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Is machine learning, also known as “artificial intelligence”, really aiding workers and increasing productivity? A study by Upwork – which, as Baldur Bjarnason so helpfully points out, sells AI solutions and hence did not promote this study on its blog as it does with its other studies – reveals that this might not actually be the case. Nearly half (47%) of workers using AI say they have no idea how to achieve the productivity gains their employers expect. Over three in four (77%) say AI tools have decreased their productivity and added to their workload in at least one way. For example, survey respondents reported that they’re spending more time reviewing or moderating AI-generated content (39%), invest more time learning to use these tools (23%), and are now being asked to do more work (21%). Forty percent of employees feel their company is asking too much of them when it comes to AI. ↫ Upwork research This shouldn’t come as a surprise. We’re in a massive hype cycle when it comes to machine learning, and we’re being told it’s going to revolutionise work and lead to massive productivity gains. In practice, however, it seems these tools just can’t measure up to the hyped promises, and in fact is making people do less and work slower. There’s countless stories of managers being told by upper management to shove machine learning into everything, from products to employee workflows, whether it makes any sense to do so or not. I know from experience as a translator that machine learning can greatly improve my productivity, but the fact that there are certain types of tasks that benefit from ML, doesn’t mean every job suddenly thrives with it. I’m definitely starting to see some cracks in the hype cycle, and this study highlights a major one. I hope we can all come down to earth again, and really take a careful look at where ML makes sense and where it does not, instead of giving every worker a ChatGPT account and blanket demanding massive productivity gains that in no way match the reality on the office floor. And of course, despite demanding massive productivity increases, it’s not like workers are getting an equivalent increase in salary. We’ve seen massive productivity increases for decades now, while paychecks have not followed suit at all, and many people can actually buy less with their salary today than their parents could decades ago. Demands imposed by managers by introducing AI is only going to make this discrepancy even worse.

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ChatGPT is a text-based generative AI tool that can do various tasks. In this course, you will learn how to write prompts, generate content, generate codes and utilise its powerful features.

In this video lesson, we will learn about Generating Tables in ChatGPT.

You can access the entire ChatGPT Course in the following playlist:
https://dailymotion.com/rss/playlist/x8jx4a

Srisailam project has reached full capacity. In this background, the officials of the project raised ten gates of water to Nagarjuna Sagar.
శ్రీశైలం ప్రాజెక్టు పూర్తిస్థాయి సామర్థ్యానికి చేరుకుంది. ఈ నేపథ్యంలో ప్రాజెక్టు పదిగేట్లు ఎత్తి నీటిని నాగార్జున సాగర్ కు అధికారులు వదులుతున్నారు.
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In the latest installment of the “Thoughts on Starshot” series, The DropTimes captures the diverse perspectives of the Drupal community on the eagerly anticipated Drupal Starshot initiative. This article delves into the reflections, hopes, and insights shared by key community members, including Kristen Pol, Murray Woodman, Nicolas Loye, Martin Anderson-Clutz, and Tim Hestenes Lehnen. As the community eagerly awaits the release of Drupal Starshot, this series highlights the collective excitement and anticipation, offering a glimpse into how Starshot is expected to shape the future of Drupal and its broader community.

Ruby on Rails Developer Quiz – How many questions can you get right?