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De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
Artificial intelligence (AI) has seen explosive growth in recent years, revolutionizing industries and reshaping our daily lives. However, with this rapid expansion comes a pressing concern - the energy consumption of AI models. Environmental advocates are beginning to highlight this issue, mirroring the scrutiny that cryptocurrency mining previously faced. A recent report by Alex de Vries, the founder of Digiconomist, seeks to quantify AI's environmental implications.<\/p>\n\n\n\n
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
The Adobe Firefly Imaging Model 2 also integrates generated text and images that can be modified into editable designs. Firefly remains reliant solely on the content derived from its Adobe Stock library. The lack of accessible images would impose constraints on Adobe's model when compared to the extensive datasets employed to train other widely used AI models.<\/p>\n","post_title":"New Features and Enhancements In Adobe Firefly's October Release","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"new-features-and-enhancements-in-adobe-fireflys-october-release","to_ping":"","pinged":"","post_modified":"2023-10-17 00:01:00","post_modified_gmt":"2023-10-16 13:01:00","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13877","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":13819,"post_author":"15","post_date":"2023-10-13 00:33:04","post_date_gmt":"2023-10-12 13:33:04","post_content":"\n
Artificial intelligence (AI) has seen explosive growth in recent years, revolutionizing industries and reshaping our daily lives. However, with this rapid expansion comes a pressing concern - the energy consumption of AI models. Environmental advocates are beginning to highlight this issue, mirroring the scrutiny that cryptocurrency mining previously faced. A recent report by Alex de Vries, the founder of Digiconomist, seeks to quantify AI's environmental implications.<\/p>\n\n\n\n
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
You can now save your images to Creative Cloud Libraries for future use in Adobe Express or any other Cloud Creative apps.<\/li>\n<\/ol>\n\n\n\nThe Adobe Firefly Imaging Model 2 also integrates generated text and images that can be modified into editable designs. Firefly remains reliant solely on the content derived from its Adobe Stock library. The lack of accessible images would impose constraints on Adobe's model when compared to the extensive datasets employed to train other widely used AI models.<\/p>\n","post_title":"New Features and Enhancements In Adobe Firefly's October Release","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"new-features-and-enhancements-in-adobe-fireflys-october-release","to_ping":"","pinged":"","post_modified":"2023-10-17 00:01:00","post_modified_gmt":"2023-10-16 13:01:00","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13877","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":13819,"post_author":"15","post_date":"2023-10-13 00:33:04","post_date_gmt":"2023-10-12 13:33:04","post_content":"\n
Artificial intelligence (AI) has seen explosive growth in recent years, revolutionizing industries and reshaping our daily lives. However, with this rapid expansion comes a pressing concern - the energy consumption of AI models. Environmental advocates are beginning to highlight this issue, mirroring the scrutiny that cryptocurrency mining previously faced. A recent report by Alex de Vries, the founder of Digiconomist, seeks to quantify AI's environmental implications.<\/p>\n\n\n\n
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
AI energy consumption compared to crypto mining's consumption<\/h2>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
\nYou can now save your images to Creative Cloud Libraries for future use in Adobe Express or any other Cloud Creative apps.<\/li>\n<\/ol>\n\n\n\nThe Adobe Firefly Imaging Model 2 also integrates generated text and images that can be modified into editable designs. Firefly remains reliant solely on the content derived from its Adobe Stock library. The lack of accessible images would impose constraints on Adobe's model when compared to the extensive datasets employed to train other widely used AI models.<\/p>\n","post_title":"New Features and Enhancements In Adobe Firefly's October Release","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"new-features-and-enhancements-in-adobe-fireflys-october-release","to_ping":"","pinged":"","post_modified":"2023-10-17 00:01:00","post_modified_gmt":"2023-10-16 13:01:00","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13877","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":13819,"post_author":"15","post_date":"2023-10-13 00:33:04","post_date_gmt":"2023-10-12 13:33:04","post_content":"\n
Artificial intelligence (AI) has seen explosive growth in recent years, revolutionizing industries and reshaping our daily lives. However, with this rapid expansion comes a pressing concern - the energy consumption of AI models. Environmental advocates are beginning to highlight this issue, mirroring the scrutiny that cryptocurrency mining previously faced. A recent report by Alex de Vries, the founder of Digiconomist, seeks to quantify AI's environmental implications.<\/p>\n\n\n\n
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
AI energy consumption compared to crypto mining's consumption<\/h2>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
