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Joined 1 year ago
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Cake day: June 6th, 2023

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  • Not OP, but I copy my reply from the last time someone asked an opinion on kagi:

    I use it, but to be honest I did not do a comprehensive comparison. I like it mostly for the fine grained website control. For work and some personal stuff I often look for code and can push websites like GitHub to appear more often. Or I can block Pinterest in my search results. I tried to do this in SearXNG, but this was too much of a hassle so in a way I pay kagi for convenience. I recently got a new job and will evaluate in the coming months if it is still worth the money, but right now I am satisfied. Nobody else I know would pay for a search engine, so I can understand the stance, but I am really fed up with all the advertising and enshitification so I thought why not give it a try. And yes, because it was recommended here.









  • When people talk about AI, they’re generally referring to systems or machines that can perform tasks which typically require human intelligence. These tasks might include things like recognizing speech, translating languages, or making decisions. AI isn’t about simulating human consciousness or emotions but about replicating the ability to perform specific intelligent tasks.

    AI systems can range from simple, rule-based algorithms (which might seem like glorified if-else statements) to complex, learning systems. This is where machine learning comes in. Machine learning is actually a subset of AI. It’s a way of achieving AI where the system learns from data. Instead of being explicitly programmed to perform a task, the system is given huge amounts of data and learns patterns or rules from it. Over time, it can make predictions or decisions based on what it has learned.

    So, not all AI is machine learning, but all machine learning is AI. Hope this clears things up a bit!




  • Mkengine@feddit.detoScience Memes@mander.xyz*sad laughing noises*
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    7 months ago

    I have ADHD and finishing my PhD right now. My doctoral supervisor practically gave me free rein and I was able to let my creativity run free. This resulted in a new method in the field of ML that we now even have patented. But let me tell you, everything around it was hell. The teaching was exhausting, the lectures were exhausting and the publishing was exhausting. I’m glad it’s over, all those boring tasks are really getting on my nerves and I’m looking forward to working in the industry soon. So if you really consider this, don’t rush this decision.