Month: July 2024

Reflection

Was the result relatively accurate in your estimation?

Arriving at this task, I have never used Craiyon before. I found the site easy to use but very slow on my computer which rarely ever happens. The generated images, although original. Seemed to lack a lot of detail and the prompting never really seemed to help the quality improve. The AI struggled with the details of the image and wasn’t able to match my instruction, such as accurately creating a dog wearing a red cape or creating a realistic human face. This does seem to be a common limitation of AI image generators that I have used. The AI always seems to produce variations that are close but not exactly what I envisioned.

Were those images what you had in mind when you gave the AI the prompts?

The images definitely did not meet my expectations. The AI’s interpretation of “a dog wearing a red cape” resulted in various red clothing items instead of a consistent cape. Similarly, the human face distortion indicates that the AI might not be adept at generating realistic human features, especially in dynamic poses like jumping when I entered the prompt to “create a man who has just graduated from his masters program at the university of british columbia jumping up in the air on campus, excited to be all done.”

What differed?

The main differences were:

• Inconsistent Details: The AI generated different red clothing items instead of a specific red cape. I assumed that a cape would be a specific enough type of garment that the AI would be able to produce.
• Distorted Human Features: The AI struggled with creating a realistic human face, particularly in an action pose. The images were mostly headshots of men smiling or graduation related images that didn’t fit my request.

What can you infer about the model or the training data based on the results?

These inconsistencies may suggest that the AI model might not have been trained on enough diverse and high-quality images of the specific scenarios that I requested. Perhaps this AI tool, Craiyon, relies on patterns and previously requested images to learn and improve. If Craiyon hasn’t seen requests like mine such as dogs in capes or people jumping in specific contexts, perhaps Craiyon struggled to produce original accurate pictures. The article from Vox highlights similar limitations of AI-generated images. It mentions that while AI models like DALL-E can create impressive visuals, they often fall short in generating detailed and accurate representations, especially for complex or specific prompts (Heilweil, 2022). This aligns with my experience, where the AI’s output did not fully match my expectations. While I would conclude that AI image generators have made positive strides, they definitely still have limitations, especially with detailed and specific prompts. While the technology continually improves, it may require multiple banks of information and refinements to get closer to a desired outcome.

References

Heilweil, R. (2022, December 7). AI is finally good at stuff. Now

        what? Vox. https://www.vox.com/recode/2022/12/7/23498694/ai

artificial intelligence-chat-gpt-openaiLinks to an external site.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Well then… this made me feel foolish, or perhaps frustrated, or maybe annoyed, or I guess all of the above! Doing the exercise was actually fun as I found a lot of humour in it throughout the quiz. It is actually quite funny because I actually find myself very critical of website design on a regular basis and question the buttons and forms all the time. The design choices in this activity made it incredibly confusing. Reflecting on my own internet usage I can comfortably say that I have learned to click without usually thinking. In a sense, we rarely read the text on buttons and instead look for different things to click to make the process quicker. Clicking a box to say that we have agreed to something is a regular occurrence and looking for red or green click friendly icons is very common indeed. I feel that we have been conditioned to do these things and are now normalized so much so, that we forget that we are doing them. This quiz by User Inyerface does an amazing job of showcasing patterns and our habits of not reading and just clicking (Brignull, 2011). Usually, websites that are scams operate a lot like this and show these dark patterns even more so. I can recall many experiences where clicking on the ‘x’ to close a page sometimes begins a download or opens up an ad, much like this quiz did. Although there was definitely some humour involved in this quiz, the scary realities out there can be quite alarming. I have family members who have put in there email address or password to sites that are fake or that ask for information after announcing that you’ve won a free vacation. It can be quite a mess if you get caught in clicking without paying attention. The assignment did a wonderful job of showing these characteristics and teaching/reminding us a valuable lesson.

 

Reference

Brignull, H. (2011). Dark Patterns: Deception vs. Honesty in UI Design. Interaction Design, Usability, 338.

Upon completing the Golden Record assignment, the next step required my peers and I to take a quiz in an effort to gather data based on our song selections. Using the Palladio app, something that I have never done before, we were to interpret the collected data through a visual output, as shown below.

