They’d presumably do worse. LLMs have no intrinsic sense of programming logic. They are merely pattern matching against a large training set. If you invent a new language that doesn’t have sufficient training examples…
Same. I use Apple Notes. I have a few notes pinned (regular work, creative work, self-education, travel, chores). I write tasks. Break them up into small tasks with indents. Pick a task from the pool and execute.…
Genuinely curious; while I understand why we would want a language to be open-source (there's plenty of good reasons), do you have anecdotes where the open-sourceness helped you solve a problem?
It's like the secret beaches in every south-east asian nook and crany. They're so secret there's signs pointing to them every where and they are overrun with tourists.
I see the value in showcasing that LLMs can run locally on laptops — it’s an important milestone, especially given how difficult that was before smaller models became viable. That said, for something like this, I’d…
My thinking is threaded. I maintain lists (in a simple txt file and more recently, in Notes on the Mac) and add the tasks to it. Subtasks go into an indent. I have different notes for regular work/pet…
I would argue that framework isn't the winning component, the people are. A lot of people can say similar things for framework <<X>> and they'd be right given their own experience but I think they give themseleves too…
I would guard against "arguing from the extremes". I would think "on average" compact is more helpful. There are definitely situations where compactness can lead to obfuscation but where the line is depends on the…
In your specific example, time of day, weather (foggy, sunny, over-cast) along with images of cars with different colors, models, makes, from different angles will all be training parameters to begin with so the neural…
I'm wondering if this is a limitation though. If it can be learnt from training data, would it not be part of the neural network training data? I imagine we use Scallop to bridge the gap where we can't readily learn…
I read the paper on Lobster a little bit. Scallop does its reasoning on the CPU - whereas Lobster is an attempt to move that reasoning logic to the GPU. That way the entire neurosymbolic pipeline stays on the GPU and…
It's a combination of neural networks and symbolic reasoning. You can use a neurosymbolic approach by combining deep learning and logical reasoning: A neural network (PyTorch) detects objects and actions in the image,…
This. I'm trying to set up a personal developer blog and I have a very specific set of requirements. Tried several static blogging frameworks. Apart from the software bloat, I found myself spending a gratituous amount…
This paper suggests that LLMs can be trained to handle multi-stage questioning by automatically optimizing prompts using feedback-based methods, improving their ability to process complex, multi-step interactions.
Same. I was writing my own language compiler with MLIR/C++ and GPT was ok-ish to dive into the space initially but ran out of steam pretty quickly and the recommendations were so off at one point (invented MLIR…
They’d presumably do worse. LLMs have no intrinsic sense of programming logic. They are merely pattern matching against a large training set. If you invent a new language that doesn’t have sufficient training examples…
Same. I use Apple Notes. I have a few notes pinned (regular work, creative work, self-education, travel, chores). I write tasks. Break them up into small tasks with indents. Pick a task from the pool and execute.…
Genuinely curious; while I understand why we would want a language to be open-source (there's plenty of good reasons), do you have anecdotes where the open-sourceness helped you solve a problem?
It's like the secret beaches in every south-east asian nook and crany. They're so secret there's signs pointing to them every where and they are overrun with tourists.
I see the value in showcasing that LLMs can run locally on laptops — it’s an important milestone, especially given how difficult that was before smaller models became viable. That said, for something like this, I’d…
My thinking is threaded. I maintain lists (in a simple txt file and more recently, in Notes on the Mac) and add the tasks to it. Subtasks go into an indent. I have different notes for regular work/pet…
I would argue that framework isn't the winning component, the people are. A lot of people can say similar things for framework <<X>> and they'd be right given their own experience but I think they give themseleves too…
I would guard against "arguing from the extremes". I would think "on average" compact is more helpful. There are definitely situations where compactness can lead to obfuscation but where the line is depends on the…
In your specific example, time of day, weather (foggy, sunny, over-cast) along with images of cars with different colors, models, makes, from different angles will all be training parameters to begin with so the neural…
I'm wondering if this is a limitation though. If it can be learnt from training data, would it not be part of the neural network training data? I imagine we use Scallop to bridge the gap where we can't readily learn…
I read the paper on Lobster a little bit. Scallop does its reasoning on the CPU - whereas Lobster is an attempt to move that reasoning logic to the GPU. That way the entire neurosymbolic pipeline stays on the GPU and…
It's a combination of neural networks and symbolic reasoning. You can use a neurosymbolic approach by combining deep learning and logical reasoning: A neural network (PyTorch) detects objects and actions in the image,…
This. I'm trying to set up a personal developer blog and I have a very specific set of requirements. Tried several static blogging frameworks. Apart from the software bloat, I found myself spending a gratituous amount…
This paper suggests that LLMs can be trained to handle multi-stage questioning by automatically optimizing prompts using feedback-based methods, improving their ability to process complex, multi-step interactions.
Same. I was writing my own language compiler with MLIR/C++ and GPT was ok-ish to dive into the space initially but ran out of steam pretty quickly and the recommendations were so off at one point (invented MLIR…