# forck.live — 21–27 June 2021 > AI lab announcements, news reports and podcasts. forck.live follows what companies announce about their own products. Press may corroborate an official story; it never leads and never appears as an item of its own. A missing date stays missing. A title is the publisher's words — where a company does not publish in English, an English rendering is listed separately as `Title in English` and named as this site's translation, never as theirs. This file is one issue of the weekly archive: every confirmed first-party announcement of ISO week 2021-W25, 21–27 June 2021, newest first. The window never moves, so this URL always names the same seven days — but a post published inside them and detected later is added when it arrives, so a closed week can still gain entries. Every entry is one first-party announcement, and carries the same eight fields in this order before any others: Company · Announced · Category · Coverage · Announcement · Group · Source · Record `Source` is the company's own page the announcement was traced to and `Record` is this site's page for it. Both are safe to cite. `Coverage` is a number of outlets, or `not counted` — which means this record reached no count of its own, never that nobody wrote about it. `Category` is this tracker's own analysis, and is authoritative wherever it is stated. `not stated` means either that nothing has analysed the post yet or that the analysis placed it outside this taxonomy; neither is a verdict about the announcement. `Announcement` is whether the post is news of something the company did, rather than a how-to, a customer story, a changelog listing or a staffing note. `Group` is which of this record's groups the entry falls in, carried on the entry itself so it holds where the groups are headings and where they are not. One of: `models`, `covered`, `announcements`, `routine`. Anything after `Record` is held detail that only some announcements carry. - This week's page: https://forck.live/week/2021-W25 - The current issue, and the catalogue of the other weeks: https://forck.live/briefing.md - Catalogue: https://forck.live/llms.txt ## Announcements ### Replit — Dynamic version for Nix derivations - Company: Replit (replit.com) - Announced: 2021-06-25 - Category: not stated - Coverage: not counted - Announcement: no - Group: routine - Source: https://replit.com/blog/nix_dynamic_version - Record: https://forck.live/items/18059-dynamic-version-for-nix-derivations - Subject: Replit Agent Replit describes how it solved the problem of specifying a version in Nix derivation code by using the commit short SHA as the version. The post explains the challenges encountered, such as the Nix store not having access to the .git directory, and the solution using copyPathToStore to copy the source files including .git into the store. ### LG AI Research — [ICLR 2021] Part 1: Reinforcement Learning for Real-World Problems - Company: LG AI Research (lgresearch.ai) - Announced: 2021-06-25 - Category: not stated - Coverage: not counted - Announcement: no - Group: routine - Source: https://www.lgresearch.ai/blog/view?seq=125 - Record: https://forck.live/items/4989-iclr-2021-part-1-reinforcement-learning-for-real-world-problems - Subject: EXAONE Highlights from ICLR 2021, specifically reinforcement learning papers, but does not announce any AI product or model from LG AI Research. ### LG AI Research — [ICLR 2021] Part 2: Generative Model Trends at ICLR 2021 - Company: LG AI Research (lgresearch.ai) - Announced: 2021-06-25 - Category: not stated - Coverage: not counted - Announcement: no - Group: routine - Source: https://www.lgresearch.ai/blog/view?seq=126 - Record: https://forck.live/items/4988-iclr-2021-part-2-generative-model-trends-at-iclr-2021 - Subject: EXAONE This blog post from LG AI Research discusses generative model trends at ICLR 2021, highlighting two notable papers: 'Score-based Generative Modeling through Stochastic Differential Equation' and 'VAEBM: A Symbiosis between Variational Autoencoders and Energy-Based Models'. ### LG AI Research — LG AI Research Participated in CVPR 2021 - Company: LG AI Research (lgresearch.ai) - Announced: 2021-06-23 - Category: not stated - Coverage: not counted - Announcement: no - Group: routine - Source: https://www.lgresearch.ai/news/view?seq=124 - Record: https://forck.live/items/11095-lg-ai-research-participated-in-cvpr-2021 - Subject: EXAONE LG AI Research participated in CVPR 2021, a global deep learning conference held online from June 19 to 25. LG AI Research held LG AI Day on June 21 for Korean participants, featuring presentations on domain generalization in urban-scene segmentation, continual learning, and compositional reasoning for complex tasks. ### LG AI Research — LG AI Research Participated in CVPR 2021 - Company: LG AI Research (lgresearch.ai) - Announced: 2021-06-23 - Category: not stated - Coverage: not counted - Announcement: no - Group: routine - Source: https://www.lgresearch.ai/blog/view?seq=124 - Record: https://forck.live/items/4990-lg-ai-research-participated-in-cvpr-2021 - Subject: EXAONE LG AI Research participated in CVPR 2021, an online deep learning conference, where they held LG AI Day with presentations on their research and introduced their Vision lab's work.