\nYou can now save your images to Creative Cloud Libraries for future use in Adobe Express or any other Cloud Creative apps.<\/li>\n<\/ol>\n\n\n\nThe Adobe Firefly Imaging Model 2 also integrates generated text and images that can be modified into editable designs. Firefly remains reliant solely on the content derived from its Adobe Stock library. The lack of accessible images would impose constraints on Adobe's model when compared to the extensive datasets employed to train other widely used AI models.<\/p>\n","post_title":"New Features and Enhancements In Adobe Firefly's October Release","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"new-features-and-enhancements-in-adobe-fireflys-october-release","to_ping":"","pinged":"","post_modified":"2023-10-17 00:01:00","post_modified_gmt":"2023-10-16 13:01:00","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13877","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":13819,"post_author":"15","post_date":"2023-10-13 00:33:04","post_date_gmt":"2023-10-12 13:33:04","post_content":"\n
Artificial intelligence (AI) has seen explosive growth in recent years, revolutionizing industries and reshaping our daily lives. However, with this rapid expansion comes a pressing concern - the energy consumption of AI models. Environmental advocates are beginning to highlight this issue, mirroring the scrutiny that cryptocurrency mining previously faced. A recent report by Alex de Vries, the founder of Digiconomist, seeks to quantify AI's environmental implications.<\/p>\n\n\n\n
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
AI energy consumption compared to crypto mining's consumption<\/h2>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
\nYou can now save your images to Creative Cloud Libraries for future use in Adobe Express or any other Cloud Creative apps.<\/li>\n<\/ol>\n\n\n\nThe Adobe Firefly Imaging Model 2 also integrates generated text and images that can be modified into editable designs. Firefly remains reliant solely on the content derived from its Adobe Stock library. The lack of accessible images would impose constraints on Adobe's model when compared to the extensive datasets employed to train other widely used AI models.<\/p>\n","post_title":"New Features and Enhancements In Adobe Firefly's October Release","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"new-features-and-enhancements-in-adobe-fireflys-october-release","to_ping":"","pinged":"","post_modified":"2023-10-17 00:01:00","post_modified_gmt":"2023-10-16 13:01:00","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13877","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":13819,"post_author":"15","post_date":"2023-10-13 00:33:04","post_date_gmt":"2023-10-12 13:33:04","post_content":"\n
Artificial intelligence (AI) has seen explosive growth in recent years, revolutionizing industries and reshaping our daily lives. However, with this rapid expansion comes a pressing concern - the energy consumption of AI models. Environmental advocates are beginning to highlight this issue, mirroring the scrutiny that cryptocurrency mining previously faced. A recent report by Alex de Vries, the founder of Digiconomist, seeks to quantify AI's environmental implications.<\/p>\n\n\n\n
De Vries identifies the training phase of AI models as the most energy-intensive stage. During this phase, AI systems are fed vast datasets, even before they provide any responses. While environmental groups have mostly focused on this stage, De Vries underscores the importance of examining the inference phase as well. In the inference phase, AI models are tested against real-world data, which may significantly contribute to the overall energy footprint.<\/p>\n\n\n\n
AI energy consumption compared to crypto mining's consumption<\/h2>\n\n\n\n
De Vries compares the attention received by AI's energy consumption to that of cryptocurrencies. Notably, the cryptocurrency sector's energy usage garnered substantial public concern only after the 2017 bubble burst. Which highlights the slow response time of environmental groups to emerging energy-related issues.<\/p>\n\n\n\n
While some experts predict catastrophic energy consumption by AI, others argue that these predictions are exaggerated. As AI is a relatively new technology, efficiency improvements are expected to reduce energy consumption in the coming years dramatically. Such improvements in hardware and software efficiencies are anticipated to offset the environmental impact.<\/p>\n\n\n\n
De Vries warns against relying solely on technology advancements to solve AI's environmental issues. He believes that the increase in efficiency might lead to higher AI demand. He hopes that increasing headlines regarding AI's energy consumption will prompt environmental groups to take action, having learned from the cryptocurrency industry's experiences.<\/p>\n\n\n\n
Despite limited available data, De Vries urges the public to consider sustainability and the various challenges AI poses, such as data privacy, biased responses, and the generation of false information. As AI continues to gain prominence, it is essential to balance embracing its potential and addressing its environmental consequences.<\/p>\n","post_title":"AI Energy Consumption Being Compared To Crypto Mining, Researcher Says","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ai-energy-consumption-being-compared-to-crypto-mining-researcher-says","to_ping":"","pinged":"","post_modified":"2023-10-13 00:33:26","post_modified_gmt":"2023-10-12 13:33:26","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.thedistributed.co\/?p=13819","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"total_page":false},"paged":1,"class":"jblog_block_13"};
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