Row 88861

Row ID: 88861 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 88861 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Data labeling, data QA, anomaly detection.

Reducing friction in sales processes by automating routine processes and generating coaching / feedback to sales staff.

Customer chat-bot, enhanced with internal customer service wiki

Coding agents.

The ROI is there, you just need staffing and budget and some patience because Rome was not built in a day. The world is moving very fast and you have to look at AI in order to simply maintain your place on the league charts. If you are not embracing AI you have already fallen 2 years beyond, and time is compressing more than ever.

FieldValue
text Data labeling, data QA, anomaly detection. Reducing friction in sales processes by automating routine processes and generating coaching / feedback to sales staff. Customer chat-bot, enhanced with internal customer service wiki Coding agents. The ROI is there, you just need staffing and budget and some patience because Rome was not built in a day. The world is moving very fast and you have to look at AI in order to simply maintain your place on the league charts. If you are not embracing A…
label r/datascience
dataType comment
communityName r/datascience
datetime 2024-05-25
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Raw Record

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  "text": "Data labeling, data QA, anomaly detection. \n\nReducing friction in sales processes by automating routine processes and generating coaching / feedback to sales staff.\n\nCustomer chat-bot, enhanced with internal customer service wiki\n\nCoding agents.\n\nThe ROI is there, you just need staffing and budget and some patience because Rome was not built in a day.  The world is moving very fast and you have to look at AI in order to simply maintain your place on the league charts.  If you are not embracing AI you have already fallen 2 years beyond, and time is compressing more than ever.",
  "label": "r/datascience",
  "dataType": "comment",
  "communityName": "r/datascience",
  "datetime": "2024-05-25",
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}
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