Life & fun · alternatives · 2026
24 alternatives to A weekend replication of STOKE, a stochastic superoptimiser
Haskell re-implementation of STOKE, the stochastic superoptimizer - blaze/notebooks/tutorial.ipynb at master · bollu/blaze
This project is a weekend implementation of STOKE, a stochastic superoptimizer that improves x86 assembly code through randomized search and Markov chain Monte Carlo techniques. It is designed for developers and… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. A weekend replication of STOKE, a stochastic superoptimiser launched in 2019; newer entries below may have overtaken it.
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The video demo runs a 7b Model on a normal gaming GPU. I think it already works quite well (accounting for the limited hardware power). :)
2024 · github.com · its alternatives →
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A discrete-time Python-based solver for the Stochastic On-Time Arrival routing problem - mehrdadn/SOTA-Py
2017 · github.com · its alternatives →
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Experimental Global Optimization Algorithm. Contribute to chrisstroemel/Simple development by creating an account on GitHub.
2018 · github.com · its alternatives →
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A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
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We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
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A complete transformer engine in C — inference, training, chat, vision. - carlovalenti/TRiP
Apr 2026 · github.com · its alternatives →
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A simple re-implementation of Google's sparsehash as a learning excercise. - qpfiffer/Simple-Sparsehash
2015 · github.com · its alternatives →
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STROT (arXiv:2505.01636): compile-time LLM code synthesis with deterministic, self-routing NLU runtimes. PyPI: strot-ai - strot-ai/Project-STROT
5d ago · github.com · its alternatives →
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Arc enables continual learning for agents to adapt, learn, and transfer knowledge in live environments. Open-source SDK for building agents that learn from experience and improve over time.
2025 · arc.computer · its alternatives →
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Probabilistic language based on pattern matching and constraint propagation, 153 examples - mxgmn/MarkovJunior
2022 · github.com · its alternatives →
- 11
I want to share a really dumb, but very practical project I have packaged this summer, to perform operations on strings much faster. I was using Python to work with a multi-terabyte newline-delimited file. Reading, splitting, and shuffling it was a nightmare. So, I wrapped a trivial hardware-friendly heuristic I've been using for the last few years into a CPython library. The part I enjoyed the most is implementing SIMD behavior without SIMD instructions... Using 64-bit words to work at 8-bit granularity. Unlike conventional SIMD, the code would remain the same for ~~almost~~ any hardware.…
2023 · ashvardanian.com · its alternatives →
- 12OA
https://github.com/gugarosa/opytimizer Did you ever reach a bottleneck in your computational experiments? Are you tired of selecting suitable parameters for a chosen technique? If yes, Opytimizer is the real deal! This package provides an easy-to-go implementation of meta-heuristic optimizations. From agents to search space, from internal functions to external communication, we will foster all research related to optimizing stuff. Use Opytimizer if you need a library or wish to: - Create your optimization algorithm; - Design or use pre-loaded optimization tasks; -…
2021 · its alternatives →
- 13SA
Hey HN, I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans. It boils down to two main goals: 1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating state changes or getting lost in long procedural scripts. I wanted a library that enforces that "Input -> Transform -> Output" flow by default. 2. Easing the transition to Python: For many…
Feb 2026 · its alternatives →
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Zero-Copy Context Bridging Gateway for Multi-Agent GPU Inference. Bypasses the expensive prefill phase by dynamically stitching KV Caches at the memory level using PagedAttention. Cuts TTFT latency by up to 25x and saves 40%+ VRAM for collaborative LLM workflows. - DaqulaLin/MemStitch
Jul 2026 · github.com · its alternatives →
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Minimal, readable LLM post-training experiments on one 8GB GPU. Measures forgetting, seed variance, and RL emergence. - pochenai/nano-llm-posttraining
Aug 2026 · github.com · its alternatives →
- 16OS
Everyone saw the AlphaEvolve hype. I got obsessed with how it might work under the hood and decided to just build it myself. My setup uses GPT-4.1 to mutate matrix multiplication code, guided by a bunch of hand-crafted mutation strategies (loop reordering, tiling, Strassen, etc.). Each candidate is evaluated on both speed and accuracy. Then I apply Pareto selection with crowding distance to evolve better ones over generations. I ran into all the usual LLM reward hacks-returning the input, calling np.dot, etc. So I forced primitive-only implementations and tightly constrained the mutation…
2025 · its alternatives →
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A finite-state machine library for the Go programming language - calebwin/go-sm
2018 · github.com · its alternatives →
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An Erlang library for carefully refactoring critical paths - sthadka/fuge
2016 · github.com · its alternatives →
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VibeSolve is an open-source tool that turns a plain-English description of an optimisation problem into Timefold code. Mathematical optimisation is a branch of mathematics and computer science that searches for the minimum/maximum of objective functions, and has applications in transport, logistics, scheduling etc. We are exploring where LLMs can add value in optimisation algorithm development, and where they get in the way. Right now, it works well for rapid prototyping. It does not create production-ready code and requires technical skills to use. It is noticeably better at creating…
Jun 2026 · vibesolve.ai · its alternatives →
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Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments. - AgnostiqHQ/covalent
2022 · github.com · its alternatives →
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A high-level, high-performance dynamic programming language
2017 · julialang.org · its alternatives →
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Bayesian CausalImpact for Python — R-compatible Gibbs sampler in Rust (PyO3), 30x faster, no TensorFlow - YuminosukeSato/bsts-causalimpact
Mar 2026 · github.com · its alternatives →
- 23UI
Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
2023 · usearch-images.com · its alternatives →
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Open-source governed, local-first memory control plane for AI agents and teams. arXiv:2608.08253 - qualixar/superlocalmemory
Feb 2026 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →