Row 91277

Row ID: 91277 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 91277 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I'm going with "no". I say this as someone that's fairly passionate about machine learning. My objection to the release is based on these points:

- Since we can't tell if the content is hallucinated, in the best case we're left checking results that have been moved farther down the page. In the worst case, people take the result at face value and it's wrong.

- The content, be it right most of the time or not, hallucinates frequently enough that it's embarrassing. Google was always competent at more subtle implementations. Their computational photography was absolutely state of the art. Photo search was top notch. Clever algorithmic ranking used to be great. It was the quiet, carefully considered applications of ML that were most compelling. This feels like a vocal "behold my greatness" when really it's a flagrant demonstration of something that is mediocre at best.

- I can't imagine the carbon footprint of all that inference is small. Since the results are, as mentioned above, somewhere between useless and harmful, it's just dumping greenhouse gas into the atmosphere.

FieldValue
text I'm going with "no". I say this as someone that's fairly passionate about machine learning. My objection to the release is based on these points: - Since we can't tell if the content is hallucinated, in the best case we're left checking results that have been moved farther down the page. In the worst case, people take the result at face value and it's wrong. - The content, be it right most of the time or not, hallucinates frequently enough that it's embarrassing. Google was always competent…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-25
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Raw Record

{
  "text": "I'm going with \"no\".  I say this as someone that's fairly passionate about machine learning.  My objection to the release is based on these points: \n\n- Since we can't tell if the content is hallucinated, in the best case we're left checking results that have been moved farther down the page. In the worst case, people take the result at face value and it's wrong.\n\n- The content, be it right most of the time or not, hallucinates frequently enough that it's embarrassing. Google was always competent at more subtle implementations. Their computational photography was absolutely state of the art. Photo search was top notch. Clever algorithmic ranking used to be great. It was the quiet, carefully considered applications of ML that were most compelling.  This feels like a vocal \"behold my greatness\" when really it's a flagrant demonstration of something that is mediocre at best.\n\n- I can't imagine the carbon footprint of all that inference is small. Since the results are, as mentioned above, somewhere between useless and harmful, it's just dumping greenhouse gas into the atmosphere.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-25",
  "username_encoded": "Z0FBQUFBQm5Lak1zd3B4NGdSa1Y1RjBlZDllelY0LUZWejl3Um9EWkJvNW5fVGNfelZ3RGhTRk53VWxIZTFFaEhfWXVRZFpVZzVjOTZBWWY3WGtBdEJ6c21UdllmeFlucUE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak85SFVmZ3hQdXVkeXZ4c1BHd2FVQ3M2VVRTZDBmS3k3cnRZWkF3M0ZJQW5wVWxBUzVkWDItXy01Z0wybXJ5bVR5ZmI3T1VWd0E3Yk5FMUtXcGI0eVVUcHJHVjdwWmtnTEpxR2pGM2ZZOUFBVXExUFJMWXM1bnVZNjBkZGs0SElDYlhlUzZQUjlyUXF2Vl80RzhTdzA1OGsxYnVCMVRHVUZkdWJwR3ZGRlUta0JIdkJsNmdpZkljSTcza0pLa3Rlazl3VnFMV0Y4ajdLbS1uQVQxaGpjcHNoQWczcU83VlpLRGVMVWt2SkVoLUFZdz0="
}
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