Sid retweeted

Tim Sweeney@TimSweeneyEpicOct 18
United States
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When I was writing Unreal Engine 1, my time was divided as follows:
- Around 30% went to seriously deep coding on hard problems: assembly language texture mappers, C++ BSP trees, data persistence, object oriented systems design, and networking.
- Around 70% was just typing and refactoring large bodies of code needed for a complete engine feature set. This was not hard, and while I was doing it my mind was mostly on the deeper coding topics, thinking and planning for what's next. It didn't feel much different from vibe coding today, except that it was just me typing code on an IBM Model M keyboard rather than prompting it and reviewing the results.
So, it has always seemed perfectly logical that we would rely on AI for that 70%, once the AI could do it with a similar quality standard as we could, which has never been perfection. It came as no surprise that, after a few years of AI model evolution, it was able to take the reigns on that 70% and free up programmers' time for more valuable tasks.
What's more of a surprise is the emergence of AI as a sort of insta-Carmack able to solve hard technical problems quite cleverly and often cleanly, and that it's able to reason about and work in complex 3D scenes both by operating the tools and by directly understanding the raw data files.
I abandoned assembly language in 1998 when out-of-order CPUs made much simpler C/C++ code faster, and never I missed it. If prompting through architectural documents, concept art, and design plans can transcend typing code and tweaking vertices, that will enable developers to spend their time on higher-level, higher value technical and creative tasks.
What matters is the end product, whether it's a game or an engine. Anything developers can do to try out more ideas and make better software and games faster is a win for everyone.
Sid retweeted
We're hiring safety researchers at @thinkymachines! 🦺
My team works on safety across the model development stack -- pre-training data filtering, harmful capability evals, safety post-training, red-teaming, abliteration/malicious fine-tuning.
We're particularly interested in building evals and tooling to make strong safety cases for open-weights releases. We think this is where some of the most important safety research will happen in the next few years.
If any of this resonates, apply here: jobs.ashbyhq.com/ThinkingMac…
Sid retweeted
Replying to @lauriewired
@lauriewired had a based take something I found encapsulated the present state of the software dev ecosystem
Vibe coding can be thought of as the advent of the calculator. The same way calculator did not kill math vibe coding won't kill software development.
Sid retweeted
It's very cool that Apple shipped a 20B parameter on-device.
You can't put 20B parameters in RAM at any reasonable precision. To make it work they are using pretty exotic architecture by today's standards.
A small model predicts from the query (or prompt) which experts to load from Nand into RAM. The key distinction from a typical MoE is that you do this once per query and then generate all the tokens with the same experts (instead of switching the experts for every token).
Sid retweeted
Huawei proposes HiFloat4 FP4 (HiF4) format for Huawei Ascend NPUs and achieves performance comparable to BF16 baselines, while delivering substantial improvements in computational efficiency.
Sid retweeted
Replying to @AnthropicAI
I actually want to love you so badly like your values and your research first approach
But u push me to hate you at every step u push me to hate you





























