To be honest I feel like it’s B that’s looks and seems the most correct to me
The definition according to google and the dictionary of technological singularity is the following : The technological singularity (also, simply, the singularity) is the hypothesis that the invention of artificial superintelligence will abruptly trigger runaway technological growth, resulting in unfathomable changes to human civilization.
The dangers this brings to man kind is the fact that people will turn out to not be people or there may be a different species considered as humans or human kind .Also we were made as humans from something else artificial super intelligence will basically be forming from us which means it will be forming from something that was already mean basically meaning there will be something changed within the species or artificial super intelligence itself.
Answer:
def feet_to_inches( feet ):
inches = feet * 12
print(inches, "inches")
feet_to_inches(10)
Explanation:
The code is written in python. The unit for conversion base on your question is that 1 ft = 12 inches. Therefore,
def feet_to_inches( feet ):
This code we define a function and pass the argument as feet which is the length in ft that is required when we call the function.
inches = feet * 12
Here the length in ft is been converted to inches by multiplying by 12.
print(inches, "inches")
Here we print the value in inches .
feet_to_inches(10)
Here we call the function and pass the argument in feet to be converted
Answer:
Each time you insert a new node, call the function to adjust the sum.
This method has to be called each time we insert new node to the tree since the sum at all the
parent nodes from the newly inserted node changes when we insert the node.
// toSumTree method will convert the tree into sum tree.
int toSumTree(struct node *node)
{
if(node == NULL)
return 0;
// Store the old value
int old_val = node->data;
// Recursively call for left and right subtrees and store the sum as new value of this node
node->data = toSumTree(node->left) + toSumTree(node->right);
// Return the sum of values of nodes in left and right subtrees and
// old_value of this node
return node->data + old_val;
}
This has the complexity of O(n).
Explanation:
