Håvard Ihle ✓

@htihle

AI researcher, I made WeirdML, worried about ASI

2 871Followers

721Following

1 462Posts total

1MViews on collected posts

Последние посты

Håvard Ihle ✓@htihle18 Sep

@htihle btw, how surprised were you with the Astra/Fable score when you got it? Did you expect the score to be much lower (below 25-30%)? Bc if we're already at 55%, well... we have to start thinking about v4 :(( 400 views · 9 likes · 0 reposts · 1 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

Thanks to the Norwegian Defence Research Establishment for allowing me to work on this (it was a LOT of work), and thanks to EpochAI and METR for supporting the API costs of this project. https://t.co/5ofela79jj https://t.co/GigczMF7WR https://t.co/J8Hd7e8I4A 1K views · 60 likes · 1 reposts · 1 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

In WeirdML v2 we had 17 separate tasks, and the models needed to solve them each in 2 minutes on a small GPU. In WeirdML Bonanza, the models get all the 17 WeirdML v2 tasks, and they have to solve all of them at the same time in 2 minutes on the same small GPU. The models do h

1.2K views · 35 likes · 0 reposts · 1 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

The TOD Pipeline task gives the model raw data from a realistic simulation of a radio telescope. It has to use the data to calibrate the telescope, work out the layout of the focal plane, filter the data and map it onto the sky. The raw data includes atmospheric emission, gain

1.3K views · 32 likes · 2 reposts · 1 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

In the Ship Detect task the models are given access to 5k simulated images of different types of ships from various angles and in various conditions. They need to build a ship detection pipeline from scratch using hand-written detection algorithms and small ML models based on h

1.4K views · 41 likes · 1 reposts · 1 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

We give a detailed look into the data and setup for 4 of our 11 tasks, to give an idea of the breadth and complexity of the tasks, and to give more insight into how the tasks are scored. Selected tasks: https://t.co/SrfsmoLrvy 4/8 https://t.co/lHRTsD7Rdm

1.8K views · 37 likes · 0 reposts · 2 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

To get more information from each run, we introduce area-under-the-curve scoring and risk-free hints. Scores become more gradual, the skill ceiling higher and skill floor lower, so each task tells us far more than a single pass/fail grade. Details: https://t.co/S1wraSLjY2 3/8 h

2.3K views · 53 likes · 0 reposts · 1 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

Our initial results show a large advantage for GPT 6 Astra, especially in terms of token efficiency. Results will keep rolling in and new models are being added. Find up-to-date results and all the details on the webpage: https://t.co/uJ2kTxNkHa 2/8 https://t.co/PJwn6f9Lch

2.9K views · 79 likes · 2 reposts · 4 replies Open on X →

Håvard Ihle ✓@htihle18 Sep

Introducing WeirdML v3, a fully agentic benchmark featuring 11 complex hand-made tasks. Models must explore and understand unfamiliar data, develop ML and data analysis pipelines and produce results despite limited data, unspecified goals and/or very limited feedback. 1/8 http

92.4K views · 625 likes · 53 reposts · 51 replies Open on X →

Håvard Ihle ✓@htihle27 Jun 2025

WeirdML v2 is now out! The update includes a bunch of new tasks (now 19 tasks total, up from 6), and results from all the latest models. We now also track api costs and other metadata which give more insight into the different models. The new results are shown in these two https

936.3K views · 253 likes · 22 reposts · 13 replies Open on X →

На фоне аккаунтов своего размера

9 постов за последние 90 дней рядом с диапазоном under 10K подписчиков. доходит до меньшего числа людей, зато вовлекает их куда сильнее.

Медианные просмотры1 443этот аккаунт4 175медиана для under 10K

Охват, %50.26%этот аккаунт250.82%медиана для under 10K

Вовлечённость, %2.71%этот аккаунт1.41%медиана для under 10K

Показатель	Этот аккаунт	Медиана для under 10K	Отношение
Медианные просмотры на пост	1 443	4 175	0.35×
Охват (просмотры ÷ подписчики)	50.26%	2.5× audience	0.20×
Вовлечённость	2.71%	1.41%	1.93×

Другие в этом диапазоне → Сравнить с другим аккаунтом → Как считаются эти ориентиры →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

936.3K27 Jun

92.4K18 Sep

2.9K

2.3K

1.8K

1.4K

1.3K

1.2K

400

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.03%27 Jun

0.80%18 Sep

2.90%

2.34%

2.21%

2.98%

2.72%

2.96%

6.00%

2.50%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.41%.

What the audience does

Likes69.5%1 224 in total

Reposts4.6%81 in total

Replies4.3%76 in total

Quotes1.0%18 in total

Bookmarks20.5%361 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Последние посты

На фоне аккаунтов своего размера

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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