Boost post - [x] Favourite post - [x] Report post - [ ] Post Comments API - [x] OpenApi specification - [ ] API test cases - [x] Rate limiting - [x] Create comment on post - [x] Create comment as reply - [x] Upload images with comments - [x] Retrieve post comment by id - [x] Retrieve comments from a post - [x] Filterable by language(s) - [x] Filterable by preferred languages - [x] Update post comment by id - [x] Delete post comment by id - [x] Boost post comment - [x] Favourite post comment - [x] Report post comment - [ ] Magazine API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve details about a magazine (title, rules, description, isAdult, moderators, tags, badges, etc) - [x] By name as well - [x] Retrieve list of magazines - [x] Retrieve list of user's subscribed magazines - [x] Retrieve list of user's moderated magazines - [x] Retrieve list of user's blocked magazines - [x] Subscribe to magazine - [x] Unsubscribe from magazine - [x] Block magazine - [x] Unblock magazine - [x] Retrieve Mod Log - [ ] User API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve user details - [x] Follow user - [x] Unfollow user - [x] Retrieve users following a user - [x] Retrieve users followed by a user (if visible) - [x] Retrieve user's subscribed magazines - [x] Retrieve user's subscribed domains - [x] Block user - [x] Unblock user - [x] Retrieve current user's blocked users - [x] Edit current user's profile - [x] Edit current user's settings - [ ] Message API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve incoming messages - [x] Mark messages as read - [x] Mark messages as not read - [x] Message user - [x] Reply to message thread - [ ] Notification API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve incoming notifications - [x] Retrieve a count of unread notifications - [x] Mark a notification as read - [x] Mark a notification as not read - [x] Mark all notifications as read - [x] Delete a notification - [x] Delete all notifications - [ ] Domain API - [x] OpenAPI specification - [ ] API test cases - [x] Rate limiting - [x] Retrieve domain details - [x] Retrieve entries from domain - [x] Filterable by language(s) - [x] Filterable by preferred languages - [x] Retrieve entry comments from domain - [x] Filterable by language(s) - [x] Filterable by preferred languages - [x] Subscribe to domain - [x] Unsubscribe from domain - [x] Block domain - [x] Unblock domain - [ ] Instance API - [x] OpenAPI specification - [ ] API test cases - [x] Retrieve instance About text - [x] Retrieve instance FAQ text - [x] Retrieve instance Contact text - [x] Retrieve instance Terms of Service text - [x] Retrieve instance Privacy policy text - [x] Retrieve global mod log - [ ] Add moderation APIs - [x] OpenAPI specification - [ ] API test cases - [x] Mark threads as adult - [x] Mark comments as adult - [x] Mark posts as adult - [x] Mark post comments as adult - [x] Pin threads - [x] Trash threads - [x] Restore threads - [x] Trash comments - [x] Restore comments - [x] Trash posts - [x] Restore posts - [x] Trash post comments - [x] Restore post comments - [x] Ban user from magazine - [x] Change language tag of threads - [x] Change language tag of comments - [x] Change language tag of posts - [x] Change language tag of post comments - [ ] Add magazine admin APIs - [x] OpenAPI specification - [ ] API test cases - [x] Create magazine - [x] Update magazine - [x] (Soft) Delete magazine - [x] Purge Entry - [x] Retrieve reports - [x] Reject reports - [x] Accept reports * I think reports should be accessible to all mods, not just the magazine creator - [x] Add moderator(s) - [x] Remove moderator(s) - [x] Create badge(s) - [x] Delete badge(s) * How do these actually work? Are these meant to be like flair on reddit? - [x] Add tag(s) - [x] Remove tag(s) - [x] Retrieve list of banned users - [x] Remove user from ban list - [x] Retrieve list of trashed entries * Also should be available to any mod - [x] Retrieve appearance settings - [x] Update appearance settings - [x] Retrieve magazine statistics - [ ] Admin APIs - [x] OpenAPI specification - [ ] API test cases - [x] Move entry to another magazine - [x] Ban/unban user from instance - [x] Retrieve a list of banned users - [x] Delete user from instance - [x] Purge user from instance - [x] Purge threads/posts/comments - [x] Verify user on instance - [x] Retrieve instance stats - [x] Retrieve instance settings - [x] Update instance settings - [x] Update instance About text - [x] Update instance FAQ text - [x] Update instance Contact text - [x] Update instance Terms of Service text - [x] Update instance Privacy policy text - [x] Retrieve list of defederated instances - [x] Defederate instance - [x] Refederate instance - [x] Retrieve oauth2 clients - [x] Retrieve oauth2 client usage stats - [x] Revoke oauth2 client keys - [ ] Instance Admin Configs - [x] Configurable rate limiting - [x] View API usage data - [ ] Authentication/Authorization pass - [x] OpenAPI specification - [x] API test cases - [x] Implement OAuth2 server for 3rd party application user auth - [x] Add a user consent page informing the user what permissions the app is requesting - [x] Add the minimum page needed to accept - [x] Add information about what roles grant what permissions in a decent manner - [x] Add translatable messages for the page's text and role grants - [x] Add optional client logo to consent page - [ ] Maybe? make it look nice (I am not a UI designer so I'll probably leave this for a future PR by someone else) - [x] Add API to create an API client - similar to Mastodon's [here](https://docs.joinmastodon.org/spec/oauth/) - [x] Add API to view oauth consents given to (an) app(s) - [x] Add API to revoke oauth consent from an app - [ ] Add page to revoke oauth consent from an app - [x] Add appropriate roles to existing APIs - [x] Flesh out what roles need to be separated and break them down by permissions - [x] Enable heavily rate limited anonymous read access to the API - should be enough for normal human usage of the API, but anything heavier should prefer a token Let me know what you think should be added/changed/improved about this list and about the code I've currently got - I'm learning PHP with this project so I expect there to be lots of improvements to be made

