Artificial intelligence/training: Difference between revisions

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===Energy use===

While [[Self-hosting|self-hosted]] models can be trained with a single consumer-grade GPU, data-centers with hundreds or thousands of GPUs (known for being more power-hungry than CPUs) are used to train corporate-grade (or "enterprise") models. This can worsen [[wikipedia:Climate_change|climate change]].

While [[Self-hosting|self-hosted]] models can be trained with a single consumer-grade [[wikipedia:Graphics_processing_unit|GPU]], data-centers with hundreds or thousands of GPUs (known for being more power-hungry than CPUs) are used to train corporate-grade (or "enterprise") models. This can worsen [[wikipedia:Climate_change|climate change]].

===Bandwidth abuse===

Massive data needs massive bandwidth. Scraping web-pages across the entire internet requires sending millions of requests to all known servers. Some AI companies go as far as to ''repeatedly'' send requests for the same content (or several revisions of the same content) as frequent bursts in short intervals, which is indistinguishable from [[wikipedia:Denial-of-service_attack|distributed denial-of-service (DDoS) attacks]].

=== Chip shortage ===

Many AI companies have pre-ordered massive amounts of computer components. So much that it doesn't even fit in their current data-centers. This is done in anticipation for ''more'' data-centers being built.{{Citation needed}} This has caused such components to become scarce, and prices to spike. The most notable being the [[wikipedia:2024–present_global_memory_supply_shortage|increase in RAM prices]].

==Examples==

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 ===Energy use===
-While [[Self-hosting|self-hosted]] models can be trained with a single consumer-grade GPU, data-centers with hundreds or thousands of GPUs (known for being more power-hungry than CPUs) are used to train corporate-grade (or "enterprise") models. This can worsen [[wikipedia:Climate_change|climate change]].
+While [[Self-hosting|self-hosted]] models can be trained with a single consumer-grade [[wikipedia:Graphics_processing_unit|GPU]], data-centers with hundreds or thousands of GPUs (known for being more power-hungry than CPUs) are used to train corporate-grade (or "enterprise") models. This can worsen [[wikipedia:Climate_change|climate change]].
 ===Bandwidth abuse===
 Massive data needs massive bandwidth. Scraping web-pages across the entire internet requires sending millions of requests to all known servers. Some AI companies go as far as to ''repeatedly'' send requests for the same content (or several revisions of the same content) as frequent bursts in short intervals, which is indistinguishable from [[wikipedia:Denial-of-service_attack|distributed denial-of-service (DDoS) attacks]].
+=== Chip shortage ===
+Many AI companies have pre-ordered massive amounts of computer components. So much that it doesn't even fit in their current data-centers. This is done in anticipation for ''more'' data-centers being built.{{Citation needed}} This has caused such components to become scarce, and prices to spike. The most notable being the [[wikipedia:2024–present_global_memory_supply_shortage|increase in RAM prices]].
 ==Examples==