Computational lithography: Driving nanometer precision in microchip manufacturing | ASML – YouTube
Our computational lithography software is powered by physical models and algorithms enabled by cutting-edge machine learning and data science techniques. From early design to high-volume manufacturing, it lets us use our unique knowledge about the inner workings of lithography systems to optimize the chip patterning process. Layer by layer, chip by chip, wafer by wafer, […]
A quote from Steven Johnson
The emergence of long context models is, I believe, the single most unappreciated AI development of the past two years, at least among the general public. It radically transforms the utility of these models in terms of actual, practical applications. Source: A quote from Steven Johnson
Copy Exactly! – Wikipedia
Copy Exactly! is a factory strategy model developed by the computer chip manufacturer, Intel, to build new manufacturing facilities with high capacity practices already in place.[1] The Copy Exactly! model allows factories that successfully design and manufacture chips to be replicated in locations globally.[2] Source: Copy Exactly! – Wikipedia
Generalizing an LLM from 8k to 1M Context using Qwen-Agent | Qwen
In this blog, we have introduced how to build the agent that is capable of handling 1M-context with a 8k-context model. It then becomes obvious how to synthesize the data once the agent is prepared. For instance, we could enlist volunteers to interact with the agents and record the outcomes to construct the fine-tuning dataset. […]
The Crash and Rebirth of a Six-Year-Old Open Source Project – DIYgod
The project was developed six years ago, and many trendy Node.js technologies and dependencies that were touted as the “Next Generation” at that time have become outdated. Many popular new technologies nowadays cannot be applied, such as JSX, TypeScript, Serverless, etc. Its architecture is also very unreasonable, with information about each route scattered in multiple […]
Anthropic’s Prompt Engineering Interactive Tutorial
Claude is sensitive to patterns (in its early years, before finetuning, it was a raw text-prediction tool), and it’s more likely to make mistakes when you make mistakes, smarter when you sound smart, sillier when you sound silly, and so on. Source: Anthropic’s Prompt Engineering Interactive Tutorial
Bytes Are All You Need: Transformers Operating Directly On File Bytes – Apple Machine Learning Research
our model requires absolutely no modality-specific processing at inference time, and uses an order of magnitude fewer parameters at equivalent accuracy on ImageNet. We demonstrate that the same ByteFormer architecture can perform audio classification without modifications or modality-specific preprocessing Source: Bytes Are All You Need: Transformers Operating Directly On File Bytes – Apple Machine Learning […]
Online Cryptography Course by Dan Boneh
Stanford course on computer cryptography. Source: Online Cryptography Course by Dan Boneh
Bringing developer choice to Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview
It’s increasingly clear that any strategy that ties you to models from exclusively one provider is short-sighted. The best available model for a task can change every few months, and for something like AI code assistance model quality matters a lot. Getting stuck with a model that’s no longer best in class could be a […]
Carpentopod: A walking table project
some software for fun to generate various optimized walking mechanisms. And when I also picked up some electronics and wood working skills in more recent years, I was able to turn one of these mechanisms into an actual wireless walking wooden coffee table: the Carpentopod. Source: Carpentopod: A walking table project 木 牛流马