Hey everyone, I recently started dropshipping and crossed $425+ in the last 31 days, growing over 700% this month alone. I know how tough it can be to get started, so if you’re someone who’s struggling or just beginning, I’m open to collaborating. I’ll share everything that’s working for me, from product research and supplier strategies to listing optimization and order handling. We can either build a store together or grow yours side by side. No paid course, no hype,Just hit $425 in 31 days with dropshipping – looking to partner and grow together just real teamwork and profit-sharing if it’s a joint project. If you’re serious and ready to grow, let’s do this together.
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I’m finishing a bachelor’s in computer science with a linguistics minor in around 2 years, and am considering a master’s in computational linguistics afterwords.
Ideally I want to work in the NLP space, and I have a few specific interests within NLP that I may even want to make a career of applied research, including machine translation and text-to-speech development for low-resource languages.
I would appreciate getting the perspectives of people who currently work in the industry, especially if you specialize in MT or TTS. I would love to hear from those with all levels of education and experience, in both engineering and research positions.
1. What is your current job title, and the job title you had when you entered the field?
2. How many years have you been working in the industry?
3. What are your top job duties during a regular work day?
4. What type of degree do you have? How helpful has your education been in getting and doing your job?
5. What are your favorite and least favorite things about your job?
6. What is your normal work schedule like? Are you remote, hybrid, or on-sightThanks in advance!
Edit: Added questions about job titles and years of experience to the list, and combined final two questions about work schedules.
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I’ve never seen anything like it. I mean, I know scamming is an integral part of America and an integral part of the world, but I feel like the white hot center of scamming is the PumpFun Telegram Solana confluence.
It is fun to make a token on PumpFun, but just the amount of sheer scammery that happens once you create a Telegram group, I’ve never seen anything like it.
In a way, it scares me that it’s a preview of things to come. That the 21st century will just be one long, unending scam. That any technology will be co-opted to just scam, and that the technologies that are being created facilitate scams better than they used to.
Chwowww, all I gotta say is the shit sucks and is terrible for you. Like junk food dipped in pesticides.
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As a math major, I was interested in seeing what different fields of mathematical research looks like. I decided to just browse the Arxiv, but I can’t help to notice the difference between Stat.ML and CS.LG sections.
From my understanding, they are both suppose to be about Machine Learning research, but what I found was that many of the CS.LG articles applied ML to novel scenarios instead of actually researching new mathematical/statistical models. Why are these considered ML research, if they are not researching ML but using it?
Does this reflect a bigger divide within the machine learning research field? Is there some fields in ML that are more suited for people interested in math research? if so, are those generally hosted in the math/stats department, or still under the CS department?
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The sight of the Batmobile in São Paulo isn’t just a nostalgic trip down memory lane; it’s a testament to the enduring legacy of Batman and his world. This spectacular event reminds us of the powerful impact pop culture has on our lives, offering a momentary escape and sparking imagination wherever it goes.
So next time you’re out and about, keep your eyes peeled. Who knows? You might just spot a piece of superhero history cruising past you, bringing adventure to life in the most unexpected places.