I am not going to lie; the program was instantly intimidating. Loading the file by following the instructions was manageable but the data was immense, just take a look at the above image. However, after discovering more about the program, using Palladio turned out to be very interesting and well worth the learning curve. The app made it fairly easy to somewhat interpret the data and see different connections amongst our group. It really was like reading a new language at times because of the complexity that it came with. I found it a lot easier when clicking the different facet options based on how the program divided the students of the course. Working with the smaller groups, I tried to spread out the MET students on the perimeter of the workplace and then see how the connections happened. Spreading out the lines as much as possible made it easier for me to understand and interpret the data. I untangled every group this way and also if any student was the only person to choose a song that song would be distanced away from the rest of the data.

First, I looked for the tracks that were original to the students. Out of five members of the group, all of them had chosen songs that the other’s had not. Four out of five chose two songs that were original to them. I found this interesting that while they share commonalities, they had different selections than the rest as well. I also noted that only one song was similar between them all which was Track 18: Fifth Sympathy which is a classical number that most likely found its way onto their lists because of how well it’s known to the rest of the world.

The group that I was part of was Group two, which I was typically most interested in when comparing as making assumptions related to myself is always more intriguing. Group two had one song in common which was Track 6: El Cascabel. It is such a vibrant, Mexican, feel good song that I believe definitely belonged in our playlists based on the way it makes you feel when listening to it. While three students had unique songs chosen only by themselves, I did not have a song that I only chose. Does this make me more predictable and less original? Maybe so, because when I noticed that some students did not select Johnny B Goode to be part of their selection, I was shocked (in a humourous way of course) that they would leave off such a classic. Based on how some of their songs were selected, I would infer that their choices were perhaps influenced by the cultural significance of the tracks, while my predictability perhaps landed more songs such as Johnny B Goode.

Only 4 students were part of the next group, a lot more manageable. The songs in common here were more apparent now but there were not a lot of original selections made. Some of the similar selections included Track 24: Flowering Streams, Track 14: Melancholy Blues, Track 10: Gavotte en rondeaux, Track 21: The Fairie Round and Track 7: Johnny B Goode. I find this group had a very good taste of uplifting and positive music as their commonalities were all solid choices.

Looking at Group four, I instantly noticed that Abdulehed had four tracks that only he selected. I find that the selections that were commonly chosen were all selected because of their great musicality and that Abdulhed had some great taste in cultural music. They did not have much in common at all which showed their unique musical senses.

The next group was very unique in that they each had three of their own choices and four similar selections. These three students chose the same songs that, once again, focused on the feel good musical aspects of the list. Positive and uplifting song choices continued to be selected by most students in the groups and I feel that they best represent our group as a whole as well as the entire human race.

Lastly, two students were very easy to interpret as Palladio makes it easy to see their five similar choices and their other differences as well. This was obviously the easiest to separate and spread apart while the others had some errors in my screenshots as well, noticing some songs in places that I should have moved them from.

Reflection

The assignment was one that I really enjoyed and felt that it provided culture and significance to the course. It also really got me thinking on a deeper level regarding perception and predictability. I really enjoyed trying to distinguish and interpret the data involved but also realizes that it was still hard to determine why songs were ultimately selected. I felt that Palladio did an excellent job of presenting the data in a way which could be manipulated to see more clearly.  The most difficult thing about the interpretation was constantly going back and forth to the song choices and re-listening before inferring why a song was selected, which was a tedious process. It would take a team to try and sort through this the proper way in the end.

I found it difficult to consider so many possibilities of song selection from what’s missing and why or why not songs were chosen. I could make assumptions but I do not feel as though other students may feel that is appropriate to do as personal preference is so unique to every individual. I could look at my own choices and question why others did not select the same songs as I did but the data would not be able to tell me this in the long run. Much like our digital footprint, we may be able to be interpreted and tracked from things in which we do or follow but why we make our choices and how they are grouped with the population is not up to us. It is simply impossible to assume data and we need to remember this always as we could be caught in certain situations grouping individuals based on selections that they make and not searching further.

