Answer:
Ethics in artificial intelligence and robotics are of greater importance today as machine learning or robots are put to use to benefit humans and also ti harm humans.
Explanation:
Ethics in robotics or artificial intelligence in sometimes referred to as "roboethics". It is very necessary in todays time because robots are made to interact with the society, the humans.
This is the key concern for ethics which is based on growing awareness of the requirement to regulate, the advancements in the field of AI in the near future. The future law or regulations should be on the basis of some of the shared values such as privacy, freedom, security, respect for human dignity, non - military, inclusions, etc. Here, the uncertainty is also being recognized, the uncertainty to know the advancements of AI in the near future. Therefore the regulations and ethical dilemmas should be rethought in the middle.
Answer:
There are many types of information al references such as Encyclopedias, dictionaries, thesaurus Almanacs, atlases, thesauruses, Atlases, almanacs, and encyclopedias.
Explanation:
There are also informational websites. The way to find this is to look at the website url to see if it ends in .gov, .edu, and .org . But make sure you cite your source so you don't plagiarize.
If you don't have any questions feel free to ask in the comments.
Answer:
numbers = 1:1:100;
for num=numbers
remainder3 = rem(num,3);
remainder5 = rem(num,5);
if remainder3==0
disp("Yee")
else
if remainder3 == 0 && remainder5 == 0
disp ("Yee-Haw")
else
if remainder5==0
disp("Haw")
else
disp("Not a multiple of 5 or 4")
end
end
end
end
Explanation:
- Initialize the numbers variable from 1 to 100.
- Loop through the all the numbers and find their remainders.
- Check if a number is multiple of 5, 3 or both and display the message accordingly.
Answer:
import numpy as np
def sample_median(n, P):
return np.median( np.random.choice ( np.arange (1, len(P) + 1 ), n, p = P ) )
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(5, [0.3,0.7])
print(sample_median(5, [0.3,0.7])
Explanation:
- Bring in the numpy library to use the median function provided by the numpy library.
- Define the sample_median function that takes in 2 parameters and returns the median with the help of built-in random, choice and arrange functions.
- Call the sample_median function by providing some values to test and then display the results.
Output:
4.5
4.0
2.0
1.0