The industry spent two years teaching LLMs to speak JSON. That work mattered: free-form text was unusable in production. Today, every serious inference provider uses some implementation (often open-source) of structured output. Structured output has become essential infrastructure that the team at .txt is proud to have spearheaded. Even as the ecosystem evolves, and open-source alternatives emerged, our engine remains the state of the art.
The control layer for AI
The industry spent two years teaching LLMs to speak JSON. That work mattered: free-form text was unusable in production. Today, every serious inference provider uses some implementation (often open-source) of structured output. Structured output has become essential infrastructure that the team at .txt is proud to have spearheaded. Even as the ecosystem evolves, and open-source alternatives emerged, our engine remains the state of the art.
Structured Outputs with Will Kurt and Cameron Pfiffer - Weaviate Podcast #119!
make ai speak computer by dottxt @ Nouscon 2024
Sakana AI on Twitter / X
We’re excited to introduce Text-to-LoRA: a Hypernetwork that generates task-specific LLM adapters (LoRAs) based on a text description of the task. Catch our presentation at #ICML2025!Paper: https://t.co/2FRiVF1UXJCode: https://t.co/rx4G7dq1SWBiological systems are capable of… pic.twitter.com/UdUYfqRXBS— Sakana AI (@SakanaAILabs) June 12, 2025
Large language model
A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots.[1] Biased or inaccurate training data can make an LLM's output less reliable.[2]
Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First
Large Language Model (LLM) agents, acting on their users' behalf to manipulate and analyze data, are likely to become the dominant workload for data systems in the future. When working with data,...
Big AI is accelerating the metacrisis: What can we do?
The world is in the grip of ecological, meaning, and language crises that are converging into a metacrisis. Big AI is accelerating them all. LLM engineering sits at the core. Despite the public good motives of language engineers and the promise of LLMs, this work is being leveraged to create unprecedented wealth and power for a handful of individuals and corporations while causing existential harm to life on earth. As a profession, we urgently need to come together to explore alternatives and to design a life-affirming future for our field of natural language processing that is centered on human flourishing on a living planet.
DeepL AI Platform: Translation, Voice & API
Explore our AI suite and get more done: Translate speech, text, and media, or integrate the DeepL API.
Stevens: a hackable AI assistant using a single SQLite table and a handful of cron jobs
There’s a lot of hype these days around patterns for building with AI. Agents, memory, RAG, assistants—so many buzzwords! But the reality is, you don’t need fancy techniques or libraries to build useful personal tools with LLMs.
The Kaitchup – AI on a Budget | Benjamin Marie | Substack
Weekly tutorials and news on adapting large language models (LLMs) to your tasks and hardware using the most recent techniques and models. The Kaitchup proposes a collection of 180+ AI notebooks regularly updated. Click to read The Kaitchup – AI on a Budget, by Benjamin Marie, a Substack publication with tens of thousands of subscribers.
There are no lossless transformations of natural-language text
In my work at Clay I recently wrote an internal policy on acceptable use of AI writing by engineers, and I’m sharing it here. It’s my hope that one day better AI tools might be able to help us think, but until then I fear that using AI to write does the exact opposite.
Writing with AI help can shift your opinions | Cornell Chronicle
Artificial intelligence-powered writing assistants that autocomplete sentences or offer “smart replies” not only put words into people’s mouths, they also put ideas into their heads, according to new research.
Andrej Karpathy Stopped Using AI to Write Code. He’s Using It to Build a Second Brain Instead
His new workflow turns raw research into a self-maintaining wiki.No vector databases, no RAG pipelines, just markdown files and an LLM that…
AI code and software craft - alex wennerberg
Much has been said about audio, video and text "slop": low-quality, AI-generated content that has proliferated on the internet since the release of publicly-accessible AI models. Garbage content has always existed online, but the novelty of AI is that it has made its generation orders of magnitude less labor-intensive. For anyone who lacks a discerning eye, or is doing some task where discernment simply does not matter, AI has become a sufficient replacement for human hands.
AI Agents: Key Concepts and How They Overcome LLM Limitations
An AI agent is an autonomous software entity that is often used to augment a large language model. Here's what developers need to know.
