At the upcoming #GlobalIndiaAISummit 2024, organized by @GoI_MeitY
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@alpanrav
, Chief Scientist AI/ML–will discuss our solutions in the tuberculosis cascade of care during the “IndiaAI: Real-world AI Solutions,” session on July 3, 2024. Register here https://
indiaai.gov.in/globalindiaais
ummit/form
…
RESEARCH
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AI Solutions for Tuberculosis Care at Global India Summit
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Optimizing LoRA Training: Rank and Step Count Adjustments
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you can also try adjusting the training settings with a different lora rank or step count. it's a tricky balance depending on the training set.
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Reducing Concept Strength to Prevent Overfitting
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Lowering concept strength to something like 0.2 when generating tends to reduce overfitting
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AI Disinformation: Balancing Innovation and Truth Protection
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@WEF_Unofficial article "Stopping AI Disinformation: Protecting Truth in the Digital World" addresses AI's dual role highlighting the innovations AI brings and the significant challenges it poses. While it amplifies disinformation through synthetic content, it also holds promise
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H100 GPUs Named After Grace Hopper, Computing Pioneer
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H100s are named after Grace Hopper, computer scientist and US navy rear admiral. She invented the first computer compiler, with the belief that programming should be English-based. "So I decided data processors ought to be able to write their programs in English, and the
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Sakana AI Hiring for Evolutionary Computing and Foundation Models
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Sakana AIは採用しています！
進化的計算と基盤モデルの更なる発展を自ら切り開きたい方は、当社の募集要項をご覧ください。 -
Amazon Proposes New AI Benchmark to Measure RAG
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Amazon proposes a new AI benchmark to measure RAG Choosing the right algorithm for RAG could yield more AI improvements than scaling to larger and larger language models, say AWS researchers. https://
zdnet.com/article/amazon
-proposes-a-new-ai-benchmark-to-measure-rag/
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LLM Captions for Text-to-Image Diffusion Model Training
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I took the liberty of asking Copilot, and it answered the following: “Let’s explore the interplay of data processing inequality, rate distortion, information bottlenecks, and representation in the context of using synthetic captions from LLMs to train a text-to-image diffusion
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Language Models Image Captioning with LLM Evaluation Filtering
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And this is what a typical LM does for captioning the same image. It’s not perfect but it is more scalable and detailed. With some LLM eval filtering would look even better.
