Blog

In today's data-driven world, businesses rely heavily on databases to store, manage, and analyze their information. Choosing the right type of database can significantly impact your organization's efficiency, scalability, and overall success. In this article, we offer an overview of various database types and tips on how to choose the right one for your business.

In our Functional Futures podcast episodes, we interview technical leaders from companies that use Haskell for real-world tasks. This season will be dedicated to the business side of development with functional programming. Our guest is Max Tagher, the co-founder and CTO of Mercury, the fintech startups use for banking* and all their financial workflows. Mercury has been using Haskell from the start of the company, from scratch. And our conversation will be dedicated to that. *Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group, Column N.A., and Evolve Bank & Trust, Members FDIC

The TON blockchain has emerged as a robust platform offering scalability, speed, and security. Businesses are increasingly adopting it for the development of decentralized applications (dApps). To take advantage of its full potential, understanding TON's smart contracts is essential. This article is an introduction to TON smart contract development, where we guide you through the essential steps, tools, and best practices needed to get started.

This is the second article in our series “LLMs for Business.” In it, we explore how to fine-tune large language models and use them safely so they don’t harm your business.

The GHC team at Serokell continues its work towards dependent types in Haskell. Our ultimate goal is that Haskell becomes a language where the use of advanced type system features is not just possible but practical. In this report, Serokell's GHC team members Vladislav Zavialov and Andrei Borzenkov describe their recent contributions.

We've seen many articles on large language models (LLMs) aimed at the general public and decision-makers. Many of them are either overly simplistic or, conversely, cover too complicated technical aspects. In our blog post, we take a balanced approach to explaining the essence of LLMs and their fundamental processes. In the first article of a series dedicated to large language models, we discuss their foundational principles and various approaches to running them.