Development of AI Applications with Effect
This article discusses AI integration packages from Effect—a set of tools designed to simplify working with large language models in modern applications. It describes…
Introduction to Large Language Models (LLM)
Applications and Benefits of LLM in IT
Cookbooks" and LLM development guides
We at MWS have launched a language model aggregator, where you can work with multiple LLMs through a single interface. In MWS GPT, the following models are available:…
Don’t you dare rewrite the code? What do you mean?
Yet again, someone on LinkedIn decided to have some fun. They say Elon Musk has decided to rework the US Social Security software in a new way. Oh dear, what a blockheaded…
Replacement of Langchain: How OpenAI Agents SDK Handles Deep Search?
Agents are super buggy. In our company projects, we noticed that Langchain started to perform worse. In multi-agent systems, agents often loop because they don’t understand…
Counting the number of tokens for LLM in the Linux kernel sources and beyond…
This article about the new extension of the transformer architecture – Titan from Google – that allows expanding the limits of LLM to 2 million tokens, prompted me to…
Implementation of LLM in Software Development: Is it Worth It?
Hello, this is Yulia Rogozina, a business process analyst at Sherpa Robotics. Today I translated an article for you, the topic of which concerns the use of Large Language…
Processing of catalog and products on LLM
There is a classic problem on any marketplace related to how to categorize and understand product descriptions. It is especially exacerbated by the fact that users create…
Processing and comparing marketplace products on LLM
There is a classic problem on any e-commerce platform related to how to categorize and understand product descriptions. It is especially exacerbated by the fact that…
Thinking models o1-3: a brief overview and what programmers can expect next
When LLMs first appeared, they were a bit like children - they said the first thing that came to their mind and didn't care much about logic. They needed to be reminded:…
Improving RAG with Knowledge Graphs
Generation with augmented sampling is a method that connects external data sources to improve the output of large language models. This method is ideal for LLM to access…
Speculative Inference Algorithms for LLM
In recent years, the quality of LLM models has significantly improved, quantization methods have become better, and graphics cards more powerful. Nevertheless, the quality…
Basics and advanced techniques of RAG
In this post, we will talk in detail about RAG at each of its stages, its modifications, and its promising directions of development at the time of writing.
Super Ethical Reality: what to consider before using LLM in development
Should we trust something that cannot understand the consequences of its actions? The answer seems obvious, but as the niche of linguistic models develops, we increasingly…
Is there a soul in LLM?
Colleagues, don't argue and don't be afraid - I'm not going to prove the existence or absence of a soul in either robots or humans :) After all, a definition of the soul…
The most advanced LLMs make predictions about their development for 2025
I asked the following question to the most popular LLMs.
Autogeneration of tests for Java/Kotlin in IntelliJ IDEA: comparison of AI tools
For most developers, tests are the least favorite part of the job. Recently, we confirmed this by surveying more than 400 developers at the Joker and Heisenbug conferences…
How the SIBUR Innovation Laboratory is organized and why it is needed
Creating innovations quickly and flexibly can be done in a startup or a small company, but what if you are an industrial giant with more than 25 factories across the…
How LLMs are changing system architecture: from simple data pipelines to intelligent autonomous agents
At every technical conference lately, the word "agents" is sure to be mentioned. They are presented in different ways: as the next step after RAG, as a silver bullet…
