New embedding models and API updates
We are launching a new generation of embedding models, new GPT-4 Turbo and moderation models, new API usage management tools, and soon, lower pricing on GPT-3.5 Turbo.
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This AI Paper Introduces PirateNets: A Novel AI System Designed to Facilitate Stable and Efficient Training of Deep Physics-Informed Neural Network Models
With the world of computational science continually evolving, physics-informed neural networks (PINNs) stand out as a groundbreaking approach for tackling forward and inverse problems governed by partial differential equations (PDEs). These models incorporate physical laws into the learning process, promising a significant leap in predictive accuracy and robustness. But as PINNs grow in depth and…
IBM AI Research Introduces Unitxt: An Innovative Library For Customizable Textual Data Preparation And Evaluation Tailored To Generative Language Models
Though it has always played an essential part in natural language processing, textual data processing now sees new uses in the field. This is especially true when it comes to LLMs’ function as generic interfaces; these interfaces take examples and general system instructions, tasks, and other specifications expressed in natural language. As a result, there…
Language Bias, Be Gone! CroissantLLM’s Balanced Bilingual Approach is Here to Stay
In an era where language models (LMs) predominantly cater to English, a revolutionary stride has been made with the introduction of CroissantLLM. This model bridges the linguistic divide by offering robust bilingual capabilities in both English and French. This development marks a significant departure from conventional models, often biased towards English, limiting their applicability in…
Weak-to-strong generalization
ByWeb Dev
We present a new research direction for superalignment, together with promising initial results: can we leverage the generalization properties of deep learning to control strong models with weak supervisors?
Revolutionizing Fluid Dynamics: Integrating Physics-Informed Neural Networks with Tomo-BOS for Advanced Flow Analysis
Background Oriented Schlieren (BOS) imaging is an effective technique for visualizing and quantifying fluid flow. BOS is cost-effective and flexible, unlike other methods like Particle Image Velocimetry (PIV) and Laser-Induced Fluorescence (LIF). It relies on the distortion of objects in a density-varying medium due to light refraction, with digital image correlation or optical flow algorithms…
Fireworks AI Open Sources FireLLaVA: A Commercially-Usable Version of the LLaVA Model Leveraging Only OSS Models for Data Generation and Training
A variety of Large Language Models (LLMs) have demonstrated their capabilities in recent times. With the constantly advancing fields of Artificial Intelligence (AI), Natural Language Processing (NLP), and Natural Language Generation (NLG), these models have evolved and have stepped into almost every industry. In the growing field of AI, it has become essential to have…
