Contact us
Locations
United States of America
- deepsense.ai, Inc.
- 2100 Geng Road, Suite 210
- Palo Alto, CA 94303
- United States of America
Poland
- deepsense.ai Sp. z o.o.
- al. Jerozolimskie 44
- 00-024 Warsaw
- Poland
- ul. Łęczycka 59
- 85-737 Bydgoszcz
- Poland
Let us know how we can help
- Our service offerings
- contact@deepsense.ai
- Media relations
- media@deepsense.ai
Creating your own code writing agent. How to get results fast and avoid the most common pitfalls
/in Generative AI /by Alan Konarski, Maks Operlejn and Patryk KowalskiDelve into this comprehensive guide to learn how to create your own code-writing agents, while understanding the possible limitations. Read now!
Creating your whole codebase at once using LLMs – how long until AI replaces human developers?
/in Generative AI /by Alan Konarski, Maks Operlejn and Patryk KowalskiFind out how coding agents in LLMs are spearheading advancements in AI development. Learn more about the most popular examples of code-writing agents!
Standard Template for Machine Learning projects – deepsense.ai’s approach
/in Machine learning /by Piotr GródekWant to find out how to effectively standardize your ML project? Here, we present our approach to creating a Machine Learning project template. Learn more!
Generative AI developer toolkit
/in Generative AI /by Paweł KmiecikA thrilling adventure in the world of next-gen programming awaits, powered not by replacing humans with AI, but by using AI to enhance human potential. In this blog post we will discuss the most interesting and powerful GenAI tools that you should know more about.
Operationalizing Large Language Models: How LLMOps can help your LLM-based applications succeed
/in Generative AI /by Mateusz KwaśniakIn this blog post we will discuss the importance of LLMOps principles and best practices, which will enable you to take your existing or new machine learning projects to the next level.
How to efficiently implement LLMs in your business operations
/in Generative AI /by deepsense.aiA comprehensive guide to incorporating Large Language Models into your company for increased efficiency and business value.
Data generation with diffusion models – part 2
/in Generative AI /by Natalia CzerepOne of the most challenging tasks in data generation with diffusion models is generating labels intended for semantic segmentation. At deepsense.ai, we have embraced the challenge of devising a novel approach that simultaneously generates images complete with precise segmentation masks. We are sharing the results of our work in this blog post.
Diffusion models in practice. Part 3: Portrait generation analysis
/in Generative AI /by Jarosław Kochanowicz, Dawid Stachowiak, Jan Woś, Maciej Domagała and Dawid ŻywczakIn this blog post, we empirically investigated portrait generation using diffusion models. Imitating human evaluation, we objectively measured aspects usually left to subjective manual checks and arbitrary decisions.
How we developed a GPT‑based solution for extracting knowledge from documents
/in Generative AI /by Piotr GródekIn this blogpost we will discuss our latest GPT-based solution addressing the challenge of extracting knowledge from a set of PDF documents.
OpenAI LLM APIs: OpenAI or Microsoft Azure?
/in Generative AI /by Patryk WyżgowskiIn this article, we share our insights related to two main ways of accessing the OpenAI models, both directly from the organization’s API and via Microsoft Azure OpenAI Service.