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Can verified Skrill users in Finland/EEA withdraw LTC directly to Cake Wallet?(reddit.com)
Finland / EEA user here. My Skrill account is fully verified (KYC completed). Can anyone in Finland or another EEA country currently buy Litecoin in Skrill and withdraw it directly to a non-custodial wallet such as Cake Wallet? If yes, are there any restrictions, limits, or additional verification checks? -I'm specifically interested in recent first-hand experiences from 2025–2026. Thank you, and have a nice day! -Thanks in advance, and have a nice day! submitted by /u/j3sus_is_b4ck [link] [Kommentare]
Open weights are not enough: we need open training frameworks for research and better algorithms [P](reddit.com)
Open weights are important and critical, but they are not enough by themselves. If we want open ML and AI research to move forward, we also need open training frameworks: codebases that do more than run jobs. They should make the training process visible, understandable, and modifiable, so researchers/engineers/practitioner can build new algorithms instead of fighting hidden systems. That was the motivation behind FeynRL (pronounced “FineRL”) a framework I built for RL post-training of LLMs, VLMs, and agents. RL is already hard to make work. With LLMs, VLM, and agents, it becomes even messier: rollout engines, reward computation, distributed training, weight syncing, credit assignment problems, long-horizon behavior, and many small implementation details that can quietly break everything. The core idea behind FeynRL is simple: algorithms should stay algorithms, systems should stay systems, and researchers/engineers/practitioner should be able to understand the full training loop end-to-end without spending days or weeks. GitHub: https://github.com/FeynRL-project/FeynRL The framework is designed to keep the framework explicit: from data loading and rollout generation to reward computation, loss construction, optimization, and evaluation. The goal is to make it easier to develop new algorithms, training recipes, reward designs, rollout strategies, and optimization methods without going through a convoluted hidden system. The framework currently includes examples for SFT, DPO, and RL-style post-training for both vllm and llm, with support for single-GPU, multi-GPU, and cluster setups. Would love feedback, issues, suggestions. Also, curious to hear what parts of RL post-training infrastructure people still find too hidden, hard to debug, or hard to modify. submitted by /u/summerday10 [link] [Kommentare]
How to get into PhD program [D](reddit.com)
I am currently a cs graduate student at a top university after completing a comp eng undergrad there My thesis is more to do with embedded system security and maybe applied ml Unfortunately I didn’t get into any ml focused graduate program as they’re extremely competitive even with good grades from a top undergrad (and some projects of course) I want to do a PhD in ml as I’m currently having a tonne of fun taking optimization and ml courses - further I’ve been studying it for years already I think my interests lie mostly in optimization ie shampoo, soap, hessian free/approximations Also inference optimization is pretty cool but I’m more of a math person even though my undergrad was in computer engineering I enjoy learning about things like pca, lda, other stats techniques on my own I’ve had about 7 internships but they were all in software except one where I did a bit of ml near the end ie fitting decision trees to data Currently I couldn’t get a job after 1 year of applying so I’m in a masters program at my school. I have 0 publications and my supervisor puts out maybe 1 paper every 3 years so it’s unlikely I’ll get one from my thesis, if I’m lucky I could do some sort of anomaly detection paper but even that’s unlikely (t-test is pretty much unbeatable) What steps should I take to get into a PhD program after graduating and what classes should I take as my math background feels like it’s lacking when I read something like the shampoo paper submitted by /u/proturtle46 [link] [Kommentare]
Turkey has one of the world's most active crypto communities — what do people think about NEO today?(reddit.com)
Turkey is often mentioned as one of the countries with the highest levels of crypto adoption and one of the most active crypto communities in the world. ​ At the same time, most discussions seem to focus on Bitcoin, Ethereum, Solana, memecoins and the latest trends. ​ This made me curious about NEO. ​ NEO has been around for years, survived multiple market cycles, continues to develop its ecosystem, and still has dedicated communities around the world, including in Turkey. ​ I'm interested in hearing honest opinions from both Turkish and international crypto users: ​ - What is NEO's reputation today? - What are its biggest strengths? - What has held it back from receiving more attention? - Do you think NEO still has opportunities to grow in today's market? ​ Looking forward to hearing different perspectives and experiences. ​ For anyone interested in following the ecosystem more closely, I've found these communities useful: ​ Neo Blockchain Discord: https://discord.gg/neosmarteconomy ​ NeoPod Community Discord: https://discord.gg/HYq4EBwMnj ​ NeoPod has been hosting AMAs, community discussions and reward-based activities, while the Neo Discord remains the main place for ecosystem news, announcements and developer updates. submitted by /u/reaverraziel168 [link] [Kommentare]