Read more in our launch blog post: https://
blog.google/products/gemin
i/gemini-2-5-pro-latest-preview
… And please keep the feedback coming!
LLMS
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Google Launches Gemini 2.5 Pro Latest Preview
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Gemini 2.5 Pro update achieves SOTA performance with thinking budgets
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Introducing our latest update to Gemini 2.5 Pro (06-05), which we expect to become our long term stable release. At a glance: – SOTA on HLE, Aider, and GPQA
– Now supports thinking budgets
– Same cost, on pareto frontier
– Closes gap on 03-25 regressions -
Fine-tuning GPT-2: When LLMs Aren’t Necessary for ML
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After playing with fine-tuning gpt-2 for some simple classification tasks, my honest take is that for most *supervised* ML projects you really, really, really don’t need the LLMs. For simple image/text/signal problems use a pre-trained nn, such as one of the deep NNs trained on
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Software Inertia and LLM Adaptation: UI Automation vs Legacy Systems
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Imo you are also dramatically under-estimating inertia, including in Software (e.g. see pervasive use of COBOL to this day). The more general formulation looks something like this. Do LLMs adapt to all existing software? (e.g. Operator seeing UI screens, making clicks)
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Pretraining: The Beautiful Art of Learning to Compress Knowledge
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pretraining, the act of learning-to-compress the entirety of human knowledge and thereby creating a general-purpose model that can simulate any natural process, is really a beautiful learning paradigm. everything is just going to get messier & more complicated from here
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Live Webinar: Interpreting LLMs with DLBacktrace Technology
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🔴 We're Live! Join our webinar: Inside the Black Box – Interpreting LLMs with DLBacktrace (DLB) by AryaXAI 🧠 Model reasoning beyond attention 📊 Benchmarking insights 🎙️ Live Q&A Jump in: 🔗 Zoom Link: hubs.la/Q03qTnK_0 #AI #LLMs #Explainability #DLBacktrace
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CapSpeech: Open-Source Pretraining Dataset and Models
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CapSpeech is a fully open-source project for academic use, offering a large-scale pretraining dataset, high-quality fine-tuning subsets, & pretrained models.
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Qwen unveils new high-performance multilingual embedding standard
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Qwen silently dropped the new standard for embeddings on the Hub!
– 0.6B, 4B and 8B versions (probably would use only the 0.6B)
– 32k context length – 100 languages – SOTA on MTEB, but like real SOTA, with 10 points margin on the second bests https://
x.com/tomaarsen/stat
/tomaarsen/status/1930579927020994694
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Potential Impact of Sora Integration into Microsoft Bing
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This is the real unlock, zero onboarding, mobile-first, no cost. Sora inside Bing might be Microsoft’s next $100B ecosystem play.
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Using LLMs to accelerate academic research workflows
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Try this prompt on your current topic. Test it in 3 LLMs. Watch how much faster your research moves. Save this thread if you're a student, PhD, or academic researcher.