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.
Given the pro-privacy stance of the platform, it’s taken as a given that it’ll be used for a number of reasons, not all of them good. And Telegram has been attached to a fair few scandals related to terrorism, sexual exploitation and crime. Back in 2015, Vox described Telegram as “ISIS’ app of choice,” saying that the platform’s real use is the ability to use channels to distribute material to large groups at once. Telegram has acted to remove public channels affiliated with terrorism, but Pavel Durov reiterated that he had no business snooping on private conversations. These entities are reportedly operating nine Telegram channels with more than five million subscribers to whom they were making recommendations on selected listed scrips. Such recommendations induced the investors to deal in the said scrips, thereby creating artificial volume and price rise. 'Wild West' Markets continued to grapple with the economic and corporate earnings implications relating to the Russia-Ukraine conflict. “We have a ton of uncertainty right now,” said Stephanie Link, chief investment strategist and portfolio manager at Hightower Advisors. “We’re dealing with a war, we’re dealing with inflation. We don’t know what it means to earnings.” Investors took profits on Friday while they could ahead of the weekend, explained Tom Essaye, founder of Sevens Report Research. Saturday and Sunday could easily bring unfortunate news on the war front—and traders would rather be able to sell any recent winnings at Friday’s earlier prices than wait for a potentially lower price at Monday’s open.
from ru
