{
  "user": {
    "created_at": "2014-04-27T00:20:12.000Z",
    "default_profile_image": false,
    "description": "AI research paper tweets, ML @Gradio (acq. by @HuggingFace 🤗)\n\ndm for promo",
    "fast_followers_count": 0,
    "favourites_count": 26248,
    "followers_count": 229989,
    "friends_count": 1862,
    "has_custom_timelines": true,
    "is_translator": false,
    "listed_count": 3046,
    "location": "subscribe → ",
    "media_count": 13651,
    "name": "AK",
    "normal_followers_count": 229989,
    "possibly_sensitive": false,
    "profile_banner_url": "https://pbs.twimg.com/profile_banners/2465283662/1610997549",
    "profile_image_url_https": "https://pbs.twimg.com/profile_images/1451191636810092553/kpM5Fe12_normal.jpg",
    "screen_name": "_akhaliq",
    "statuses_count": 21274,
    "translator_type": "none",
    "url": "https://t.co/TbGnXZJwEc",
    "verified": false,
    "withheld_in_countries": [],
    "id_str": "2465283662"
  },
  "id": "1697100539731857796",
  "conversation_id": "1697100539731857796",
  "full_text": "WeatherBench 2: A benchmark for the next generation of data-driven global weather models\n\npaper page: https://t.co/aFQVm2hPwR\n\nWeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an open-source evaluation framework, publicly available training, ground truth and baseline data as well as a continuously updated website with the latest metrics and state-of-the-art models: https://t.co/fBQwwe2iVM. This paper describes the design principles of the evaluation framework and presents results for current state-of-the-art physical and data-driven weather models. The metrics are based on established practices for evaluating weather forecasts at leading operational weather centers. We define a set of headline scores to provide an overview of model performance. In addition, we also discuss caveats in the current evaluation setup and challenges for the future of data-driven weather forecasting.",
  "reply_count": 2,
  "retweet_count": 37,
  "favorite_count": 177,
  "hashtags": [],
  "symbols": [],
  "user_mentions": [],
  "urls": [
    {
      "url": "https://t.co/qKmLBK1cKb",
      "expanded_url": "https://huggingface.co/papers/2308.15560",
      "display_url": "huggingface.co/papers/2308.15…"
    }
  ],
  "media": [
    {
      "media_url": "https://pbs.twimg.com/media/F41P7pJXIAAuGiO.jpg",
      "type": "photo"
    }
  ],
  "url": "https://twitter.com/_akhaliq/status/1697100539731857796",
  "created_at": "2023-08-31T04:14:33.000Z",
  "#sort_index": "1697100539731857796",
  "view_count": 51975,
  "quote_count": 2,
  "is_quote_tweet": false,
  "is_retweet": false,
  "is_pinned": false,
  "is_truncated": true,
  "startUrl": "https://twitter.com/_akhaliq/status/1697100539731857796"
}