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Antoni Kozelski

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Antoni Kozelski is an AI entrepreneur and the founder and CEO of Vstorm, a company specializing in custom AI and LLM-based software development.24 He founded Vstorm in October 2017 with the mission to help companies ethically implement AI, enabling growth and innovation.2

Key points about Antoni Kozelski:

  1. Professional background:

    • CEO and co-founder of Vstorm since October 20172
    • Founding partner of Ventures21, a tech-driven venture builder in Europe, since November 20222
  2. Company achievements:

    • Vstorm has served 45+ clients across 9 countries1
    • The company achieved 220% growth in the previous year1
    • Recognized as a 2023 Clutch Champion, placing in the top 10% of companies on the platform1
  3. Education and certifications:

    • Studied Business Administration and Management at Katolicki Uniwersytet Lubelski Jana Pawła II2
    • Holds certifications in Design Thinking from Google and as a Consultant from Mindsonar Polska2
  4. Entrepreneurial journey:

    • Started his entrepreneurial career with $500 and no tech or business background4
    • Now leads a company with millions in revenue, growing 200%+ year-over-year4
  5. Focus areas:

    • Specializes in AI, machine learning, and custom software development3
    • Works with startups, SMEs, and enterprises from the USA, Europe, and the UK4

Antoni Kozelski is committed to leveraging AI to boost company growth for entrepreneurs and intrapreneurs, while also documenting his entrepreneurial journey and sharing insights with others in the field.4

Highlights

Jun 6 · linkedin

🤖 😳

#ai #llms #innovation

🤖 😳 


#ai #llms #innovation
Apr 30 · linkedin

What is RAG? - Retrieval-Augmented Generation

It’s a language model but on steroids. One of the AI solutions for your company

#RAG, or Retrieval-Augmented Generation, is an #artificialintelligence #technology that combines the processes of information retrieval with text generation. This model consists of two main components:

𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐞𝐫: This component is responsible for finding relevant information that can be useful in responding to a user's question. The retriever typically searches a large database or a collection of documents to identify text fragments that are most relevant to the posed query.

𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐨𝐫: After receiving information from the retriever, the generator uses this data to create a coherent and meaningful response. The generator usually relies on machine learning technologies, such as neural networks, to construct responses based on the selected text fragments.

The RAG model is particularly useful in situations where responding to a question requires understanding and integrating information from multiple sources, a challenge for traditional generative models that rely only on a model's internal knowledge.

𝐈𝐧 𝐰𝐡𝐢𝐜𝐡 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐑𝐀𝐆 𝐜𝐚𝐧 𝐛𝐞 𝐚𝐩𝐩𝐥𝐢𝐞𝐝?

In all. Due to its universality, every industry can benefit.

𝐇𝐨𝐰 𝐭𝐨 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐑𝐀𝐆 𝐬𝐢𝐦𝐩𝐥𝐲?

Use it together with GPT (Generative Pre-trained Transformer). By pairing RAG with GPT, you can enhance your system's ability to handle complex questions more effectively. This combination uses the strengths of both technologies: finding relevant information and turning it into clear answers.

RAG represents a significant step forward in making AI more adaptable and insightful across diverse industries. Combining retrieval with generation, ensures more accurate and contextually appropriate responses, enhancing both customer interaction and decision-making processes in any sector.

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Related Questions

What inspired Antoni Kozelski to start Vstorm?
How has Vstorm's growth impacted the tech industry?
What are some notable projects Vstorm has worked on?
How does Vstorm differentiate itself from other AI companies?
What is the mission behind Ventures21, co-founded by Antoni Kozelski?
Antoni Kozelski
Antoni Kozelski, photo 1
Antoni Kozelski, photo 2
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Location

Wroclaw Metropolitan Area