@rdawgishere.bsky.social
Student UofT. Will I use this purely to keep track of my learning progress? Maybe.
Does bisexual mean once every sexual or once every other sexual?
08.02.2025 16:18 β π 11 π 10 π¬ 0 π 0Soup is too healthy for some winter days
06.02.2025 03:04 β π 2 π 0 π¬ 0 π 0That's crazy. Poutine slaps on a cold winter day
06.02.2025 02:26 β π 1 π 0 π¬ 1 π 0Your love for humanity?
01.02.2025 02:40 β π 2 π 0 π¬ 1 π 0Overheard
31.01.2025 03:13 β π 3 π 0 π¬ 0 π 0Lol okay
29.01.2025 01:46 β π 1 π 0 π¬ 0 π 0Lmao how have I been groomed? L take lol
27.01.2025 17:33 β π 1 π 0 π¬ 1 π 0I think J6 is enough documentation
25.01.2025 14:59 β π 1 π 0 π¬ 1 π 0Also not having ads everything post helps too
21.01.2025 19:05 β π 2 π 0 π¬ 1 π 0I think NLP and LLMs service extremely different usecases and you have to consider the limitations of LLMs like their latency, cost, privacy and how they are black-boxes before claiming the death of NLP.
Similar to how computer vision techniques complement CNNs we might see something like this.
Overheard
13.01.2025 16:02 β π 4 π 0 π¬ 0 π 0But I think after something like the Ontario line, it's something the city should look into. it would dramatically help fund the TTC, and pave way for a more pedestrian toronto
12.01.2025 18:16 β π 2 π 0 π¬ 1 π 0That looks so good!!
12.01.2025 18:05 β π 0 π 0 π¬ 0 π 0As much as I love NYC'S congestion relief zone, I don't think Toronto's transit framework is robust enough to handle such a policy.
12.01.2025 18:00 β π 2 π 0 π¬ 1 π 0Not to brag, but I can always put a USB-C cable in the right way up first time.
02.01.2025 11:12 β π 3195 π 167 π¬ 150 π 18Product idea: headphones that can display what youβre listening to.
Iβm always curious.
Optional of course, no oneβs making you.
Mind if I slip into something a little more comfortable? *returns to womb*
30.12.2024 20:50 β π 329 π 46 π¬ 9 π 2Computer Vision is possibly the most fun subarea of ML. So many tools and techniques that are possible
09.12.2024 05:48 β π 3 π 0 π¬ 0 π 0Day 3 ML stuff goals:
- Try Finetuning using LoRA
- Try to Implement CoT and Tot.
Day 2 ML stuff progress:
- Scrapped all the data legally
- Implemented the GPT API.
Day 2 ML stuff Goals:
- Revise CI/CD
- (legally) scrape data
- Try GPT API
Alright day 1 Progress:
1. Did some DevOps review
2. Created an Infrastructure diagram
3. Initialised my repo
Day 1: Learning how to Deploy ML products
1. Creating the first project with Brave - 3 hours
