Lattice Labs
Infrastructure for training and serving open models efficiently.
Repositories · 39
SciML/ReservoirComputing.jl
Reservoir computing utilities for scientific machine learning (SciML)
sylvaticus/BetaML.jl
Beta Machine Learning Toolkit
lone-cloud/gerbil
A desktop app for running Large Language Models locally.
google/grain
Library for reading and processing ML training data.
ml-tooling/best-of-jupyter
🏆 A ranked list of awesome Jupyter Notebook, Hub and Lab projects (extensions, kernels, tools). Updated weekly.
meshery-extensions/tcslabs-academy
Meshery Academy for TCS Labs
OpenSTEF/openstef
Automated Machine Learning pipelines. Builds the Open Short Term Energy Forecasting package.
marc-shade/Ollama-Workbench
A comprehensive platform for managing, testing, and leveraging Ollama AI models with advanced features for customization, workflow automation, and collaborative development.
News · 10
DeepSeek open sources DSpark, a new framework to speed up LLM inference by up to 85%
<p>Even as the geopolitical conversation around AI continues to grow more fraught following the<a href="https://venturebeat.com/technology/anthropic-blocks-all-public-access-to-claude-fable-5-mythos-5-following-us-government-order-what-enterprises-should-do"> U.S. government's actions to limit the new models from Anthropic</a> and <a href="https://venturebeat.com/technology/openai-unveils-gpt-5-6-sol-terra-and-luna-models-but-only-accessible-to-limited-preview-partners-for-now-per-us-gov">O
Predicting model behavior before release by simulating deployment
OpenAI introduces Deployment Simulation, a method to predict AI model behavior before deployment using real conversation data to improve safety and evaluation accuracy.
My reasons to run local models
<!-- SC_OFF --><div class="md"><ul> <li>I can finetune any model on any dataset I want.</li> <li>I can use techniques like speculative decoding and other sota approaches to get the max tps</li> <li>The llm provides like anthropic and openai are not getting access to my data</li> <li>The hardware is reusable for vision text speech, and I can run any blend of models for free as much as I want</li> <li>I can curate any dataset/content that I want without worrying about the costs</li> <li>I like wat
State of Open Models: Summer 2026 Observations
Major lab releases open weights for a frontier model
The release includes the base and instruct checkpoints under a permissive license.
Hypothetically speaking...
<!-- SC_OFF --><div class="md"><p>Would it not be possible to create crowd sourced, truly open sourced distilled LLMs with a simple wrapper around command line based AI services that exist today?</p> <p>I'm imagining a layer that goes around whatever application people currently use for coding/AI boyfriend that collects your inputs and associates them with your outputs. With enough volunteers doing this, you could create huge data sets. I understand training these models requires massive compute
IEEE Rolls Out Large Language Models Virtual Training Course
<img src="https://spectrum.ieee.org/media-library/a-middle-aged-black-man-taking-a-virtual-coding-class-in-his-home-office.jpg?id=66951841&width=1245&height=700&coordinates=0%2C156%2C0%2C157" /><br /><br /><p><a href="https://spectrum.ieee.org/recursive-self-improvement" target="_self">Large language models</a> have moved out of the research lab and into engineers’ daily workflow. LLMs serve as reasoning engines that can orchestrate complex tasks including identifying vulnerabilities