The hottest 14 days ever recorded are the last 2 weeks - Lemmy.world

kbin Enhancement Suite: a community-curated script manager that lets you customize your kbin experience - /kbin meta - kbin.social

A couple of weeks ago, @[email protected] made [this post](https://kbin.social/m/kbinStyles/t/75584/kbin-megamod-proposal-and-proof-of-concept-for-integrated-collection-of) about a project that they were working on. Since then, @[email protected], @[email protected], @[email protected] and I have been hard at work, and we...

A break from the lawn: can an iconic meadow seed wider change?

A new study at King's College, Cambridge reveals the striking benefits of letting lawns go wild. But can others be persuaded to break with a 300-year old social norm?

Petals - Run large language models at home, BitTorrent‑style - Lemmy.world

cross-posted from: https://lemmy.world/post/1535820 [https://lemmy.world/post/1535820] > > I’d like to share with you Petals: decentralized inference and finetuning of large language models [https://petals.ml/] > > - https://petals.ml/ [https://petals.ml/] > > - https://research.yandex.com/blog/petals-decentralized-inference-and-finetuning-of-large-language-models [https://research.yandex.com/blog/petals-decentralized-inference-and-finetuning-of-large-language-models] > > > > What is Petals? [https://research.yandex.com/blog/petals-decentralized-inference-and-finetuning-of-large-language-models] > > > > >Run large language models at home, BitTorrent‑style > > > > >Run large language models like LLaMA-65B, BLOOM-176B, or BLOOMZ-176B collaboratively — you load a small part of the model, then team up with people serving the other parts to run inference or fine-tuning. > > >Single-batch inference runs at 5-6 steps/sec for LLaMA-65B and ≈ 1 step/sec for BLOOM — up to 10x faster than offloading, enough for chatbots and other interactive apps. Parallel inference reaches hundreds of tokens/sec. > > >Beyond classic language model APIs — you can employ any fine-tuning and sampling methods, execute custom paths through the model, or see its hidden states. You get the comforts of an API with the flexibility of PyTorch. > > > > - Colab Link [https://colab.research.google.com/drive/1uCphNY7gfAUkdDrTx21dZZwCOUDCMPw8?usp=sharing] > > - GitHub Docs [https://github.com/bigscience-workshop/petals] > > > > >Overview of the Approach > > > > >On a surface level, Petals works as a decentralized pipeline designed for fast inference of neural networks. It splits any given model into several blocks (or layers) that are hosted on different servers. These servers can be spread out across continents, and anybody can connect their own GPU! In turn, users can connect to this network as a client and apply the model to their data. > > When a client sends a request to the network, it is routed through a chain of servers that is built to minimize the total forward pass time. Upon joining the system, each server selects the most optimal set of blocks based on the current bottlenecks within the pipeline. Below, you can see an illustration of Petals for several servers and clients running different inputs for the model. > > > > [https://lemmy.world/pictrs/image/5d01f513-588f-43a5-9185-827217ab2ebb.png] > > > > >Benchmarks > > > > >We compare the performance of Petals with offloading, as it is the most popular method for using 100B+ models on local hardware. We test both single-batch inference as an interactive setting and parallel forward pass throughput for a batch processing scenario. Our experiments are run on BLOOM-176B and cover various network conditions, from a few high-speed nodes to real-world Internet links. As you can see from the table below, Petals is predictably slower than offloading in terms of throughput but 3–25x faster in terms of latency when compared in a realistic setup. This means that inference (and sometimes even finetuning) is much faster with Petals, despite the fact that we are using a distributed model instead of a local one. > > > > [https://lemmy.world/pictrs/image/dad697d6-38a7-4234-b8c8-cf62d667c561.png] > > > > >Conclusion > > > > >Our work on Petals continues the line of research towards making the latest advances in deep learning more accessible for everybody. With this work, we demonstrate that it is feasible not only to train large models with volunteer computing, but to run their inference in such a setup as well. The development of Petals is an ongoing effort: it is fully open-source (hosted at https://github.com/bigscience-workshop/petals [https://github.com/bigscience-workshop/petals]), and we would be happy to receive any feedback or contributions regarding this project! > > > > - You can read the full article here [https://research.yandex.com/blog/petals-decentralized-inference-and-finetuning-of-large-language-models]