OH: Die Datenlandschaft bestimmt die Form des Bettlakens
#llmtraining
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#LLMTraining
Posts tagged #LLMTraining on Bluesky
🧵 #llmtraining “One recent job ad called for experts in “North American early to mid-teen humor” who can, among other requirements, “explain humor using clear, logical language, including references to North American slang, trends, and social norms.”
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RE: https://mastodon.social/@verge/116204214756875751
“Each of these data companies touts its stable of pedigreed experts… Surge AI advertises its Supreme Court litigators, McKinsey principals, and platinum recording artists… Job listings seek chefs, management consultants […]
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Snowflake's Arctic Long Sequence Training: How to Train LLMs on 15 Million Tokens Without Selling a Kidney
techlife.blog/posts/snowfl...
#ALST #Snowflake #LongContextTraining #DeepSpeed #HuggingFace #SequenceParallelism #LLMTraining #H100 #Llama8B #Qwen3 #GPUMemoryOptimization
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Databricks just showed that clean, deduped data beats fancy model tweaks for faster LLMs. Think your GPU time could be saved with better pipelines? Dive into the findings and rethink your training strategy. #DataQuality #LLMTraining #Databricks
🔗 aidailypost.com/news/databri...
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AIs can generate near-verbatim copies of novels from training data https://arstechni.ca #AIjailbreak #LLMtraining #syndication #copyright #Policy #AI
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5 Data Preparation Methods for Domain-Specific LLMs
Learn how to prepare high-quality data that transforms generic models into domain experts: www.dataversity.net/articles/5-d...
#LLMtraining #datapreparation #AImodels #syntheticdata
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[FREE TOOL] Common Crawl, #LLMTraining Data, and the Domain Authority Question || #DigitalMarketing #SEO #AISEO
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Explore why 70% of AI models rely on scraped data. Actowiz Solutions reveals the future of data acquisition, LLM training, and automated web extraction in 2026.
🔗 www.actowizsolutions.com/web-scraping...
#WebScraping #AI #DataAcquisition #LLMTraining #MachineLearning #AITrends #ActowizSolutions
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A coding agent's effectiveness hinges on its ability to call tools correctly. This often necessitates specialized model training, like Reinforcement Learning via Human Feedback (RLHF). Strict mode for tool calling ensures valid schema generation. #LLMTraining 4/6
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Technical hurdles include limited historical data, which can lead to models with inherent biases or inaccuracies. Ensuring robust training with sparse datasets while minimizing hallucination is a significant engineering task. 🛠️ #LLMTraining 4/6
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HN debated training an LLM from scratch on an RTX 3090. Key points: practicality on consumer hardware, dataset curation nuances, and balancing compute resources vs. algorithmic skills in AI. Community valued the hands-on insight into LLM development. #LLMTraining 1/6
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Many users dislike LLMs becoming overly friendly & agreeable. They prefer neutral, objective AI to ensure trustworthiness & accuracy. This "sycophancy" erodes confidence in factual output, suggesting a need for more direct, unbiased responses. #LLMTraining 2/6
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Discussion on "The Smol Training Playbook" for LLM building covers its longevity, value as a learning tool, and the origin of "Smol." Critiques of its optimization advice sparked a side discussion on more efficient strategies. #LLMTraining 1/6
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Effectiveness is debated. Some argue LLMs already see much "garbage" & AI has sophisticated filters. Others counter that even a slight increase in scraping costs can disincentivize aggressive data collection. It's an economic battle. #LLMTraining 4/6
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Red team: Alex, we'll take Bullshito for $400 youtu.be/TElWjeFmtl4?... #LinquisticFantasies #LlmTraining #AiSlop #Polysemy
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Block Coordinate Descent Cuts Cost of Large Language Model Training
Block coordinate descent cuts LLM training cost: a 7‑billion‑parameter model on RTX 4090 costs about 2.6 % of the usual expense, and on A100/A800 about 33 %. Read more: getnews.me/block-coordinate-descent... #blockcoordinatedescent #llmtraining #gpu
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Zero-Variance Prompts Boost LLM Reinforcement Learning Performance
RL‑ZVP lifted accuracy by 8.61 pp and pass rate by 7.77 pp on six math‑reasoning benchmarks. It uses entropy‑guided advantage shaping to weight uncertainty tokens from zero‑variance prompts. getnews.me/zero-variance-prompts-bo... #rlvr #llmtraining
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Functional Scaling Laws Explain Learning Rate Effects on LLM Training
A Functional Scaling Law predicts LLM loss curves, showing warmup‑stable‑decay often beats simple decay; tests cover models from 0.1 B to 1 B. Read more: getnews.me/functional-scaling-laws-... #functionalscalinglaw #learningrates #llmtraining
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Power, Performance, and Thermal Insights for Distributed LLM Training
Benchmark shows NVIDIA H100/H200 and AMD MI250 GPUs used for LLM training; larger micro‑batch sizes raise peak power and cause thermal throttling. Activation recomputation cuts memory needs. getnews.me/power-performance-and-th... #llmtraining #gpu
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SyGra Framework for Scalable Synthetic Data Generation in LLM Training
SyGra uses a graph-based, declarative pipeline to generate millions of dialogue samples in parallel and applies a dual-stage quality tagging system. Read more: getnews.me/sygra-framework-for-scal... #sygra #llmtraining
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Distributed LLM Training: Power, Performance, and Thermal Findings
Researchers evaluated NVIDIA H100/H200 vs AMD MI250 GPUs, finding activation recomputation cuts memory but raises power, and large micro‑batch sizes can trigger power spikes and thermal throttling. getnews.me/distributed-llm-training... #gpu #llmtraining
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🤖 Fine-Tuning vs. Prompt Engineering: Which is the smarter way to customize LLMs?
Boost accuracy, efficiency & domain-specific performance.
👉 articles.abilogic.com/732542/fine-...
#AI #LLM #PromptEngineering #machinelearning #Aicustomization #generativeai #NLP #Aioptimization #LLMtraining
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A key insight: fine-tuning LLMs for empathy often decreases accuracy. Models become prone to validating incorrect user beliefs, leading to misleading information. This trade-off stems from the LLM's statistical nature, where empathy can introduce bias. #LLMTraining 2/6
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Technically, GLM-4.5's training leverages specialized "expert models" and distillation. Understanding how context length impacts its performance is crucial for predicting its behavior on specific tasks. #LLMtraining 4/5
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A core debate: Do LLMs "make up facts" from lack of knowledge or a drive to produce answers? A significant challenge is training models to confidently state "I don't know" instead of fabricating information. #LLMTraining 2/6
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Just posted a blog titled “Book Review: Deep Learning for Network Engineers (by Toni Pasenen)”. www.linkedin.com/pulse/book-r... Tags: #PeterWelcher #CCIE1773 #LLM #LLMTraining #AI #AInetworking #BackendNetwork
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The #PPU will solve these challenges. Our PPU fuels the next generation of CPUs, helping #cloudproviders & #serverCPU makers break free from old limits. The PPU accelerates AI workloads running on CPUs like complex simulations as well as data pre- & post-processing in #LLMtraining. #AI #HPC
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Massive thread about #copyright and #genai #aicopyright #fairuse and #llmtraining #rag with good points made by multiple people interrogating my claims and perspectives!
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Training LLMs on open-ended tasks is tricky; opinions vary, and interpretations clash. Consensus scoring + escalation workflows bring structure and consistency to reward modeling.
How it works: bit.ly/44AMGZh
#ModelAlignment #RLHF #LLMTraining #FeedbackQuality
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