MENU
Which factor of a Waterfall' approach is most likely to result in the failed delivery of an Al project?
Suggested Answer: D
Get Premium AIF Questions
as Interactive Web-Based Practice Test or PDF
Real Exam Format
Detailed Explanations
Instant Access
Get Your Practice Test
Healthcare can benefit from AI, and in particular Machine Learning, in a number of ways. One example is diagnostic image analysis, which can help to automatically identify and classify abnormalities in medical images such as X-rays, CT scans, and MRI scans. Machine Learning algorithms can be used to detect patterns in the data which can be used to accurately diagnose diseases and illnesses.
29 comments · newest first
DO
Dorthy
11 months ago
I disagree, A isn't as critical as the others.
KI
Kiley
11 months ago
C isn't great, but B is worse for team dynamics.
AN
Annice
12 months ago
Surprised that people overlook A, it really drags everything down!
PH
Phil
12 months ago
I think D is the real issue, can't adapt if you can't revise.
CH
Chandra
1 year ago
Definitely B, lack of collaboration kills projects.
JO
Josefa
1 year ago
I thought option A was significant too, but now I'm leaning towards option D since it really restricts flexibility in the project.
KE
Kenda
1 year ago
I feel like all these factors could lead to failure, but I vaguely recall that taking too long in the design phase (option C) can also be a big problem.
CH
Cherrie
1 year ago
I'm not so sure about that. I remember a practice question where option D was highlighted as a major issue because it prevents necessary adjustments.
HE
Helga
1 year ago
I think option B might be the right choice since the Waterfall model can really limit communication between teams.
MU
Muriel
1 year ago
The longer delivery time for all requirements is a concern, but I think the lack of collaboration is the biggest red flag here. AI projects need that cross-functional teamwork to be successful.
TA
Tawanna
1 year ago
Hmm, I'm not sure. The longer design phase could also be a big problem, since AI projects often need to be more flexible and responsive to changing requirements.
MI
Michel
1 year ago
I think the key factor here is the lack of collaboration and cross-boundary communication in a Waterfall approach. That's likely to be the biggest issue for an AI project, which requires a lot of iterative work and input from different teams.
QU
Queenie
1 year ago
I'd go with option D - discouraging revisiting and revising prior phases. That rigidity is really going to hold back an AI project, which needs to be able to adapt and iterate.
JA
Janine
1 year ago
Hmm, I'm a bit confused on this one. I know there's a command to save without exiting, but I can't remember the exact syntax. Maybe I should review the Vim cheat sheet before the exam.
MA
Maurine
1 year ago
Based on my understanding, exceptions in IBM RPA are when the script stops processing due to an issue, like the vault not being open or the server running out of memory. I think option B or D might be the best answer.
SH
Shawnta
2 years ago
Trying to use a waterfall approach for an AI project is like trying to herd cats. Option D is the only sane choice.
DA
Daniela
1 year ago
Lorrine: Definitely, no room for going back and forth.
MI
Mica
1 year ago
User 3: It's important to stick to the plan in a waterfall approach.
LO
Lorrine
1 year ago
User 2: Yeah, once you move on, you can't go back.
LA
Laquanda
2 years ago
User 1: I agree, option D is the way to go.
GI
Gilbert
2 years ago
Waterfall and AI? Might as well try to teach a dog how to do calculus. Option D is the only way to go, my friends.
CL
Clay
2 years ago
Waterfall and AI? That's like putting a square peg in a round hole. Option D is the only sensible choice here.
JO
Jolanda
2 years ago
I agree, the waterfall model's rigid nature is not well-suited for the iterative nature of AI development. Option D is the way to go.
WY
Wynell
1 year ago
User 2: I agree, once a phase is complete, it's hard to go back and make changes.
CA
Carlene
2 years ago
User 1: I think option D is the key factor for failed delivery in AI projects.
NI
Nilsa
2 years ago
The waterfall approach's lack of flexibility and inability to revisit prior phases is definitely the biggest issue for an AI project. Option D is the clear winner here.
ME
Melissa
2 years ago
That's a good point, Cheryll. Collaboration is key in any project, especially in AI where different expertise is needed.
CH
Cheryll
2 years ago
I disagree, I believe it's B) Discourages collaboration and cross boundary communication. Without proper communication, the project can easily go off track.
ME
Melissa
2 years ago
I think the factor that is most likely to result in the failed delivery of an AI project is D) Discourages revisiting and revising any prior phase once it is complete.