Rewrite AI-generated text into natural, human-sounding content for blogs, emails, social posts, and everyday writing. Simple, fast, and reliable.
Everyone has been calling for an Oct low because of similar patterns in previous midterm years. We've all been watching Ben Cowen's videos. If everyone is expecting the bottom to be in October, would that change things? I'm not a smart man so please dont make fun of me submitted by /u/Guy-Lambo [link] [Kommentare]
Paranoid LLMsOne thing I notice with LLM-generated code is that they are paranoid. And that affects code quality. For me, I will do things the naive way, and only when I encounter errors during testing will I add safety nets for edge cases. But LLMs tend to want to catch all possible things that might go wrong from the get-go, even when we know that an error is not possible, or when we actually want the error to propagate and crash the program.Maybe it’s because of how they are trained on coding benchmarks. They are optimised to not make the program crash no matter what. When we humans code, we want the program to crash so that we become aware of a problem fix it, not necessarily by adding error-catching logic but maybe by enforcing some kind of invariant into the system.Another example of paranoia is how LLMs tend towards defensive code. For me, if I know that there is only one place that a function is being called, I will not add any checks on the arguments inside the function or try to coerce types - there is simply no need! On the other hand, LLMs default to trying to handle as many variations of malformed function arguments as possible, doing null checks, converting types, etc. It assumes that this function will eventually be called from 10 other places with messy arguments.What is the common theme here? LLMs try to solve imaginary problems. In doing so, they silently swallow program behavior. I want exceptions to raise, so that I can prevent that exception from ever throwing in the first place. I do not want to catch it. I want malformed function arguments to cause a crash, so that I can reconsider the function scope and how it is being called in different places. I do not want to let the show run on with type coercions that I have never allowed.2026-07-10 · 2 min read../
An interactive guide to how attention, embeddings, and positional encoding work together to predict the next move.
What a Buffer is in Node.js: a mutable byte view for files, sockets, hashes, images, protocol frames, encoding, slicing, and typed-array memory.
Hi! My team and I are trying to make it easier to program our assembly robot. We think current approaches with large AI models are going in the wrong direction, making robots unreliable and turning them into black boxes. From our point of view, AI should help program the robot, not control it directly. The problem is that there is no convenient language for programming complex movements. So instead, we fill a large lookup table (dataset) at 30 fps while the robot is controlled through teleoperation. AI acts just as the glue between these examples and fills in the gaps without adding new knowledge. This makes the model reliable, predictable, and debuggable, like code. And as I showed in the video, it took me 5 minutes to set up tray picking with randomness. What do you think about this approach? submitted by /u/Wing-Realistic [link] [Kommentare]
4 AI engines tested on SEO tool pricing accuracy. Copilot scored highest and cited ClaroRank as its source. July 2026.
