Show HN: My LLM CLI tool can run tools now, from Python code or plugins
LLM 0.26 introduces the ability for large language models to run tools directly in the terminal, allowing integration with models from OpenAI, Anthropic, and others through a Python function interface and CLI tool.
Show HN: AutoThink – Boosts local LLM performance by 43% with adaptive reasoning
AutoThink enhances local LLM performance by 43% through adaptive reasoning, allocating computational resources based on query complexity—complex queries receive 70-90% of tokens, while simple ones get 20-40%.
Look Ma, No Bubbles: Designing a Low-Latency Megakernel for Llama-1B
Low-latency megakernel design for Llama-1B achieves 78% memory bandwidth utilization on H100 GPUs, outperforming existing systems by over 1.5x by merging multiple kernels into a single execution unit.
[R] Bloat in machine learning shared libs is >70%
The paper "The Hidden Bloat in Machine Learning Systems" reveals that device code is a major contributor to bloat, with reductions in code size of up to 75% for device code and 72% for host code using the tool Negativa-ML.
Revisiting the algorithm that changed horse race betting (2023)
Bill Benter's horse betting algorithm, which generated over $1 billion in profits, utilizes a multinomial logit model to estimate winning probabilities, refined through decades of data and modern coding techniques.
Compiling a Neural Net to C for a 1,744× speedup
Compiling a neural network to C achieved a remarkable 1,744× speedup in inference speed by utilizing logic gates instead of traditional activation functions, specifically for a 3×3 kernel function in Conway’s Game of Life.
Developing first petahertz-speed phototransistor in ambient conditions
Researchers at the University of Arizona have developed the world's first petahertz-speed phototransistor, capable of operating in ambient conditions, which could enable computers to process data over 1,000 times faster than current technology.
Launch HN: Relace (YC W23) – Models for fast and reliable codegen
Relace offers a Fast Apply model that merges code snippets at 4300 tokens per second, significantly reducing merge errors compared to competitors like Sonnet and Llama, while also saving ~40% on Claude 4 output tokens.
[R] New ICML25 paper: Train and fine-tune large models faster than Adam while using only a fraction of the memory, with guarantees!
Outcome-Based Reinforcement Learning to Predict the Future
Outcome-based reinforcement learning (RL) can achieve frontier-scale accuracy in forecasting by adapting algorithms like Group-Relative Policy Optimisation (GRPO) and ReMax, effectively handling binary, delayed, and noisy rewards in real-world applications.
[R] AutoThink: Adaptive reasoning technique that improves local LLM performance by 43% on GPQA-Diamond
AutoThink enhances local model reasoning by 43% on GPQA-Diamond through adaptive resource allocation, dynamically adjusting thinking time based on query complexity.
[R] Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks
LLMs exhibit a significant accuracy variance in automated reasoning, with performance ranging from +34.8% on logical tasks to -44.5% on factual tasks, highlighting the need for careful evaluation of their outputs.
FlowTSE: Target Speaker Extraction with Flow Matching
FlowTSE introduces a novel approach to target speaker extraction (TSE) using conditional flow matching, simplifying the process compared to existing generative methods that often involve complex pipelines.
Direct Preference Optimization vs. RLHF
Direct Preference Optimization (DPO) enhances language models by aligning them with human preferences through direct training on preference data, eliminating the need for complex reinforcement learning methods.
Launch HN: MindFort (YC X25) – AI agents for continuous pentesting
MindFort develops autonomous AI agents that continuously identify, validate, and patch security vulnerabilities in web applications, functioning as a 24/7 AI red team.