Neural networks
Source reports covering Neural networks. Stories will appear when analysis and community reactions are ready.
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Source reports
English ↔ Claudish Translator
tool
1 min read
Claudish is a bidirectional translator between English and a language called Claudish. It is powered by compiled neural programs with 0.6 billion parameters. The translator supports conversion from English to Claudish and from Claudish back to English.
Could a computer scientist build a brain?
research
36 min read
A program is proposed to enable a single cell to build itself into a brain using only genomic information. The program must be compact enough to fit within a genome and efficient enough to complete development in a timely manner.
Can you reverse engineer an ASIC?
tool
5 min read
A new puzzle challenges participants to reverse engineer a chip layout without additional information about its function. Modern chips are initially created from code using hardware description languages like Verilog, which are then synthesized into a netlist.
AI-generated videos to maximally drive a target brain region
research
1 min read
NEvo is a neural-guided system designed for synthesizing videos through evolutionary algorithms. It leverages deep learning techniques to enhance video generation and editing processes.
The Smallest Brain You Can Build: A Perceptron in Python
tool
9 min read
A perceptron is the simplest form of a neural network, processing one input to produce a binary output. It can be built from scratch in Python using basic components like a weight, a bias, and a loop, allowing for live learning demonstrations in a browser without complex mathematics or libraries.
Leiden Declaration on Artificial Intelligence and Mathematics
research
14 min read
The Leiden Declaration on Artificial Intelligence and Mathematics acknowledges the transformative impact of AI technologies on mathematical practice. It recognizes both the potential benefits and diverse reactions among researchers regarding the use of AI in mathematics.
Learning the Integral of a Diffusion Model
research
83 min read
Sampling from a diffusion model involves an iterative process where a denoiser estimates the tangent direction to a path through input space. Neural networks can be trained to directly predict the integral that transforms samples from a simple noise distribution into samples from a target distribution.
I'm scared about biological computing
opinion
2 min read
Biological computing applies mathematical concepts and probabilities used in AI to human neurons. This intersection raises concerns about the ethical implications and potential dystopian outcomes of merging biological systems with computational processes.
There Will Be a Scientific Theory of Deep Learning
research
2 min read
A scientific theory of deep learning is emerging that characterizes key properties and statistics related to the training process, hidden representations, final weights, and performance of neural networks. The research consolidates various ongoing studies in deep learning theory.
An NSFW filter for Marginalia search
tool
13 min read
An NSFW filter for Marginalia Search is being developed in response to requests from API consumers. The filter will utilize a single hidden layer neural network, having explored various other methods prior to this decision.
Tinybox- offline AI device 120B parameters
tool
5 min read
Tinygrad is a neural network framework designed for simplicity and speed, breaking down complex networks into three operation types: ElementwiseOps, ReduceOps, and MovementOps. ElementwiseOps include operations like SQRT and ADD, ReduceOps perform functions like SUM and MAX on a single tensor, and MovementOps manage data movement without copying, utilizing ShapeTrack.
Neural Boids
research
10 min read
Noids, or neural boids, utilize a small neural network to generate steering forces based on visual input from each agent, comprising 1,922 learned parameters. This system mimics the behavior of real birds in a murmuration, where no leader or predetermined choreography directs the movement of the flock.
A CPU that runs entirely on GPU
tool
8 min read
nCPU is a CPU architecture that operates entirely on GPU, utilizing tensors for registers, memory, flags, and the program counter. All arithmetic operations, including addition, multiplication, bitwise operations, and shifts, are performed through trained neural networks, with specific methods like Kogge-Stone carry-lookahead for addition and learned byte-pair lookup tables for multiplication.
'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images
research
8 min read
A thermodynamic computer can generate images from noise while consuming significantly less energy than traditional generative AI models. This technology mimics the functionality of AI neural networks.
Hypernetworks: Neural Networks for Hierarchical Data
21 min read
Hypernetworks extend traditional neural networks to effectively handle hierarchical data, acknowledging that real-world data often consists of multiple distinct datasets rather than a single flat mapping. This method allows for the modeling of variations in observations, such as those seen in clinical trials across different hospitals, where hidden parameters influence outcomes.