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Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model
The historically controversial (13) extent of mutual convergence in mimicry is illustrated by a detailed case study (Fig.
4) share a white hindwing marginal fringe and strong blue iridescence of the dorsal wing surface also present in their phenotypically closest conspecifics, H.
Both pattern features are likely to have been secondarily derived (rather than ancestral within each species) on the basis of gene phylogenies, biogeographic distribution, and phylogeographic reconstruction (12, 16, 26, 33).
This shared biogeographic history is also compatible with the potential for strict interspecies coevolution, since reciprocal evolutionary influence between two taxa requires that they co-occur in both space and time (26).
melpomene (34), subsequent genomic analyses (taking into account population sizes) have reconstructed their diversification over closely overlapping time ranges (28, 29).
melpomene have influenced each other (albeit to varying extents), with each species acting as both model and mimic to some degree, meeting the essential condition of strict reciprocal (13, 19) coevolution.
Left (A, D, and G): Mutual convergence in focal taxa (focal taxa, gray circles) with reciprocal transfer of pattern features (e.g., forewing band shape versus wing color) between two clades (1 and 2, respectively black versus gray outlines).
When expressed in terms of the phenotypic distance from the focal taxa (G to I), mutual convergence (G) is characterized by a decreasing distance along the arrow of evolutionary change in both clades.
DeepMind's Losses and the Future of Artificial Intelligence
DeepMind, likely the world’s largest research-focused artificial intelligence operation, is losing a lot of money fast, more than $1 billion in the past three years.
Certainly, genuine machine intelligence (also known as artificial general intelligence), of the sort that would power a Star Trek–like computer, capable of analyzing all sorts of queries posed in ordinary English, would be worth far more than that.
That technique combines deep learning, primarily used for recognizing patterns, with reinforcement learning, geared around learning based on reward signals, such as a score in a game or victory or defeat in a game like chess.
DeepMind gave the technique its name in 2013, in an exciting paper that showed how a single neural network system could be trained to play different Atari games, such as Breakout and Space Invaders, as well as, or better than, humans.
DeepMind’s StarCraft outcomes were similarly limited, with better-than-human results when played on a single map with a single “race” of character, but poorer results on different maps and with different characters.
(DeepMind’s recent results with kidney disease have been questioned in similar ways.) Deep reinforcement learning also requires a huge amount of data—e.g., millions of self-played games of Go.
technological human resources, on par with many other countries They said women are an indispensable component of the country's human resources in science and technology, and that encouraging more women to engage in basic research will help improve science education and scientific research.
Mathematics has long been viewed as a male-dominated discipline, but modern science has seen more female mathematicians contribute significant scientific breakthroughs, reshaping the gender structure.
She said women account for about 40 percent of China's scientific and technological human resources, on par with many other countries, but those who actually engage in cutting-edge scientific research or decision-making comprise an even smaller minority.
The guideline called mathematics the foundation of natural science and the development of major technological innovations, saying it supported a variety of important industries including national defense, biomedicine, artificial intelligence, energy and advanced manufacturing.
Li said women were not a minority in areas where fairness was a policy imperative, such as the national college entrance exam, and in many global sports events, but a survey of more than 6,000 women showed 32 percent had encountered a preference for men when seeking their first jobs.
makes rapid strides Li added that women also need to identify the roles they are playing in the development of the economy, politics, society and culture, besides in families.
- On 15. april 2021
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