Jul 7, 2025

Functions Are Vectors (2023)

Conceptualizing functions as infinite-dimensional vectors allows the application of linear algebra techniques to diverse fields, including image processing, curve fitting, and machine learning.

Mercury: Ultra-Fast Language Models Based on Diffusion

Mercury introduces a new class of large language models (LLMs) based on diffusion, achieving unprecedented speeds in coding applications with Mercury Coder Mini and Small models.

Anthropic cut up millions of used books, and downloaded 7M pirated ones – judge

Anthropic allegedly utilized pirated millions of books to train its AI model, Claude, raising significant copyright concerns in the tech community.

Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec

Morph enables AI-generated code edits at 4,500+ tokens/sec, eliminating the need for slow full-file rewrites and unreliable search-and-replace methods, thus enhancing developer efficiency.

[R] Energy-Based Transformers are Scalable Learners and Thinkers

Energy-Based Transformers (EBTs) demonstrate the ability to generalize System 2 Thinking through unsupervised learning, enabling them to verify input-prediction compatibility and optimize predictions via energy minimization.

Mirage: First AI-Native UGC Game Engine Powered by Real-Time World Model

Mirage is the first real-time generative engine that allows players to create and modify game worlds dynamically using natural language or input devices, marking a significant advancement in user-generated content (UGC) gameplay.

The Era of Exploration

Large language models (LLMs) are rapidly consuming data, with projections indicating that high-quality English web text may be exhausted within the decade, necessitating a shift towards self-generated data for meaningful AI progress. This transition is termed the “Era of Experience,” where the focus will be on collecting the right experiences rather than merely increasing model parameters.

Show HN: From Photos to Positions: Prototyping VLM-Based Indoor Maps

VLMs can enhance indoor localization by utilizing semantic maps and image recognition, allowing for accurate positioning within complex environments like shopping malls, as demonstrated in a recent prototype project.

[R] Using 'carrier functions' to escape local minima in the loss landscape

Neural Nets' layered structure increases model complexity while risking entrapment in local minima due to strong parameter coupling, which reduces the effective dimensionality of the loss landscape.

Evaluating the factuality of verifiable claims in long-form text generation

VERISCORE is a novel metric that evaluates the factuality of both verifiable and unverifiable claims in long-form text generation, outperforming existing metrics like FACTSCORE and SAFE in human evaluations across eight tasks.

AI Testing and Evaluation: Learnings from pharmaceuticals and medical devices

Generative AI necessitates a reevaluation of governance practices, drawing insights from the rigorous testing and evaluation frameworks used in pharmaceuticals and medical devices to ensure responsible AI development and deployment.

[P] We built this project to increase LLM throughput by 3x. Now it has been adopted by IBM in their LLM serving stack!

Enabling Fully Sharded Data Parallel (FSDP2) in Opacus

Opacus now integrates Fully Sharded Data Parallel (FSDP2) with Fast Gradient Clipping (FGC) and Ghost Clipping (GC), enhancing memory efficiency and scalability for training large models like Llama-3 8B.