# forck.live — 11–17 April 2022

> 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 2022-W15, 11–17 April 2022, 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/2022-W15
- The current issue, and the catalogue of the other weeks: https://forck.live/briefing.md
- Catalogue: https://forck.live/llms.txt

## Announcements

### Runway — High-Resolution Image Synthesis with Latent Diffusion Models

- Company: Runway (runway.com)
- Announced: 2022-04-13T16:32:44.214000+00:00
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://runway.com/research/high-resolution-image-synthesis-with-latent-diffusion-models
- Record: https://forck.live/items/7943-high-resolution-image-synthesis-with-latent-diffusion-models
- Subject: Gen / Aleph

Runway researchers introduced latent diffusion models (LDMs) that apply diffusion in the latent space of pretrained autoencoders, using cross-attention layers for conditioning inputs such as text or bounding boxes. LDMs achieve competitive performance on unconditional image generation, inpainting, and super-resolution while reducing computational requirements compared to pixel-based diffusion models.

### OpenAI — Measuring Goodhart’s law

- Company: OpenAI (openai.com)
- Announced: 2022-04-13T07:00:00+00:00
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://openai.com/index/measuring-goodharts-law
- Record: https://forck.live/items/912-measuring-goodhart-s-law
- Subject: GPT / ChatGPT / API

OpenAI discusses Goodhart's law, explaining how they must consider it when optimizing hard-to-measure objectives.

### Hugging Face — Machine Learning Experts - Lewis Tunstall

- Company: Hugging Face (huggingface.co)
- Announced: 2022-04-13
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://huggingface.co/blog/lewis-tunstall-interview
- Record: https://forck.live/items/2214-machine-learning-experts-lewis-tunstall
- Subject: Platform

An interview with Lewis Tunstall, a Machine Learning Engineer at Hugging Face, discussing his background, his book 'NLP with Transformers', and his work on the transformers library to enable ONNX export for faster model inference.

### Hugging Face — Habana Labs and Hugging Face Partner to Accelerate Transformer Model Training

- Company: Hugging Face (huggingface.co)
- Announced: 2022-04-12
- Category: partnership-acquisition
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://huggingface.co/blog/habana
- Record: https://forck.live/items/2215-habana-labs-and-hugging-face-partner-to-accelerate-transformer-model-training
- Subject: Platform

Habana Labs and Hugging Face announce a partnership to integrate Habana's SynapseAI software with Hugging Face's Optimum library, enabling faster training of transformer models on Habana Gaudi processors with minimal code changes.