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Generative AI Research and Learnings

Top ChatGPT Prompts and Prompt Engineering for Product Managers
von Nina Habicht 10 Mai, 2024
Top ChatGPT Prompts and Prompt Engineering for Product Managers
How Does Perplexity AI Work?
von Nina Habicht 04 Mai, 2024
Article about Perplexity AI and how to properly use it. We highlight the difference between ChatGPT and Perplexity AI.
How to choose between ChatGPT, Claude, Copilot and Gemini
von Nina Habicht 04 Mai, 2024
How to choose between ChatGPT, Claude, Copilot and Gemini. Please find our ultimate guideline on how the models differ and which llm is strong at which task.
How to strategically use GPTs from OpenAI
von Nina Habicht 03 Mai, 2024
This blog explains how gpts can be used as a part of your Generative AI journey and exploration towards your Ai strategy.
Why implementing ai tools is not an ai strategy
von Nina Habicht 03 Mai, 2024
This post explains why implementing ai tools without any strategy and business view can be detrimental and lead to not successful ai projects.
Generative AI in 2024, Investment areas in 2024
von Nina Habicht 01 Jan., 2024
This post is abou the major generative AI trends and investment areas in 2024
How schools and universities can use Generative AI
von Nina Habicht 29 Dez., 2023
universities and schools need to change learining approach due to generative AI. How schools and universities can use Generative AI
Supports with the definition of GPTs, alternatives and options to build own chatbots or assistant
von Nina Habicht 25 Dez., 2023
A comprehensive Guide to Alternatives of GPTs and Assistant API from OpenAI
von Nina Habicht 26 Nov., 2023
Many companies are reluctant when implementing llm-based products because they fear bein confronted with high costs. Especially for medium-sized companies which have not the ressouces or enough capacity to deploy and oprimize their AI models nor to set up an own infrastructure with MLOps. As described in our article about sustainability of Gen. AI applications , cloud and performance costs of running an llm can become very high. What are the cost types when implementing OpenAI or other llms? T here are four types of costs related to llms: Inference Costs Setup and Maintenance Costs Costs depending on the Use Case Other Costs related to Generative AI products What are inference costs? An llm has been trained on a huge library of books, articles, and websites. Now, when you ask it something, it uses all that knowledge to make its best guess or create something new that fits what you asked for. That process of coming up with answers or creating new text based on what it has learned is called inference in LLMs . Usually, developers would call a large language model like GPT-4. But here comes the "but": usually not only large language models account to the total costs when running the final product. To explain: LLMs can be used to classify data (e.g undestand that the text talks about "searching a new car insurance"), for summarization, for translation and for many other tasks. Download the ultimative Gen. AI Task Overview to learn where llms make sense:
Checklist to implement Generative AI in your company
von Nina Habicht 24 Nov., 2023
this article helps companies like enterprises and sme to successfully implement generative AI by providing best-in-breed frameworks.
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