workslop ain’t work. accountants dont last long if they make errors.
LLMS
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X/Twitter Post Mentions xAI’s Grok-4 Model
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Some guy generalized from a single (and impossible) example of teacher incompetence to produce the most toe nail curling argument against tech in schools ever. Can we admit that teaching writing to humans was a bad idea?
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Top 6 Claude Code Skills for Newbies, Including Skill-Creator
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bro A new video just dropped, still super dry, still newbie-friendly, highly recommend it here, video link at the end. "I Tried Over 100 Claude Code Skills, These 6 Are the Best". 1. skill-creator Official from Anthropic, usage is straightforward to the max: Let Claude write
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Request for AI Model Traces and Hugging Face Model
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Could you share your traces and the resulting model on HF? Would be super interesting
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Dense Attention: A Technical Direction in AI Models
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All related to dense attention, can be considered the same direction, with the same approaches.
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LLM pricing per token mirrors SaaS era, buy a GPU
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Charging $ per 1M tokens
Is basically the SaaS era of LLMs That’s why I keep saying Buy a GPU -
Neurosymbolic AI Development with Logic, Calculus, and LLMs
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I create Neurosymbolic AI using first Oder logic and predicate calculus alongside our own agentic AI stack and LLMs. @pierrepinna
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Sparse Attention and Large Context Windows: An Industry Shift in AI Models
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确实很酷，拿 2900 万美金做 12M context，
— 艾略特 (@elliotchen100) 5 mai 2026
侧面证明了一件事：整个行业都开始相信稀疏注意力是 dense attention 的解药。
SubQ 走的是「重训一个模型」，属于垂直整合，风险大回报也大。@evermind 的 MSA 走的是「给主流模型加记忆」，属于 水平嵌入，谁的模型都能用。
另外，SubQ API 跟 SubQ… https://t.co/yZ8IugqquAYeah, that's pretty cool—using $29 million to build a 12M context window, which indirectly proves one thing: the entire industry is starting to believe that sparse attention is the antidote to dense attention. SubQ takes the "retrain a single model" approach, which is vertical