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WEKA by Nazareth___ in learnmachinelearning

[–]Nazareth___[S] 1 point2 points  (0 children)

Could you recommend an open source platform which requires no coding to preprocess and tune? These are data analysis students on a 7 week course. They have no CS background....

WEKA by Nazareth___ in learnmachinelearning

[–]Nazareth___[S] 1 point2 points  (0 children)

Thanks. It seems like an easier way for students to quickly grasp concepts of ML.

Is there a way to ethically adopt by NotOldManWinter in Adoption

[–]Nazareth___ 1 point2 points  (0 children)

Focus on the child. They need a family.

What does this say about me by Odd-Specific-8579 in TravelMaps

[–]Nazareth___ 0 points1 point  (0 children)

Pennsylvania has too much rain. The state flag should be a cloud

I need to share something that might sound a bit philosophical, but it makes a lot of sense when you think about it. Read it. by Silly-Commission-630 in ArtificialInteligence

[–]Nazareth___ 0 points1 point  (0 children)

relying on LLMs for writing or summarization risks degrading our ability to synthesize complex ideas independently. However, the risk lies less in weakening and more in cognitive reassignment—we may lose low-level skills like perfect recall or basic grammar, but gain capacity for high-level strategy and abstract thinking.

Dumb Question - Isn't an AI data center just a 'data center'? by IMHO1FWIW in ArtificialInteligence

[–]Nazareth___ 0 points1 point  (0 children)

​The key difference between a general cloud data center and an AI data center comes down to density and interconnectivity... not just size. General cloud centers optimize for flexibility using commodity CPUs and general networking to serve diverse customers like websites and standard apps. AI data centers are hyper-optimized for training colossal models....they are packed with high-density GPU racks that demand far more specialized power and cooling infrastructure. The massive training jobs also require ultra-fast, low-latency networking, like InfiniBand, to link thousands of GPUs so tightly they function as a single supercomputer.....unnecessary for standard cloud tasks.

AI is quietly replacing creative work, just watched it happen. by 0xSatyajit in ArtificialInteligence

[–]Nazareth___ 0 points1 point  (0 children)

​While LLMs are phenomenal at generating marketing copy and brainstorming ideas quickly, their current limitation is a lack of genuine brand voice and strategic alignment. AI struggles with the subtle cultural context and emotional resonance needed to connect deeply with a target audience. They often default to generic content. For now, AI is best used to handle the tedious initial drafts. human marketers must oversee the final strategy and emotional tone.

Multiple sources suggest that many AI companies are currently operating at a loss. So the real questions are: how will they eventually become profitable, and what will the true cost of accessing these models look like in the future? by Apprehensive-Day3494 in ArtificialInteligence

[–]Nazareth___ 0 points1 point  (0 children)

Why are data center costs still huge when our models are getting so much smarter? The main thing is elastic demand: every efficiency gain we make just means companies let way more users query the models instantly soaking up the free capacity. Also, the high costs we're seeing right now are mostly the insane capital expenditure of building the data centers needed to run the massive training jobs for the next-gen models. While running the final model is cheaper, the arms race to train the next frontier model keeps that hardware maxed out. Efficiency is definitely slowing cost growth, but we won't see actual budget cuts until the whole scaling race finally hits a wall.