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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 models /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

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

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

This guide 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 17:22:132023-03-24 11:49:57Guide: 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 models /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?
How to leverage ChatGPT to boost marketing strategy

How to leverage ChatGPT to boost marketing strategy?

February 26, 2023/in Generative models /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 models /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
Paramount factors in successful machine learning projects. Part 2/2

Paramount factors in successful machine learning projects. Part 2/2

January 9, 2023/in Machine learning /by Robert Bogucki and Jan Kanty Milczek

In the first part of our guide we focused on properly executing the entire process of building and implementing machine learning models with a focus on the main goal – solving the overarching business challenge. In the second part of our material we dig deeper into the topic of modeling.

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https://deepsense.ai/wp-content/uploads/2022/12/Paramount-factors-in-successful-machine-learning-projects-part-2.jpeg 337 1140 Robert Bogucki https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Robert Bogucki2023-01-09 07:00:302023-01-09 09:27:36Paramount factors in successful machine learning projects. Part 2/2
How to perform self-supervised learning on high-dimensional data

How to perform self-supervised learning on high-dimensional data

October 28, 2022/in Computer vision, Artificial Intelligence, Machine learning /by Łukasz Kuśmierz

In this post, the self-supervised learning paradigm is discussed. This method of training machine learning models is emerging nowadays, especially for high-dimensional data. In order to focus the attention of this article, we will only work on examples from the computer vision area. However, the methods presented are general and may be successfully used for problems from other domains as well.

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https://deepsense.ai/wp-content/uploads/2022/10/How-to-perform-self-supervised-learning-on-high-dimensional-data.jpeg 337 1140 Łukasz Kuśmierz https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Łukasz Kuśmierz2022-10-28 10:00:502023-03-06 23:45:43How to perform self-supervised learning on high-dimensional data
The recent rise of diffusion-based models

The recent rise of diffusion-based models

September 5, 2022/in Generative models /by Maciej Domagała

In this post, we will sum up the very recent history of solving the text-to-image generation problem and explain the latest developments regarding diffusion models, which are playing a huge role in the new, state-of-the-art architectures.

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https://deepsense.ai/wp-content/uploads/2022/07/The-recent-rise-of-diffusion-based-models.jpeg 337 1140 Maciej Domagała https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Maciej Domagała2022-09-05 08:00:592023-02-26 21:57:37The recent rise of diffusion-based models
Five solid reasons to outsource your AI software development

Five solid reasons to outsource your AI software development

August 21, 2022/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.ai2022-08-21 10:43:502022-08-21 10:46:51Five solid reasons to outsource your AI software development
Data Science with Graphs - using knowledge graphs on the data before it reaches the ML phase

Data Science with Graphs – using knowledge graphs on the data before it reaches the ML phase

June 11, 2022/in Machine learning /by Grzegorz Rybak

Graph usage in AI recently became quite evident with an increased number of research papers and some impressive examples among the industry . This article aims to answer the question: Are there ways to improve a project’s delivery by using graphs even before reaching GraphML?

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https://deepsense.ai/wp-content/uploads/2022/06/Data-Science-with-Graphs-using-knowledge-graphs-on-the-data-before-it-reaches-the-ML-phase.jpeg 337 1140 Grzegorz Rybak https://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svg Grzegorz Rybak2022-06-11 10:19:332023-02-05 20:23:47Data Science with Graphs – using knowledge graphs on the data before it reaches the ML phase
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