 

This assignment was incredibly interesting. Discovering the existence of the Voyager Golden Records for me personally, was fascinating. The idea of sending a message from Earth out into the cosmos, intended for any potential extraterrestrial life, is both amazing and inspiring. It must have been a monumental task for Carl Sagan and the team to curate the content, meticulously selecting sounds and images that represent the diversity and essence of our planet. Reflecting on their effort, I can’t help but think about the choices they made and how I might have selected differently. If I were to choose only ten songs for the final draft, I would prioritize a broad spectrum of compositions, ensuring a wide range of representation from various cultures and musicians. This would highlight the rich artistry of human creativity and our peaceful intentions for whoever discovers the capsule. While I wouldn’t want to intimidate any extraterrestrial being, I would also love to demonstrate some of our powerful pieces in which shows our strength and the passion of a human being. The Voyager Golden Records stand as a testament to our desire to connect and share our story with the universe, symbolizing hope and curiosity. Definitely one of the assignments that I won’t forget.

My Top 10:

1. #6: Mexico, “El Cascabel,” performed by Lorenzo Barcelata and the Mariachi México. 3:14
Listening to this track, I feel that this fast-paced melody embodies passion, love, excitement and movement. I want to get up and dance when this sone hits and I feel it is critical to include this one in my top 10.

2. #7: “Johnny B. Goode,” written and performed by Chuck Berry. 2:38
Never mind the Golden Records, this is one of my favourite songs in general. Perfect to tap your foot to and smile while your frequency sparks with this classic number. Besides, anyone who finds these records needs to hear some iconic rock and roll.

3. #8: New Guinea, “Men’s House Song,” recorded by Robert MacLennan. 1:20
This song provides a very valuable perspective on our musical expression highlighting rich culture, different styles and a non-threatening and harmonious quality. I feel it represents a peaceful way about it when listening.

4. #9: Japan, shakuhachi, “Tsuru No Sugomori” (“Crane’s Nest,”) performed by Goro Yamaguchi. 4:51
As this might be the most relaxing number in the entire collection I feel that this track should absolutely be included in the medley. The fact that music like Yamaguchi’s number can evoke that feeling is truly worth it being on the final list.

5. #11: Munich, “The Magic Flute, Queen of the Night aria,” no. 14. Edda Moser, soprano. Composed by Wolfgang Amadeus Mozart. 2:55
I feel that Mozart, merely based on the fact that he is one of the most famous composers in history, should be able to showcase the intensity and storytelling to whoever may find this capsule. It will definitely be able to take someone on a thrilling ride demonstrating the capabilities of human creativity and heart.

6. #13: Peru, “Panpipes and Drum”, collected by Casa de la Cultura, Lima. 0:52
I feel that the panpipes and drum was also a fine piece of cultural representation and a different type of feel of music compared to the rest of the album’s music. It also showcases different types of sounds that can be seen as very uplifting and beautiful.

7. #14: “Melancholy Blues,” performed by Louis Armstrong and his Hot Seven. 3:05
I am a fairly big fan of the blues and feel that, like some other artists on this list, Louis Armstrong is a perfect addition of variety to the tracks. It’s a laid back vibe that showcases the desire for emotion in music from human beings.

8. #18: The Philharmonia Orchestra, “Fifth Symphony, First Movement” composed by Ludwig van Beethoven. 7:20
This sone might be the most iconic pieces on the list. Made by a human being that has created many recognizable compositions, I feel that his contribution to music should most definitely be included in the top 10. It also displays a fierce and intense range of classical music with an opening that is most likely recognized by anyone on earth.

9. #21: Holborne, Paueans, Galliards, Almains and Other Short Aeirs, “The Fairie Round,” performed by David Munrow and the Early Music Consort of London. 1:17
This number is very inspiring and represents the wonderful creativity and talents of children and human beings on this planet. It very much fits so well with the recording by Nick Sagan and I feel that whoever discovers it would be pleasantly surprised.

10. #26: “Dark Was the Night,” written and performed by Blind Willie Johnson. 3:15
I actually had no idea that this number, along with the rest of them actually, was included on this list as it’s one of my dad’s favourite musicians. Even mentioned in the Twenty Thousand Hertz podcast as a favourite, I can remember Johnson’s blues playing through my house in the summer time and it brings great comfort and soul to me when I listen. The guitar technique is unique and classic and has a ton of influence on artists after blind Willie.

 

Reference

Taylor, D. (Host). (2016-present). Voyager Golden Record [Audio podcast episode]. Twenty Thousand Hertz. https://www.20k.org/episodes/voyagergoldenrecord?rq=golden%20record