we'll have to circle back and see where it's at in Q3

Hope this finds you well,

Machine learning can facilitate the use of managerial buzzwords by enabling natural language processing algorithms to identify and categorize key phrases and terminology commonly used in management and corporate settings. This can facilitate the generation of buzzword-rich language in real-time, empowering individuals to communicate more effectively and authentically within a business context. Additionally, machine learning can also be leveraged to analyze large datasets, identifying emerging buzzwords and trends in management speak, thus allowing individuals to stay ahead of the curve and stay relevant in the constantly evolving corporate landscape.

Best,

[YOUR NAME]

(I'd say it's pretty much got it nailed)

Usually inference on hugging face for large models is free for individuals making a reasonable amount of API calls as part of their offerings, and I assume an open source version of this would be on there. I realize that it costs money.

I imagine there’ll be open source versions of ChatGPT in the near future given it’s wild popularity, I’ll probably just use that for personal projects, and in a business setting I would just have a dedicated model of that open source version running. .004 cents per 1000 tokens (or much less) is a hell of an ask if you’re doing anything where users generate tokens

It really does but there’s a point in time where OpenAI is going to want to cash in. Virtually all of their outputs could benefit from utilizing reinforcement learning to improve after the initial training, but we’ve seen how GPT3 and DallE-2 ultimately chose to be shipped as a sort of finished product that gets updates like any shipped app might, with costs attached. I don’t see why ChatGPT will be any different after x amount of time, unless Stable Diffusion is really eating their Dall-E 2 profitability and they need to find new ways of monetization that doesn’t charge the user utilizing ChatGPT

Thankfully PyTorch is Linux foundation now.

OpenAI produces SOTA models somewhat regularly in a multitude of domains and they’ve been using PyTorch since 2020. One of the best reasons to use libraries is the sheer amount of people who work on those libraries. You get all efficiency improvements, quality of life implementations, etc…

every time i've gotten NaN values it was due to a high learning rate so I second this.

you’re not a serious person

Ok lol

Explaining that one ideology may lead its followers to violate TOS more. If you want things specific to people who aren’t open fascists, AFAIK no democrats are posting QAnon shit which gets bans. Very few dems post about vaccine conspiracies. Etc etc etc. if one political party has a contingent of voters who violate terms of service more, they’re going to be banned more. Y’all just gloss over that part to pretend people who choose to do these things that they know violate TOS are victims

Where did I say republicans are open fascists? I said open fascists would be the most likely to be banned and the most likely to break tos terms, and this wouldn’t constitute unfair or unequal banning. Try rereading

Play on words with edge case and wedge issue :)

Mate when your argument relies on comparing oppressed groups in society that are oppressed due to no reason other than something they cannot change to people who openly choose to follow an ideology, the comparison starts to fall apart. You being right wing doesn’t make you oppressed, lol. You can just stop being right wing at any point.

I’m asking for proof that right wingers are suspended at a higher rate for the same actions. You don’t have anything to prove that, so you’re just guessing. Why are you interested in a data based field when you can’t demonstrate correlation that removes confounding variables?

lmao

Politics isn’t irrelevant but it is a dumb wedge case you’re making because your explicit bias in favor of right wing politics. I think it’s pretty much a no brainer that people on the left are going to like a guy less when he explicitly repeats right wing talking points, but that doesn’t explain the poll you linked showing republicans also liking him less over that same time frame. He’s becoming more unpopular with everyone, it’s just happening faster with people he’s explicitly setting out to upset, shocking.

Republicans being suspended more than democrats isn’t proof of bias against the right. I’m asking for data that specifically shows a double standard for the same actions. You’re not showing that. I imagine open fascists have the highest suspension rate of any political party but I don’t think that’s “one sided banning”, open fascists are just way more likely to explicitly break TOS, lol.

Neat! I think one of the biggest considerations to add to this in the future (if not already in it and if this class will be done again) would be to add parts on sparsification/Quantization with models for inference after training. That would really open up the ability to expand usage of the models in things like spaces. Very excited to see what's in the course!

I don’t think a 23 point swing in favorability and a growth in unfavorability in literally every group over the span of 2 months illustrates the point you’re attempting to make about Musk only growing in unpopularity due to “politics”. And that’s grown since June. But I’d love to see proof on one sided bans against the right, because this feels like the standard whining and false equivalency the right loves to espouse without any evidence. It’s wild to me that people who regularly simplify and misrepresent issues get into a data based field.