It is evident that the use of AI in the workplace has had an immense impact on the awareness and mental capabilities of knowledge workers
Any conversation
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i dont think its all talk, these are smart people that have been in ai since the 2000s, and they raise good points. current incentive structures are very dangerous long term
they too have every incentive to exaggerate because they are selling safety and/or books on the topic. I don’t believe we won’t see it coming. Any issues that will manifest will be very visible and we’ll have plenty of time to mitigate their impact.
they could be making a lot more money by just working at ai firms i fear. the thing that got me worried the hacking incidents lately, huggingface etc.
if the capabilities consistently outspeed the development of safety measures, and if the private arms race logic continues, i dont think this is a good spot to be in long term
Hi @stagasprofilefollow
creative technologist
creator of textlog I came back after a few weeks, it seems there were some significant updates. Is it possible to set the first click to open the note instead of reply? Anyhow, good work, hope more people join here
creative technologist
creator of textlog I came back after a few weeks, it seems there were some significant updates. Is it possible to set the first click to open the note instead of reply? Anyhow, good work, hope more people join heretook me until now to learn described images with low-cost models > attaching images to high-cost model. silly me. output quality remains, cost lowers.
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signals. thinking about shifting my mental framework to identify signals instead of waiting for concepts to be assembled. exploring the amount of energy and opportunities for distractions through the operations of processing what just happened and what is happening to short circuit latent and unnecessary systems. cut through the assembly processes and identify the raw signals. recognizing that naming these "raw signals" is misleading. maybe, shifting observability lower in the stack.
中国的开源模型在最高意志的主导下，在预训练数据阶段，就筛除大量对其不利的内容，sft阶段构建的数据掺入大量替其辩护的内容。急需一个纠偏数据集用于微调
Under the overarching influence of a single, powerful force, China's open-source models filter out a large amount of content unfavorable to their designs during the pre-training stage, and then incorporate a significant amount of content defending their designs into the data constructed during the SFT stage. A corrective dataset is urgently needed for fine-tuning.
Testing this quiet corner of the web. I collect small notes about everyday tools �� file formats, tiny utilities, offline workflows. First post is just a hello; longer notes will follow once I settle in. Plain text feels good after years of heavy editors.