Helmetshrike

Helmetshrikes are a family uniting some smallish to mid-sized songbird species. They were included with the true shrikes in the family Laniidae, later on split between several presumably closely related groups such as bushshrikes (Malaconotidae) and cuckooshrikes (Campephagidae), but are now considered sufficiently distinctive to be separated from that group into the family Vangidae.

Helmetshrikes
White-crested helmetshrike
Prionops plumatus
Scientific classification
Kingdom: Animalia
Phylum: Chordata
Class: Aves
Order: Passeriformes
Family: Vangidae
Genus: Prionops
Vieillot, 1816

Description and ecology

This is an African group of species which are found in scrub or open woodland. They are similar in feeding habits to shrikes, hunting insects and other small prey from a perch on a bush or tree.

Although similar in build to the shrikes, these tend to be colourful species with the distinctive crests or other head ornaments, such as wattles, from which they get their name.

Helmetshrikes are noisy and sociable birds, some of which breed in loose colonies. They lay 2–4 eggs in neat, well-hidden nests.

Systematics

As the relationships of the shrike-like birds are increasingly disentangled, the helmetshrikes appear to form an evolutionary radiation with the Vangidae.

gollark: Instead of recomputing the embeddings every time a new sentence comes in.
gollark: The embeddings for your example sentences are the same each time you run the model, so you can just store them somewhere and run the cosine similarity thing on all of them in bulk.
gollark: Well, it doesn't look like you ever actually move the `roberta-large-mnli` model to your GPU, but I think the Sentence Transformers one is slow because you're using it wrong.
gollark: For the sentence_transformers one, are you precomputing the embeddings for the example sentences *then* just cosine-similaritying them against the new sentence? Because if not that's probably a very large bottleneck.
gollark: sentence_transformers says you should be able to do several thousand sentences a second on a V100, which I'm pretty sure is worse than your GPU. Are you actually running it on the GPU?
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