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How we integrated GPT with PDF documents

How we developed a GPT‑based solution for extracting knowledge from documents

May 26, 2023/in Generative AI /by Piotr Gródek

In this blogpost we will discuss our latest GPT-based solution addressing the challenge of extracting knowledge from a set of PDF documents.

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https://deepsense.ai/wp-content/uploads/2023/05/How-we-integrated-GPT-with-PDF-documents.jpeg 337 1140 Piotr Gródek https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Piotr Gródek2023-05-26 21:58:112023-05-29 16:02:51How we developed a GPT‑based solution for extracting knowledge from documents
Diffusion models in practice. Part 2: How good is your model?

Diffusion models in practice. Part 2: How good is your model?

May 8, 2023/in Generative AI /by Jarosław Kochanowicz, Maciej Domagała, Dawid Stachowiak and Dawid Żywczak

This is the second post in our series “Diffusion models in practice”. In this article, we start our journey into the practical aspects of diffusion modeling, which we found even more exciting. First, we would like to address a fundamental question that arises when one begins to venture into the realm of generative models: Where to start?

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https://deepsense.ai/wp-content/uploads/2023/04/Diffusion-models-in-practice.-Part-2-How-good-is-your-model.jpeg 337 1140 Jarosław Kochanowicz https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Jarosław Kochanowicz2023-05-08 07:35:572023-05-08 11:03:22Diffusion models in practice. Part 2: How good is your model?
How to train a large language model using limited hardware?

How to train a large language model using limited hardware?

April 17, 2023/in Generative AI /by Alicja Kotyla

Large language models (LLMs) are yielding remarkable results for many NLP tasks, but training them is challenging due to the demand for a lot of GPU memory and extended training time. To address these challenges, various parallelism paradigms have been developed, along with memory-saving techniques to enable the effective training of LLMs. In this article, we will describe these methods.

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https://deepsense.ai/wp-content/uploads/2023/04/How-to-train-a-large-language-model-using-limited-hardware.jpeg 337 1140 Alicja Kotyla https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Alicja Kotyla2023-04-17 08:00:402023-04-17 12:06:16How to train a large language model using limited hardware?
Data generation with diffusion models - part 1

Data generation with diffusion models – part 1

April 3, 2023/in Generative AI /by Natalia Czerep

It is widely known that computer vision models require large amounts of data to perform well. Unfortunately, in many business cases we are left with a small amount of data. There are several approaches to overcoming the issue of insufficient data, one of which is supplementing the available dataset with new images, which is discussed in this article.

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https://deepsense.ai/wp-content/uploads/2023/04/Data-generation-with-diffusion-models-part-1.jpeg 337 1140 Natalia Czerep https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Natalia Czerep2023-04-03 08:00:192023-04-03 11:26:21Data generation with diffusion models – part 1
Diffusion models in practice. Part 1 - The tools of the trade

Diffusion models in practice. Part 1: The tools of the trade

March 29, 2023/in Generative AI /by Jarosław Kochanowicz, Maciej Domagała, Dawid Stachowiak and Krzysztof Dziedzic

The AI revolution continues, and there is no indication of it nearing the finish line. The last year has brought astonishing developments in two critical areas of generative modeling: large language models and diffusion models.

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https://deepsense.ai/wp-content/uploads/2023/03/Diffusion-models-in-practice.-Part-1-The-tools-of-the-trade.jpeg 337 1140 Jarosław Kochanowicz https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Jarosław Kochanowicz2023-03-29 08:00:582023-03-29 10:26:33Diffusion models in practice. Part 1: The tools of the trade
Solution guide - The diverse landscape of large language models. From the original Transformer to GPT-4 and beyond

Report: The diverse landscape of large language models. From the original Transformer to GPT-4 and beyond

March 22, 2023/in Generative AI /by Artur Zygadlo

This report is an attempt to explain and summarize the diverse landscape of LLMs in early 2023.

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https://deepsense.ai/wp-content/uploads/2023/03/Solution-guide-The-diverse-landscape-of-large-language-models.-From-the-original-Transformer-to-GPT-4-and-beyond.jpeg 337 1140 Artur Zygadlo https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Artur Zygadlo2023-03-22 17:22:132023-04-24 11:48:06Report: The diverse landscape of large language models. From the original Transformer to GPT-4 and beyond
ChatGPT – what is the buzz all about?

ChatGPT – what is the buzz all about?

March 10, 2023/in Generative AI /by Eryk Mazuś and Maciej Domagała

Over the last few months, ChatGPT has generated a great deal of excitement. Some have gone as far as to suggest it is a giant step in developing AI that will overtake humanity in many important areas, both in business and social life. Others view it more as a distraction on the path towards achieving human-level intelligence. How did ChatGPT generate such hype? In this article, we’ll try to explain.

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https://deepsense.ai/wp-content/uploads/2023/03/ChatGPT-–-what-is-the-buzz-all-about.jpeg 568 1920 Eryk Mazuś https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Eryk Mazuś2023-03-10 10:00:182023-03-10 15:31:11ChatGPT – what is the buzz all about?
Five solid reasons to outsource your AI software development

Five solid reasons to outsource your AI software development

March 4, 2023/in Artificial Intelligence /by deepsense.ai

Customized AI software development is one of the most powerful approaches to leveraging AI in business. Undoubtedly, the main difficulty of this approach is the ability to successfully develop and implement AI projects. Cooperation with an experienced AI vendor, who is responsible for end-to-end delivery, is one of the most effective solutions, bringing with it a number of benefits.

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https://deepsense.ai/wp-content/uploads/2022/08/Five-solid-reasons-to-outsource-your-AI-software-development.jpeg 337 1140 deepsense.ai https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg deepsense.ai2023-03-04 10:43:502023-04-15 14:12:52Five solid reasons to outsource your AI software development
How to leverage ChatGPT to boost marketing strategy

How to leverage ChatGPT to boost marketing strategy?

February 26, 2023/in Generative AI /by Ewa Szkudlarek

The revolution in marketing is happening before our very eyes. The latest developments in the area of generative models mark a milestone where artificial intelligence and human expertise have come together like never before, and the use of AI in marketing is no longer just a buzzword. With ChatGPT and other large language models, marketers will be able to harness the power of AI in an easy way.

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https://deepsense.ai/wp-content/uploads/2023/02/How-to-leverage-ChatGPT-to-boost-marketing-strategy.jpeg 337 1140 Ewa Szkudlarek https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Ewa Szkudlarek2023-02-26 21:41:222023-02-26 21:47:07How to leverage ChatGPT to boost marketing strategy?
How can we improve language models using reinforcement learning? ChatGPT case study

How can we improve language models using reinforcement learning? ChatGPT case study

February 20, 2023/in Generative AI /by Kinga Prusinkiewicz

ChatGPT is a cutting-edge natural language processing model released in November 2022 by OpenAI. It is a variant of the GPT-3 model, specifically designed for chatbot and conversational AI applications.

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https://deepsense.ai/wp-content/uploads/2023/02/How-can-we-improve-language-models-using-reinforcement-learning-ChatGPT-case-study.jpeg 337 1140 Kinga Prusinkiewicz https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Kinga Prusinkiewicz2023-02-20 07:00:452023-03-13 16:49:54How can we improve language models using reinforcement learning? ChatGPT case study
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