In 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.
https://deepsense.ai/wp-content/uploads/2023/05/How-we-integrated-GPT-with-PDF-documents.jpeg3371140Piotr Gródekhttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngPiotr Gródek2023-05-26 21:58:112023-11-21 16:25:43How we developed a GPT‑based solution for extracting knowledge from documents
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?
https://deepsense.ai/wp-content/uploads/2023/04/Diffusion-models-in-practice.-Part-2-How-good-is-your-model.jpeg3371140Jarosław Kochanowiczhttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngJarosław Kochanowicz2023-05-08 07:35:572023-06-28 09:47:53Diffusion models in practice. Part 2: How good is your model?
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.
https://deepsense.ai/wp-content/uploads/2023/04/How-to-train-a-large-language-model-using-limited-hardware.jpeg3371140Alicja Kotylahttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngAlicja Kotyla2023-04-17 08:00:402023-10-11 11:29:56How to train a Large Language Model using limited hardware?
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.
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.
https://deepsense.ai/wp-content/uploads/2023/03/Diffusion-models-in-practice.-Part-1-The-tools-of-the-trade.jpeg3371140Jarosław Kochanowiczhttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngJarosław Kochanowicz2023-03-29 08:00:582023-08-20 12:26:17Diffusion models in practice. Part 1: A primers
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.jpeg3371140Artur Zygadlohttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngArtur 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
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.
https://deepsense.ai/wp-content/uploads/2023/03/ChatGPT-–-what-is-the-buzz-all-about.jpeg5681920Eryk Mazuśhttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngEryk Mazuś2023-03-10 10:00:182023-11-14 16:27:49ChatGPT – what is the buzz all about?
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.
https://deepsense.ai/wp-content/uploads/2022/08/Five-solid-reasons-to-outsource-your-AI-software-development.jpeg3371140deepsense.aihttps://deepsense.ai/wp-content/uploads/2023/10/Logo_black_blue_CLEAN_rgb.pngdeepsense.ai2023-03-04 10:43:502023-10-04 15:48:575 solid reasons to outsource your AI software development
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.
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.
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.
Diffusion models in practice. Part 2: How good is your model?
/in Generative AI /by Jarosław Kochanowicz, Maciej Domagała, Dawid Stachowiak and Dawid ŻywczakThis 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?
How to train a Large Language Model using limited hardware?
/in Generative AI /by Alicja KotylaLarge 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.
Data generation with diffusion models – part 1
/in Generative AI /by Natalia CzerepIt 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.
Diffusion models in practice. Part 1: A primers
/in Generative AI /by Jarosław Kochanowicz, Maciej Domagała, Dawid Stachowiak and Krzysztof DziedzicThe 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.
Report: The diverse landscape of large language models. From the original Transformer to GPT-4 and beyond
/in Generative AI /by Artur ZygadloThis report is an attempt to explain and summarize the diverse landscape of LLMs in early 2023.
ChatGPT – what is the buzz all about?
/in Generative AI /by Eryk Mazuś and Maciej DomagałaOver 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.
5 solid reasons to outsource your AI software development
/in Artificial Intelligence /by deepsense.aiCustomized 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.
How to leverage ChatGPT to boost marketing strategy?
/in Generative AI /by Ewa SzkudlarekThe 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.