Applied AI Experts Blog

Explore in-depth insights on LLMs, RAG, AI agents, MLOps, Computer Vision, Edge Solutions, Predictive Analytics, and beyond—delivering value-packed perspectives for both business leaders and developers.

  • Hallucinating Reality. An Essay on Business Benefits of Accurate LLMs and LLM Hallucination Reduction Methods

    Hallucinating Reality. An Essay on Business Benefits of Accurate LLMs and LLM Hallucination Reduction Methods

    Robert Bogucki
  • Does Your Model Hallucinate? Tips and Tricks on How to Measure and Reduce Hallucinations in LLMs

    Does Your Model Hallucinate? Tips and Tricks on How to Measure and Reduce Hallucinations in LLMs

    Katarzyna Rutkowska
  • Evaluations, Limitations, and the Future of Web Agents – WebGPT, WebVoyager, Agent-E

    Evaluations, Limitations, and the Future of Web Agents – WebGPT, WebVoyager, Agent-E

    Maks Operlejn
  • Why and How to Build AI Agents for LLM Applications 

    Why and How to Build AI Agents for LLM Applications 

    Alan Konarski
  • AI Copilot’s Impact on Productivity in Revolutionizing Ada Language Development

    AI Copilot’s Impact on Productivity in Revolutionizing Ada Language Development

    deepsense.ai
  • Optimizing Computational Resources for Machine Learning and Data Science Projects: A Practical Approach

    Optimizing Computational Resources for Machine Learning and Data Science Projects: A Practical Approach

    Łukasz Gębala Avatar
  • Implementing Small Language Models (SLMs) with RAG on Embedded Devices Leading to Cost Reduction, Data Privacy, and Offline Use

    Implementing Small Language Models (SLMs) with RAG on Embedded Devices Leading to Cost Reduction, Data Privacy, and Offline Use

    Kamil Czerski
  • From LLMs to RAG. Elevating Chatbot Performance. What is the Retrieval-Augmented Generation System and How to Implement It Correctly?

    From LLMs to RAG. Elevating Chatbot Performance. What is the Retrieval-Augmented Generation System and How to Implement It Correctly?

    Patryk Kowalski
  • Reducing the cost of LLMs with quantization and efficient fine-tuning: how can businesses benefit from Generative AI with limited hardware?

    Reducing the cost of LLMs with quantization and efficient fine-tuning: how can businesses benefit from Generative AI with limited hardware?

    Alicja Kotyla Avatar
  • Achieving accurate image segmentation with limited data: strategies and techniques

    Achieving accurate image segmentation with limited data: strategies and techniques

    Sebastian Chwilczyński
  • 6 AI predictions for 2024 from 6 deepsense.ai experts

    6 AI predictions for 2024 from 6 deepsense.ai experts

    deepsense.ai
  • Data generation with diffusion models. Part 3: Generating custom data in the blink of an eye

    Data generation with diffusion models. Part 3: Generating custom data in the blink of an eye

    Marianna Parzych
  • Llama 2. A significant milestone in the world of AI

    Llama 2. A significant milestone in the world of AI

    Dawid Stachowiak
  • deepsense.ai among top 50 AI providers in CEE

    deepsense.ai among top 50 AI providers in CEE

    deepsense.ai
  • Evaluation Derangement Syndrome (EDS) in the GPU-poor’s GenAI. Part 1: the case for Evaluation-Driven Development

    Evaluation Derangement Syndrome (EDS) in the GPU-poor’s GenAI. Part 1: the case for Evaluation-Driven Development

    deepsense.ai
  • Creating your own code writing agent. How to get results fast and avoid the most common pitfalls

    Creating your own code writing agent. How to get results fast and avoid the most common pitfalls

    Alan Konarski
  • LangChain announces partnership with deepsense.ai

    LangChain announces partnership with deepsense.ai

    deepsense.ai
  • Creating your whole codebase at once using LLMs – how long until AI replaces human developers?

    Creating your whole codebase at once using LLMs – how long until AI replaces human developers?

    Alan Konarski
  • Standard Template for Machine Learning projects – deepsense.ai’s approach

    Standard Template for Machine Learning projects – deepsense.ai’s approach

    deepsense.ai
  • Generative AI developer toolkit

    Generative AI developer toolkit

    Paweł Kmiecik
  • deepsense.ai contributes to open source tool PR-Agent

    deepsense.ai contributes to open source tool PR-Agent

    deepsense.ai
  • Operationalizing Large Language Models: How LLMOps can help your LLM-based applications succeed

    Operationalizing Large Language Models: How LLMOps can help your LLM-based applications succeed

    Mateusz Kwaśniak
  • How to efficiently implement LLMs in your business operations

    How to efficiently implement LLMs in your business operations

    deepsense.ai
  • Data generation with diffusion models – part 2

    Data generation with diffusion models – part 2

    Natalia Czerep Avatar
  • Diffusion models in practice. Part 3: Portrait generation analysis

    Diffusion models in practice. Part 3: Portrait generation analysis

    Jarosław Kochanowicz Avatar
  • deepsense.ai teamed up with WWF to protect Poland’s river ecosystems

    deepsense.ai teamed up with WWF to protect Poland’s river ecosystems

    deepsense.ai
  • OpenAI LLM APIs: OpenAI or Microsoft Azure?

    OpenAI LLM APIs: OpenAI or Microsoft Azure?

    deepsense.ai
  • How we developed a GPT‑based solution for extracting knowledge from documents

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

    deepsense.ai
  • deepsense.ai’s new office in Warsaw

    deepsense.ai’s new office in Warsaw

    deepsense.ai
  • deepsense.ai at SQLDay

    deepsense.ai at SQLDay

    deepsense.ai