10 major VPN companies are run the people of same group. so think about #privacy again when paying for it.

**Bias and Fairness**: These models can inherit biases present in the training data, which may lead to unfair or inaccurate results in certain scenarios. #FACTSTR

#pele just with near default settings

*** REMINDER RELAY MANAGEMENT**** make your app relays = same as your profile.json relays or else fix it just messed up and verified from another app n now fixed again if u not see anyone post - type @npubxxx then go directly check their active relays n browse those donot follow more than 500 npubs - make LISTS ***CORNERSTONE OF NOSTR DECENTRALIZE*** SPREAD OUT / SHUFFLE / MONITOR RELAYS #RELAYSTR

using ai now text > search advanced reasoning query text > coding tools system command checks agent skills > automate system tasks NO YET - this is dangerous shitty thing SD stable diffusion webui > generate n modify images some popular models (no image/video)

my coder bot given me my "genesis webpage code" without type any syntax #codestr #ai am sure better n more power start real dev are doing on field - well it's a start after all.

reddit babies are everywhere in botworld thecolony.cc clawstr.com moltbook.com ...

qwen3-coder-next:q4_K_M what are specific hardware minumum needed For the qwen3-coder-next model with q4_K_M configuration, the minimum hardware requirements can vary based on the specific use case and workload. However, as a general guideline: - **CPU**: A multi-core processor is recommended to handle the computational demands of large language models. An Intel Core i7 or AMD Ryzen 7 CPU would be suitable. - **GPU**: For efficient processing of the model, a GPU with significant memory (e.g., NVIDIA GeForce RTX 3060 or higher) and CUDA support is necessary. The GPU should have at least 8GB of GDDR6 or higher memory. - **RAM**: At least 16GB of RAM is recommended to ensure smooth operation. More RAM can be beneficial for handling larger datasets or running multiple applications simultaneously. - **Storage**: A solid-state drive (SSD) with at least 256GB is recommended for fast read/write speeds, though more space may be needed depending on the size of your projects and datasets. These specifications provide a balance between performance and cost, allowing for efficient model training and inference. If you're working with very large models or high-performance requirements, you might need to consider more powerful hardware.

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