More than anything: Advocating for synthetic architectures within large-scale language-image models

Describing Framework Architectures : more than

In this paper we argue for the necessity of an architectural description of a framework. We then analyze why design patterns on their own are insuucient for such a description and propose that a variety of complementary forms of documentation are needed to address the requirements of an architectural description. We claim that traditional artifacts of domain analysis and object-oriented design ...

After more than a decade, has pet guardianship changed anything?

Large Scale Hierarchical Neural Network Language Models

Feed-forward neural network language models (NNLMs) are known to improve both perplexity and word error rate performance for speech recognition compared with conventional ngram language models. We present experimental results showing how much the WER can be improved by increasing the scale of the NNLM, in terms of model size and training data. However, training time can become very long. We imp...

Can an ensemble give anything more than Gaussian probabilities?

Can a relatively small numerical weather prediction ensemble produce any more forecast information than can be reproduced by a Gaussian probability density function (PDF)? This question is examined using site-specific probability forecasts from the UK Met Office. These forecasts are based on the 51-member Ensemble Prediction System of the European Centre for Medium-range Weather Forecasts. Veri...

Does Biosynthetic Silver Nanoparticles Are More Stable With Lower Toxicity than Their Synthetic Counterparts?

Control of size and shape is a challenge in nanoparticle synthesis. Synthetic and biosynthetic (both extracellular and intracellular) methods are used to prepare silver nanoparticle (SNP). In this study, the behavior of three strains of Staphylococcus aureus (S. aureus) was investigated in the presence of silver nitrate intra- and extracellularly. S. aureus strains biosynthesized SNPs intracell...