ENH: pd.cut should be able to return a Series of IntervalDtype
#### Code Sample, a copy-pastable example if possible

```python
In [1]: import pandas as pd

In [2]: import random

In [3]: df=pd.DataFrame({'x': [random.randint(0,10) for i in range(100)]})

In [4]: pd.cut(df.x, [2*i for i in range(6)])
Out[4]:
0      (6.0, 8.0]
1             NaN
2      (0.0, 2.0]
3      (2.0, 4.0]
4      (0.0, 2.0]
         ...
95    (8.0, 10.0]
96     (2.0, 4.0]
97    (8.0, 10.0]
98     (0.0, 2.0]
99    (8.0, 10.0]
Name: x, Length: 100, dtype: category
Categories (5, interval[int64]): [(0, 2] < (2, 4] < (4, 6] < (6, 8] < (8, 10]]



```
#### Problem description

By default, the return type of `pd.cut` is categories, but we know we are creating intervals, so shouldn't it be `IntervalDtype` ?

#### Expected Output
```python
In [5]: pd.cut(df.x, [2*i for i in range(6)]).astype('Interval')
Out[5]:
0      (6.0, 8.0]
1             NaN
2      (0.0, 2.0]
3      (2.0, 4.0]
4      (0.0, 2.0]
         ...
95    (8.0, 10.0]
96     (2.0, 4.0]
97    (8.0, 10.0]
98     (0.0, 2.0]
99    (8.0, 10.0]
Name: x, Length: 100, dtype: interval
```

IMHO, I shouldn't need to do the 'astype('Interval')`

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.0.0
numpy            : 1.17.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 42.0.2.post20191203
Cython           : None
pytest           : 5.3.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.2.6
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.11.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.3.2
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : 1.2.6
numba            : None

</details>
