But the greatest potential lies in linking the two datasets.
但最大的潜力连接两大数据组。
" The goal is to build this huge dataset and make it available."
“我们的目标建立庞大的数据集并使其可被利用。”
The dataset included almost 100 predation events.
该数据集包括近100个捕食事件。
There are a ton of great hand datasets that can really understand hands like this one with 11,000 hands.
有很多很棒的手部数据集可以真正理解手,比如这个有 11000 只手的数据集。
So that's how the engineers get these giant datasets.
这就师们获得这些巨大数据集的方式。
Just as an example, available datasets like Flickr HQ has 70,000 faces. 70,000.
举个例子,像 Flickr HQ 这样的可用数据集有 7 脸。7 欸。
" Our dataset represents a massive collecting effort of thousands of scientists, " Schultheiss said.
“我们的数据集展现了数千名科学家的大规模收集作,”舒尔特斯说。
They then checked their findings against larger datasets that included thousands of adults.
然后,他们将他们的发现与包括成千上成年人在内的大型数据集进行对比。
MegaFace's creators say it's the largest publicly available facial-recognition dataset out there.
MegaFace 的创建者说,这目前最大的公开面部识别数据集。
Those observations were supported in larger datasets of hundreds of newborns and thousands of 9-year-olds.
这些察结果得到了数百名新生儿和数千名9岁儿童的大型数据集的支持。
The children’s math skills are improving and the datasets collected by the robots are huge.
孩子们的数学能力正在提高,机器人收集的数据集也非常庞大。
All the data collected will be stored by the Open Science Foundation as a public dataset.
所有收集到的数据都将由开放科学基金会作为公共数据集存储。
We don't know exactly what's in the datasets used by OpenAI or Midjourney.
我们不知道 OpenAI 或 Midjourney 使用的数据集中到底有什么。
Amazon and Microsoft, two tech giants, now offer tools to help companies improve management of their unstructured datasets, as does Google.
亚马逊和微软这两家科技巨头现在提供具,帮助公司改善对非结构化数据集的管理,谷歌也有类似行动。
Just don't forget the datasets and metrics.
只不要忘记数据集和指标。
D) They have trouble converting face datasets into the right format.
D) 他们在将人脸数据集转换为正确格式时遇到了麻烦。
And when I put the two datasets together, it was just perfect.
当我将两个数据集放在一起时,结果非常完美。
A) No computer is yet able to handle huge datasets of human faces.
A) 目前还没有计算机能够处理庞大的人脸数据集。
It is not only the size of datasets that counts. The better the data, the better the model.
重要的不仅仅数据集的大小。数据越好,模型就越好。
This means that it can synthesize new samples from the learned dataset.
也就说它可以从已学习的数据集中合成新样本。
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