Artificial intelligence/training: Difference between revisions

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'''AI training''' is a process by which data is fed into an AI model, in order to adjust its weights. This makes the output of the model closely match that of its input.

'''AI training''' is a process by which data is fed into an [[Artificial intelligence|AI]] model, in order to adjust its weights. This makes the output of the model closely match that of its input.

==How it works==

There are several ways to implement AI, and even more ways to train them, the most well-known being [[wikipedia:Backpropagation|backpropagation]]. With respect to the data-set, LLMs must be trained on massive amounts of data, which is a task that's only feasible via automation. This is in contrast to curated data-sets, in which both the data and the training is done in a more carefully controlled environment. Automated training on massive data-sets is typically done using internet web-sites as sources. The process of scraping is similar to how web-[[wikipedia:Search_engine|search-engines]] index and [[wikipedia:Cache_(computing)|cache]] pages.

There are several ways to implement AI, and even more ways to train them, the most well-known being [[wikipedia:Backpropagation|backpropagation]]. With respect to the data-set, LLMs must be trained on massive amounts of data, which is a task that's only feasible via automation. This is in contrast to curated data-sets, in which both the data and the training is done in a more carefully controlled environment. Automated training on massive data-sets is typically done using internet web-sites as sources. The process of [[wikipedia:Web_scraping|scraping]] is similar to how web-[[wikipedia:Search_engine|search-engines]] index and [[wikipedia:Cache_(computing)|cache]] pages.

==Why it is a problem==

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While it is good practice for a bot to respect <code>robots.txt</code>, there is no requirement for it, and there is no punishment for not following a website's wishes. It is additionally standard practice, but in no way enforced, that bots use a [[wikipedia:User-Agent header|User-Agent header]] to uniquely identify itself. This allows a website operator to observe a bot's traffic patterns, potentially blocking the bot outright if its scraping is not desirable. The header also typically contains a URL or email address that can be used to contact the operator in case of anomalies observed in its traffic.

Unethical ~~[[Artificial_intelligence|~~AI]] scraper bots do not follow <code>robots.txt</code> - in fact, they may not even request this file at all. They typically completely ignore it, instead opting to start from an entry point such as the root home page (<code>/</code>), working its way through an exponentially growing list of links as it finds them, with little to no delay between requests. The bots use false User-Agent header strings that would correspond to real web browsers on desktop or mobile operating systems - blocking them would also block legitimate users, or at least legitimate users on VPNs.

Unethical AI scraper bots do not follow <code>robots.txt</code> - in fact, they may not even request this file at all. They typically completely ignore it, instead opting to start from an entry point such as the root home page (<code>/</code>), working its way through an exponentially growing list of links as it finds them, with little to no delay between requests. The bots use false User-Agent header strings that would correspond to real web browsers on desktop or mobile operating systems - blocking them would also block legitimate users, or at least legitimate users on VPNs.

Some AI services opt to use separate User-Agent strings, potentially also ignoring <code>robots.txt</code>, when a request is made through user command rather than as part of model training. For example, ChatGPT identifies itself as <code>ChatGPT-User</code> rather than its standard <code>OpenAI</code> when it uses the "search the web" command - even if searching the web was an automatic decision. In a less favorable example, Perplexity AI in this same situation falsely identifies as a standard [[Google_Chrome|Chrome]] web browser running on [[Microsoft_Windows|Windows]]. AI companies defend this under the belief that they are not a "spider", but rather a "user agent" (like a web browser), when called upon by a user's request.<ref name="perplexity-aws" />

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[[Category:Artificial intelligence]]

[[Category:Artificial intelligence|*Training]]

@@ Line 1: / Line 1: @@
 {{Incomplete}}
-'''AI training''' is a process by which data is fed into an AI model, in order to adjust its weights. This makes the output of the model closely match that of its input.
+'''AI training''' is a process by which data is fed into an [[Artificial intelligence|AI]] model, in order to adjust its weights. This makes the output of the model closely match that of its input.
 ==How it works==
-There are several ways to implement AI, and even more ways to train them, the most well-known being [[wikipedia:Backpropagation|backpropagation]]. With respect to the data-set, LLMs must be trained on massive amounts of data, which is a task that's only feasible via automation. This is in contrast to curated data-sets, in which both the data and the training is done in a more carefully controlled environment. Automated training on massive data-sets is typically done using internet web-sites as sources. The process of scraping is similar to how web-[[wikipedia:Search_engine|search-engines]] index and [[wikipedia:Cache_(computing)|cache]] pages.
+There are several ways to implement AI, and even more ways to train them, the most well-known being [[wikipedia:Backpropagation|backpropagation]]. With respect to the data-set, LLMs must be trained on massive amounts of data, which is a task that's only feasible via automation. This is in contrast to curated data-sets, in which both the data and the training is done in a more carefully controlled environment. Automated training on massive data-sets is typically done using internet web-sites as sources. The process of [[wikipedia:Web_scraping|scraping]] is similar to how web-[[wikipedia:Search_engine|search-engines]] index and [[wikipedia:Cache_(computing)|cache]] pages.
 ==Why it is a problem==
@@ Line 37: / Line 37: @@
 While it is good practice for a bot to respect <code>robots.txt</code>, there is no requirement for it, and there is no punishment for not following a website's wishes. It is additionally standard practice, but in no way enforced, that bots use a [[wikipedia:User-Agent header|User-Agent header]] to uniquely identify itself. This allows a website operator to observe a bot's traffic patterns, potentially blocking the bot outright if its scraping is not desirable. The header also typically contains a URL or email address that can be used to contact the operator in case of anomalies observed in its traffic.
-Unethical [[Artificial_intelligence|AI]] scraper bots do not follow <code>robots.txt</code> - in fact, they may not even request this file at all. They typically completely ignore it, instead opting to start from an entry point such as the root home page (<code>/</code>), working its way through an exponentially growing list of links as it finds them, with little to no delay between requests. The bots use false User-Agent header strings that would correspond to real web browsers on desktop or mobile operating systems - blocking them would also block legitimate users, or at least legitimate users on VPNs.
+Unethical AI scraper bots do not follow <code>robots.txt</code> - in fact, they may not even request this file at all. They typically completely ignore it, instead opting to start from an entry point such as the root home page (<code>/</code>), working its way through an exponentially growing list of links as it finds them, with little to no delay between requests. The bots use false User-Agent header strings that would correspond to real web browsers on desktop or mobile operating systems - blocking them would also block legitimate users, or at least legitimate users on VPNs.
 Some AI services opt to use separate User-Agent strings, potentially also ignoring <code>robots.txt</code>, when a request is made through user command rather than as part of model training. For example, ChatGPT identifies itself as <code>ChatGPT-User</code> rather than its standard <code>OpenAI</code> when it uses the "search the web" command - even if searching the web was an automatic decision. In a less favorable example, Perplexity AI in this same situation falsely identifies as a standard [[Google_Chrome|Chrome]] web browser running on [[Microsoft_Windows|Windows]]. AI companies defend this under the belief that they are not a "spider", but rather a "user agent" (like a web browser), when called upon by a user's request.<ref name="perplexity-aws" />
@@ Line 110: / Line 110: @@
 {{reflist}}
-[[Category:Artificial intelligence]]
+[[Category:Artificial intelligence|*Training]]