Trend Engine: AI-Powered News & Trends

Attention new and aspiring quants! We get a lot of threads about the simple education stuff (which college? which masters?), early career advice (is this a good first job? who should I apply to?), the hiring process, interviews (what are they like? How should I prepare?), online assignments, and timelines for these things, To try to centralize this info a bit better and cut down on this repetitive content we have these weekly megathreads, posted each Monday.

[Previous megathreads can be found here.](https://www.reddit.com/r/quant/search?q=Weekly+Megathread&restrict_sr=on&sort=new&t=all)

**Please use this thread for all questions about the above topics. Individual posts outside this thread will likely be removed by mods.**

Stock-outs may very well be part of the game in dropshipping, but with robust strategies in place, they don’t have to end your play. Equip yourself with effective tools, strengthen supplier relationships, diversify your options, and stay adaptive. This proactive approach not only protects your bottom line but also boosts your store’s reputation in the long run.

It’s a translation model.

Key Features:

* **Multilingual Support for 92 Languages**: Qwen-MT enables high-quality translation across 92 major official languages and prominent dialects, covering over 95% of the global population to meet diverse cross-lingual communication needs.
* **High Customizability**: The new version provides advanced translation capabilities such as terminology intervention, domain prompts and translation memory. By enabling customizable prompt engineering, it delivers optimized translation performance tailored to complex, domain-specific, and mission-critical application scenarios.
* **Low Latency & Cost Efficiency**: By leveraging a lightweight Mixture of Experts (MoE) architecture, Qwen-MT achieves high translation performance with faster response times and significantly reduced API costs (as low as $0.5 per million output tokens). This is particularly well-suited for high-concurrency environments and latency-sensitive applications.

[benchmark](https://preview.redd.it/ebw46w8hkuef1.png?width=1860&format=png&auto=webp&s=0652bf1ba1530779185f78006929ce89c53a2aaf)

[https://qwenlm.github.io/blog/qwen-mt/](https://qwenlm.github.io/blog/qwen-mt/)

Hey everyone,

I’ve been working as a computer vision engineer for about 2 years, mostly doing object detection, tracking, OCR, and similar projects. Lately though, I’ve gotten more interested in NLP and I’m thinking about switching fields.

So far I’ve been learning on my own — I’ve built a few chatbots, trained custom NER models using spaCy, and played around with Hugging Face transformers like `bert-base-cased`. I’ve also made small apps using Streamlit and FastAPI for tasks like summarization, sentiment analysis, translation, etc.

Now I’m planning to apply for NLP jobs, but I’m not exactly sure what kind of projects would make my profile stronger. Also wondering:

* What kinds of NLP projects would be good to showcase in a portfolio?
* How’s the NLP job market these days? Is it better to go for more general ML roles?
* What should I focus on when preparing for interviews — what kind of technical questions usually come up?
* Any advice or tips from folks who’ve made a similar switch?

Would really appreciate any suggestions or experiences you’re willing to share. Thanks!

Hello and welcome to the /r/AlgoTrading Community!

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**Finally,** the two most commonly posted questions by new members are as followed:

* Where can I find historical data? [Which is answered in our wiki here](https://www.reddit.com/r/algotrading/wiki/index#wiki_how_to_get_historical_data_for_free)
* And, where can I find examples of strategies to implement? [Which you can find examples from our wiki here](https://www.reddit.com/r/algotrading/wiki/index#wiki_strategy)

**Be friendly and professional toward each other and enjoy your stay! :)**

To elaborate a bit: I currently withdraw money from my sales via SEPA to Wise, and then use Binance P2P. The platform I sell on also suggests Payoneer and Skrill, but I’m unable to open a Skrill account due to local regulations. Direct crypto withdrawal from the platform costs $20 plus a 6% fee, which is not viable.

On Wise, I pay a 0.47% fee to convert EUR to USD, and then I use Binance P2P (USD side, because with EUR there’s a 1-day hold). The P2P fee varies between 0.5% and 1% depending on market conditions. So overall, I’m paying close to 1% just to move the money into crypto.

I need your advice for this situation. I have limited capital, so I need to turn the money around quickly to restock inventory. Also, SEPA doesn’t work on weekends, which delays things further.

We know Muricans don’t want bikes, so EVs are the next best thing. Why people are not buying EVs? Lack of infrastruture. But ofc, republicans won’t let this happen because they want to appease their fossil fuels donors.

Edit: just enough communal charging stations.

Imagine this:Customer A pays full price.Customer B gets a 15% discount.Both convert.

[Delta Airlines](https://fortune.com/2025/07/16/delta-moves-toward-eliminating-set-prices-in-favor-of-ai-that-determines-how-much-you-personally-will-pay-for-a-ticket/?utm_source=emailoctopus&utm_medium=email&utm_campaign=%23235%20-%20ChatGPT%27s%20Squeeze%2C%20Agentic%20AI%20Wars%2C%20%26%20Gmail%20Shopping) is already doing it. The company is experimenting with AI technology that calculates what each customer is willing to pay based on demand, booking patterns, and individual behavior – and charges accordingly. 

Only 3% of their fares are priced this way now, but they plan to grow that to 20%.

If it works for airlines, how long before ecom brands follow?