Свежий документ Data Governance in Open Source AI [1] от Open Source Initiative про то как публиковать данные для обучения ИИ с открытым кодом. В документе много всего, важно что они промоутируют отход от чистого определения Open Data и говорят о новом (старом) подходе Data Commons с разными моделями доступа к данным.
Дословно в тексте упоминаются, привожу как есть: - Open data: data that is freely accessible, usable and shareable without restrictions, typically under an open license or in the Public Domain36 (for example, OpenStreetMap data); • Public data: data that is accessible to anyone without authentication or special permissions (for example, Common Crawl data). Note that this data can degrade as web content becomes unavailable; • Obtainable data: data that can be obtained or acquired through specific actions, such as licensing deals, subscriptions or permissions (for example, ImageNet data); • Unshareable non-public data: data that is confidential or protected by privacy laws, agreements or proprietary rights and cannot be legally shared or publicly distributed.
С точки зрения многих в открытых данных всё это звучит как размывание открытости, но с точки зрения практики ИИ в этом есть логика.
Свежий документ Data Governance in Open Source AI [1] от Open Source Initiative про то как публиковать данные для обучения ИИ с открытым кодом. В документе много всего, важно что они промоутируют отход от чистого определения Open Data и говорят о новом (старом) подходе Data Commons с разными моделями доступа к данным.
Дословно в тексте упоминаются, привожу как есть: - Open data: data that is freely accessible, usable and shareable without restrictions, typically under an open license or in the Public Domain36 (for example, OpenStreetMap data); • Public data: data that is accessible to anyone without authentication or special permissions (for example, Common Crawl data). Note that this data can degrade as web content becomes unavailable; • Obtainable data: data that can be obtained or acquired through specific actions, such as licensing deals, subscriptions or permissions (for example, ImageNet data); • Unshareable non-public data: data that is confidential or protected by privacy laws, agreements or proprietary rights and cannot be legally shared or publicly distributed.
С точки зрения многих в открытых данных всё это звучит как размывание открытости, но с точки зрения практики ИИ в этом есть логика.
Soloviev also promoted the channel in a post he shared on his own Telegram, which has 580,000 followers. The post recommended his viewers subscribe to "War on Fakes" in a time of fake news. DFR Lab sent the image through Microsoft Azure's Face Verification program and found that it was "highly unlikely" that the person in the second photo was the same as the first woman. The fact-checker Logically AI also found the claim to be false. The woman, Olena Kurilo, was also captured in a video after the airstrike and shown to have the injuries. Asked about its stance on disinformation, Telegram spokesperson Remi Vaughn told AFP: "As noted by our CEO, the sheer volume of information being shared on channels makes it extremely difficult to verify, so it's important that users double-check what they read." "He has kind of an old-school cyber-libertarian world view where technology is there to set you free," Maréchal said. At its heart, Telegram is little more than a messaging app like WhatsApp or Signal. But it also offers open channels that enable a single user, or a group of users, to communicate with large numbers in a method similar to a Twitter account. This has proven to be both a blessing and a curse for Telegram and its users, since these channels can be used for both good and ill. Right now, as Wired reports, the app is a key way for Ukrainians to receive updates from the government during the invasion.
from hk
