🚨BREAKING 🚨: Trump says that starting tomorrow, the U.S. will start imposing reciprocal tariffs on every country in the world.
No exceptions. Everyone gets taxed.🫵🏾⚡️
What do you make of this move?
Bullish 👍🏼 or Bearish 👎🏼 ?
🇨🇳34% on China
🇪🇺20% on EU
🇨🇭Switzerland 31%
🇻🇳Vietnam 46%
🇹🇼Taiwan 32%
🇯🇵Japan 24%
🇮🇳India 26%
🇰🇷Korea 25%
🇹🇭Thailand 36%
🇰🇭Cambodia 49%
🇬🇧Great Britain 10%
🇧🇩Bangladesh 37%
🇲🇾Malaysia 24%
🇿🇦South Africa 30%
🇵🇭Philippines 17%
🇮🇱Israel 17%
🇵🇰 Pakistan 29%
🇱🇰Sri Lanka 44%
And a minimum baseline tariff of 10% on everybody else.
Massive update for AI Engineers!
Training diffusion models just got a lot easier.
dLLM is an open-source library that does for diffusion models what Hugging Face did for transformers.
Here's why this matters:
Traditional autoregressive models generate text left-to-right, one token at a time. Diffusion models work differently - they refine the entire sequence iteratively, giving you better control over generation quality and more flexible editing capabilities.
The problem? Building and training these models required stitching together scattered tools and reimplementing research papers from scratch.
Most of the tooling has been scattered and is hard to reproduce.
dLLM changes this:
It unifies everything you need to train, evaluate, and deploy diffusion language models:
↳ Scalable training with LoRA, DeepSpeed, and FSDP support
↳ Unified evaluation that abstracts away inference complexity
↳ Ready-to-use recipes for pretraining, finetuning, and evaluation
The library includes implementations of models like LLaDA and Dream, plus training algorithms like Edit Flows that enable insertion, deletion, and substitution operations.
The team just released ModernBERT-Chat models showing you can turn BERT into lightweight chatbots through masked instruction tuning. This is practical and worth exploring.
The setup is straightforward. Run locally with Accelerate or scale to multi-node clusters with Slurm.
If you're working with language models and want to explore diffusion-based approaches without rebuilding infrastructure, dLLM gives you a production-ready starting point.
Link to the repo in the next tweet.
Do unto others what you want others do unto you - This has been my life’s principle.
This is why I will never do nobody dirty - it all comes back to you.
Let love lead people - love.