Articles for category: AI Tools

Benchmarking Large Language Models in Healthcare

Over the years, Large Language Models (LLMs) have emerged as a groundbreaking technology with immense potential to revolutionize various aspects of healthcare. These models, such as GPT-3, GPT-4 and Med-PaLM 2 have demonstrated remarkable capabilities in understanding and generating human-like text, making them valuable tools for tackling complex medical tasks and improving patient care. They have notably shown promise in various medical applications, such as medical question-answering (QA), dialogue systems, and text generation. Moreover, with the exponential growth of electronic health records (EHRs), medical literature, and patient-generated data, LLMs could help healthcare professionals extract valuable insights and make informed decisions.

Image search is now live!

After finishing the image classification API, I wondered if I could go further. How about building a reverse image search engine? You can try it out here: Image Search API. (Github repositiory) Update: API discontinued to save on cloud cost. This is part of a series of posts on building a product classification API: What is reverse image search? In simple terms, given an image, reverse image search finds other similar images—this would be helpful in searching for similar looking products. How do I use it? “My son has this plushie he really likes, but I don’t know what the

How Measurement Elevation and Aggregation Change Behaviors

The costs of measuring the wrong thing or the right things in the wrong way vastly outweigh the costs of collecting and processing the data. In software delivery, conversations about metrics and measurement wax and wane as people discover useful techniques or get hurt by unintended consequences. Understanding how measurement elevation and aggregation levels change people’s behaviors and business outcomes will help you create a healthier metrics system that better informs your decisions. The Economics of Measurement A measurement system is subject to economics. There is a cost of collecting data and a value in using it. The economics, particularly

Jack of All Trades, Master of Some, a Multi-Purpose Transformer Agent

We’re excited to share Jack of All Trades (JAT), a project that aims to move in the direction of a generalist agent. The project started as an open reproduction of the Gato (Reed et al., 2022) work, which proposed to train a Transformer able to perform both vision-and-language and decision-making tasks. We thus started by building an open version of Gato’s dataset. We then trained multi-modal Transformer models on it, introducing several improvements over Gato for handling sequential data and continuous values. Overall, the project has resulted in: The release of a large number of expert RL agents on a

Product Categorization API Part 3: Creating an API

This post is part 3—and the last—of the series on building a product classification API. The API is available for demo here. Part 1 and 2 are available here and here. (Github repositiory) Update: API discontinued to save on cloud cost. In part 1, we focused on acquiring the data, and cleaning and formatting the categories. Then in part 2, we cleaned and prepared the product titles (and short description) before training our model on the data. In this post, we’ll focus on writing a custom class for the API and building an app around it. This is part of

Unlock Cursor AI for FREE: 4 Secret Methods Revealed!

Are you tired of hitting paywalls while trying to boost your coding productivity? The struggle is real—Cursor AI offers game-changing assistance for developers, but those premium features behind the Pro membership can leave your wallet feeling lighter. What if I told you there’s a way to access those coveted capabilities without opening your wallet? Today, I’m pulling back the curtain on four insider techniques that savvy developers are using to harness Cursor AI’s full potential—completely free of charge: Maximizing Cursor’s Free Tier (The Official Method) Resetting Your Pro Trial (The Time-Bending Approach) Bypassing Membership Verification (The VIP Shortcut) Leveraging Open-Source

Introducing the Open Chain of Thought Leaderboard

Chain-of-thought prompting is emerging as a powerful and effective design pattern for LLM-based apps and agents. The basic idea of chain-of-thought prompting is to let a model generate a step-by-step solution (“reasoning trace”) before answering a question or taking a decision. With the Open CoT Leaderboard we’re tracking LLMs’ ability to generate effective chain-of-thought traces for challenging reasoning tasks. Unlike most performance based leaderboards, we’re not scoring the absolute accuracy a model achieves on a given task, but the difference between the accuracy with and without chain-of-thought prompting: accuracy gain Δ = accuracy with CoT – accuracy w/o CoT. This

One way to help a data science team innovate successfully

The Lazada Data Science team has paper lunches together every Friday. Usually, we discuss about new papers we read, new ideas and implementations we tried, etc. This past Friday, we invited some special guests from Aviva to discuss about our journeys in cultivating a data-driven culture and building data science into the organization. One of the guests, who is in charge of technology, mentioned something interesting. Some can transition successfully from traditional actuarial statistics to customer-based data science—but most fail Aviva is very strong in what most would consider traditional aspects of data science involving risk, actuarial statistics, etc (it’s