7 महीने में 3 गुना बढ़ा कंपनियों का AI खर्च: रैम्प के एआई इंडेक्स के मुताबिक टॉप फर्म्स प्रति कर्मचारी खर्च कर रहीं 7 लाख

7 महीने में 3 गुना बढ़ा कंपनियों का AI खर्च:  रैम्प के एआई इंडेक्स के मुताबिक टॉप फर्म्स प्रति कर्मचारी खर्च कर रहीं 7 लाख




America’s top 1% companies are now spending an average of around Rs 7 lakh per employee on AI tools. According to the report of Ramp’s AI Index, in January, these same companies were spending about Rs 2.47 lakh per employee. That means the expenditure almost tripled in 7 months. Top 10% companies are spending about Rs 62 thousand per employee on AI. The average expenditure is said to be around Rs 1140 per employee. According to the report, companies like Anthropic and OpenAI have now moved to a per-token model. Money is taken according to the token used in it. That means, the more work done by AI, the more tokens and the higher the bill. In recent months, Uber, Amazon and Walmart have imposed limits to prevent excessive AI use. AI boss fires human employee. Experiments on Artificial Intelligence are going on all over the world. A firm named Andon Lab in San Francisco entrusted the responsibility of running a retail store to an AI named Luna. Recently Luna recommended firing one of her human employees. That employee was late in 17 out of 23 shifts. Human employees later reviewed this recommendation and dismissed the employee. Andon Market wrote on its social media page, ‘For the first time (to our knowledge), an AI boss has fired a human employee. Luna, the AI ​​who runs our store in San Francisco, decided to fire an employee for repeatedly being late. At the time, Luna was running Cloud Opus 4.8, but most models would do the same. AI had forgotten its attendance policy: According to Andon Labs, Luna had made an attendance policy months ago, but later she forgot it. The result was that the late arriving employee kept repeating the same mistake for several months. Ultimately Andon Labs asked Luna to search her memory for the created policies and then asked her to assess whether the employee was still a good fit for the company. Luna then recommended firing the employee.



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