Title

Introduction¶

Explicity mention the topic you chose. Add a brief discourse of why your chosen topic is of interest to you. Discuss what you perceive as the historical and future importance of the topic.

You may choose one of the following topics, or a different topic of particular interest to you.

• AI for predicting forest fires
• Gender bias in machine learning datasets
• Racial bias in hate speech detection models
• Impact of AI on labor, such as how automation can replace human workers
• AI for smart energy systems
• AI in autonomous vehicles
• AI in security and surveillance, such as object detection, event detection, face detection
• AI in sports analytics, such as automated journalism, wearable tech, strategic game planning, injury management
• AI in Healthcare and Medical Imaging Analysis, such as diagnosis of neurological conditions, cancer screening, identifying cardiovascular abnormalities
• AI in agriculture, such as precision agriculture
• AI in retail, such as virtual fitting rooms, prediction of demand

Very briefly mention the three papers you selected and why. Highlight the research questions posed in the papers, and the objective goals of the research. What is the impact of solving the research problems that are common across the papers?

Here is an example of how to cite an item in your list of references that must appear at the end of this document: The AI field includes a variety of search algorithms [Russell and Norvig, 2010]. Perhaps some of these search algorithms could be used to support critical decision makers [Trump, et al., 2020].

Analysis of Papers¶

For each paper:

• Explain your personal understanding of the methods and approaches used. Do not quote verbatim from the paper.
• Discuss your opinion of how well the methods achieved the goals of the paper.
• Describe which parts of the paper are the most difficult to understand and what aspects of the methods are not specified with sufficient detail to allow the reader to write their own implementation.

Compare the papers by describing similarities and/or differences in the goals, methods, and results of the papers. As an optional addition to this section, discuss which presented methods you think would be most easily combined and/or translated to real-world applications.

Issues and Challenges¶

What are the major issues and challenges present across all methods in the papers? When presenting an issue/challenge, give examples based on the methods which have those issues. Speculate on possible ways to deal with them.

Conclusion¶

Give your opinion of how well the work presented in the collection of papers have advanced the state-of-the-art in their field. What remaining issues must be addressed in future work to make further significant advances?

References¶

[Russell and Norvig, 2010]: S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 3rd Edition, Pearson, 2010

[Trump, et al., 2020]: D. Trump, D. Trump, Jr., E. Trump, I. Trump, All in the Family, White House Publications, 2020.

In [15]:
import io
import nbformat
import glob
nbfile = glob.glob('A8 Report Template.ipynb')
if len(nbfile) > 1:
print('More than one ipynb file. Using the first one.  nbfile=', nbfile)
with io.open(nbfile[0], 'r', encoding='utf-8') as f:
word_count = 0
for cell in nb['cells']:
if cell.cell_type == "markdown":
word_count += len(cell['source'].replace('#', '').lstrip().split(' '))
# print(cell['source'], word_count)

print(f"Word count for file '{nbfile[0]}' is {word_count}.\n")

if word_count < 2000:
print('Your report does not have enough words!'.upper())
elif word_count > 4000:
print('Your report has too many words.  Rewrite some sections more concisely.'.upper())
else:
print('Your word count satifies the requirements.')

Word count for file 'A8 Report Template.ipynb' is 530.

YOUR REPORT DOES NOT HAVE ENOUGH WORDS!