Remove research scale-em
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Elon Musk wants to merge humans with AI. How many brains will be damaged along the way?

Flipboard

The plan is basically: If you can’t beat ’em, join ’em. In recent years, a lot of the research that’s made headlines has focused on brain implants that would translate paralyzed people’s thoughts into speech. So is the US military. Soon Nagle was playing Pong using only his mind. The company isn’t saying.

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Google at ICML 2023

Google Research AI blog

Posted by Cat Armato, Program Manager, Google Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. As a leader in ML research, Google has a strong presence at this year’s conference with over 120 accepted papers and active involvement in a number of workshops and tutorials.

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LLM Fine-Tuning and Model Selection Using Neptune and Transformers

The MLOps Blog

Given this context, a team of researchers proposed a new technique called Low-Rank Adaptation (LoRA). compute_metrics`: Evaluates a model on a dataset, calculating exact match (EM) and F1 scores. For the EM score, it decodes these predictions and labels into text and computes the EM score. join(em_ref)) em=metric1.compute(predictions=em_preds,

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AI Use Cases for Cyber and Malware Analysts

DataRobot

SOREL-20M is a large-scale dataset of 20 million files. SoReL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection , R Harang, EM Rudd – arXiv preprint arXiv:2012.07634, 2020. Free Malware Sample Sources for Researchers , Accessed on May 2, 2021. Background on Cybersecurity. References.

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The Market for Lemons

Hacker News

They understood the only way to scale JS-driven frontends are massive investments in controlling complexity, but warned none of their customers. This information asymmetry persists; the worst actors still haven't levelled with their communities about what it takes to operate complex JS stacks at scale.

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Machine Learning on Graphs @ NeurIPS 2019

ML Review

The model is trained using the variational EM algorithm (actually, there is also a surge in using EM for training & optimization in recent papers which deserves a separate article). Qu and Tang propose pLogicNet: a model for KG reasoning where KG embeddings are combined with logic rules. TransE or ComplEx, literally any will do).