【Hacker News搬运】Niantic宣布基于Pokemon Go玩家数据训练的“大型地理空间模型”

hackernews

Title: Niantic announces “Large Geospatial Model” trained on Pokémon Go player data

Niantic宣布基于Pokemon Go玩家数据训练的“大型地理空间模型”

Text:

Url: https://nianticlabs.com/news/largegeospatialmodel

很抱歉，我无法直接访问外部链接来获取内容。但是，我可以指导您如何使用JinaReader（如果这是一个假设的工具或框架）来抓取内容并进行分析。

以下是一个假设的步骤，说明如何使用JinaReader抓取、分析并总结来自提供的链接的内容，以及如何处理非中文内容：

1. **内容抓取**:
   - 使用JinaReader的API或命令行工具，指定目标URL（`https://nianticlabs.com/news/largegeospatialmodel`）进行内容抓取。
   - 确保JinaReader配置了合适的爬虫规则来处理HTML内容。

   ```python
   from jinareader import JinaReader

   reader = JinaReader()
   content = reader.fetch_content("https://nianticlabs.com/news/largegeospatialmodel")

内容分析:
- 使用JinaReader的NLP功能来分析抓取的内容。
- 提取关键信息，如标题、摘要、关键词等。
```
from jinareader import NLPProcessor

nlp_processor = NLPProcessor()
analysis = nlp_processor.analyze(content)
```

翻译非中文内容:

如果内容不是中文，使用JinaReader的翻译功能将其翻译成中文。

from jinareader import Translator

translator = Translator()
translated_content = translator.translate_to_chinese(content)

内容总结:

使用JinaReader的摘要生成功能，或手动编写一个函数来总结内容。

def summarize_content(content):
    # 这里是一个简单的总结函数，实际应用中可能需要更复杂的逻辑
    sentences = content.split('.')
    summary = '. '.join(sentences[:3])  # 假设只取前三个句子作为总结
    return summary

summary = summarize_content(translated_content)

输出结果:

输出分析后的内容、翻译后的内容以及总结。

print("分析后的内容：", analysis)
print("翻译后的内容：", translated_content)
print("内容总结：", summary)

请注意，上述代码是假设性的，因为JinaReader可能不存在，或者其API和功能可能与此描述不同。如果您有JinaReader的具体文档或API，您可以按照其提供的指南来实现上述步骤。

        
## Post by: bookstore-romeo
        
### Comments: 
        
**dankwizard**: We do this at MyFitnessPal.<p>When users scan their barcode, the preview window is zoomed in so users think its mostly barcode. We actually get quite a bit more background noise typically of a fridge, supermarket aisle, pantry etc. but it is sent across to us, stored, and trained on.<p>Within the next year we will have a pretty good idea of the average pantry, fridge, supermarket aisle. Who knows what is next
> **dankwizard**: 我们在MyFitnessPal做这件事<p> 当用户扫描他们的条形码时，预览窗口会放大，这样用户就会认为它主要是条形码。我们实际上会得到更多的背景噪音，通常是冰箱、超市过道、食品储藏室等，但这些噪音会被发送给我们、储存和训练。<p>在明年，我们将对食品储藏室、冰箱、超市走廊的平均情况有一个很好的了解。谁知道接下来会发生什么
            
**relyks**: This is pretty cool, but I feel as a pokehunter (Pokemon Go player), I have been tricked into working to contribute training data so that they can profit off my labor. How? They consistently incentivize you to scan pokestops (physical locations) through &quot;research tasks&quot; and give you some useful items as rewards. The effort is usually much more significant than what you get in return, so I have stopped doing it. It&#x27;s not very convenient to take a video around the object or location in question. If they release the model and weights, though, I will feel I contributed to the greater good.
> **relyks**: 这很酷，但我觉得作为一名扑克猎人（《口袋妖怪Go》玩家），我被欺骗了，去贡献训练数据，这样他们就可以从我的劳动中获利。怎么用？他们一贯鼓励你通过&quot；研究任务&quot；并给你一些有用的东西作为奖励。付出的努力通常比你得到的回报要重要得多，所以我已经停止了这样做；在所讨论的物体或位置周围拍摄视频不太方便。不过，如果他们发布模型和权重，我会觉得我为更大的利益做出了贡献。
            
**CaptainFever**: This title is editorialized. The real title is: &quot;Building a Large Geospatial Model to Achieve Spatial Intelligence&quot;<p>&gt; Otherwise please use the original title, unless it is misleading or linkbait; don&#x27;t editorialize.<p>My personal layman&#x27;s opinion:<p>I&#x27;m mostly surprised that they were able to do this. When I played Pokémon GO a few years back, the AR was so slow that I rarely used it. Apparently it&#x27;s so popular and common, it can be used to train an LGM?<p>I also feel like this is a win-win-win situation here, economically. Players get a free(mium) game, Niantic gets a profit, the rest of the world gets a cool new technology that is able to turn &quot;AR glasses location markers&quot; into reality. That&#x27;s awesome.
> **CaptainFever**: 这个标题是社论式的。真正的标题是：&quot；构建大型地理空间模型以实现空间智能&quot<p> &gt；否则，请使用原始标题，除非它具有误导性或链接诱饵；不要；不要发表社论<p> 我个人的外行；她的观点：<p>我；我很惊讶他们能做到这一点。几年前我玩《口袋妖怪GO》时，AR太慢了，我很少使用它；它如此受欢迎和普遍，可以用来训练LGM吗<p> 我也觉得在经济上，这是一个三赢的局面。玩家可以获得免费（增值）游戏，Niantic可以获利，世界其他地区可以获得一项很酷的新技术；AR眼镜位置标记”；成为现实。那；太棒了。
            
**ggm**: Not wanting to over-do it, but is there possibly an argument the data about geospatial should be in the commons and google have some obligation to put the data back into the commons?<p>I&#x27;m not arguing to a legal basis but if it&#x27;s crowdsourced, then the inputs came from ordinary people. Sure, they signed to T&amp;Cs.<p>Philosophically, I think knowledge, facts of the world as it is, even the constructed world, should be public knowledge not an asset class in itself.
> **ggm**: 不想做得太过火，但是否有人认为地理空间的数据应该放在公共资源中，谷歌有义务将数据放回公共资源中<p> 我；我不是在争论法律依据，但如果；如果是众包，那么投入就来自普通人。当然，他们签了T&amp；Cs<p> 从哲学上讲，我认为知识、世界的事实，甚至是构建的世界，本身都应该是公共知识，而不是资产类别。
            
**yalogin**: Even before LLMs, I knew they are going to launch a fine grained mapping service with all that camera and POI data. Now this one is actually much better obviously. Very few companies actually have this kind of data. Remains to be seen how they make money out of this
> **yalogin**: 甚至在LLM之前，我就知道他们将推出一个包含所有摄像头和POI数据的细粒度地图服务。现在这个明显好多了。实际上，很少有公司有这样的数据。他们如何从中赚钱还有待观察