TechCrunch Minute: Meta’s new Llama 3 models give open-source AI a boost

New AI models from Meta are making waves in technology circles. The two new models, part of the Facebook parent company’s Llama line of artificial intelligence tools, are both open-source, helping them stand apart from competing offerings from OpenAI and other well-known names. Meta’s new Llama models have differently sized underlying datasets, with the Llama … Read more

Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 2

In Part 1 of this series, we presented a solution that used the Amazon Titan Multimodal Embeddings model to convert individual slides from a slide deck into embeddings. We stored the embeddings in a vector database and then used the Large Language-and-Vision Assistant (LLaVA 1.5-7b) model to generate text responses to user questions based on … Read more

Scale AI training and inference for drug discovery through Amazon EKS and Karpenter

This is a guest post co-written with the leadership team of Iambic Therapeutics. Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. Our advanced generative and predictive artificial intelligence (AI) tools enable us to search the vast space of possible drug … Read more

Everything You Need To Know About TypeScript

From Fundamentals to Intermediate Techniques for Effective Developmen TypeScript is an open-source programming language developed by Microsoft that builds upon JavaScript by adding optional static typing, interfaces, classes, and other features to help developers write robust and scalable code. It compiles to plain JavaScript, making it compatible with existing JavaScript frameworks and libraries, while providing … Read more

Using the Stratification Method for the Experiment Analysis

Any experiment involves a trade-off between fast results and metric sensitivity. If the chosen metric is wide in terms of variance, we must wait a long time to ensure the experiment’s results are accurate. Let’s consider one method to help analysts boost their experiments without losing too much time or metric sensitivity. Problem Formulation Suppose … Read more

Variational Non-Bayesian Inference of the Probability Density Function: Conclusion & References

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more

Variational Non-Bayesian Inference of the Probability Density: Characterization of Coefficients

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more

Variational Non-Bayesian Inference: Generalized Wiener Algebra and Fréchet Derivative

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more

Variational Non-Bayesian Inference: Coefficients From an Ergodic Process

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more

Variational Non-Bayesian Inference of the Probability Density Function: Introduction

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more

Variational Non-Bayesian Inference: Problem Setting and Preliminaries

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more

Variational Non-Bayesian Inference of the Probability Density Function: Organization and Notation

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; (2) Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr. ::: Table of Links Introduction Organization and notation Problem Setting and Preliminaries Generalized … Read more