No ratings yet.

Note-taking is an essential part of university studies, and having a centralized platform for these notes enhances the organization of all your subjects’ content. I started using Notion at the start of my master’s after being told about it by my roommate. All of my notes taken for Information Strategy have been drafted on this platform. One feature that I was particularly surprised by was the amount of AI capabilities available within the application. As shown in the below image, the application allows users to write with AI, interact with editing features and generate written products like a social media post for example.

I decided to test this out with my notes as input for the AI generation. A part of my notes from the first lecture was taken, namely on the myths and realities of digital business models being disruptive, and I asked Notion’s AI to make a social media post of the highlighted section. Below is an image of what the generative AI tool constructed.

I was impressed by the AI’s ability to structure the notes in a presentable way and transform a mere small piece of text into something that possesses many characteristics of a typical social media post caption. Notion AI debuted in February of this year and the tool was an addition on the existing platform, this something that the CEO believes could set the tool apart from others. It’s an optional add-on to the platform’s existing pricing plans, costing an extra $10 per user per month. This is a pricing strategy that may be dangerous given the fact that other AI high performing competitors are saying that they are most likely to cite the increase in the value of existing offerings through new AI-based features and not see this as an entirely new source of revenue (McKinsey & Company, 2023). Therefore, consumers will be less inclined to pay more if other services with AI are also not increasing price. As Stefan van Duin discusses in the preparation videos of Session 6, skilled adopters of AI focus more on enhancing existing products and services instead of on lowering costs (Li et al., 2020). This re-emphasizes that Notion AI might want to rethink the choice of increasing costs and focus more on promoting this product enhancement.

Sources

Li T., van Duin S., Vlam V. (2020, October 1). The challenges and opportunities of AI. [Video]. YouTube. https://www.youtube.com/watch?v=BYqzaeeRL-8

The state of AI in 2023: Generative AI’s breakout year. (2023, August 1). McKinsey & Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year

No ratings yet.

Whilst browsing online for innovative generative AI (GenAI) tools, I stumbled across the video game site AI Dungeon that utilizes GenAI to simulate single and multiplayer text-based adventure scenarios. I started by looking at the features and layout of the website. After being directed to the site, I was able to view community favourites, timeless classics made by other users and recently added scenarios from top creators. There are two main sections on the page once you log in, namely the home page and the discover page, where ‘scenarios, worlds and adventures’ are displayed. For clarification purposes of the different constructions, a scenario is a simple template for starting a new ‘adventure’ that can be held privately or shared online, an adventure being an individual playthrough of AI Dungeon. I decided to create my own ‘scenario’, essentially a story mould that other AI Dungeon users could play and alter to form their own adventure on the platform. The first decision I had to make was choosing a template for my scenario that would determine the ‘author’s note’, in specific the writing style and theme that the AI would try adhere to in its generative piece. After this the setup page was shown where I was given options for prompting the start of the story, the backstory, banned words (words to avoid), third person addition etc. This is shown in the image presented below.

Onto the interesting part of the automated story-telling, the technology generated the start of a story based on my inputs and handed me several options after this to foster user-platform interaction. The platform gave me options along the way to jump in, continue the story, retry the AI story generation and erase parts of the story. The platform makes clear use of large language models (LLM) to generate original content through performing a variety of natural language processing tasks (NLP) tasks (Chen et al., 2021). In fact, the platform uses Griffin, a 6 billion parameter GPT-J model developed by EleutherAI (AI Dungeon, n.d.). Below is an image showing what came out of the generation, interestingly a lot of questions and direct speech are used to maximize the level of interaction between the user and the platform. Users even have the option to generate an image which in this case was not very representative of the story in my point of view. However, the LLMs used are subject to some threats to its users which need to be mitigated, namely data privacy violations, algorithmic bias and misuse (Rosenauer & Sahin, n.d.). This is something that regulatory frameworks need to address in the near future. But that discussion is for another time, all in all, a quite fun experience trying to generate a story using a limited number of inputs!

Sources:

Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. D. O., Kaplan, J., … & Zaremba, W. (2021). Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374.

Rosenauer, P., & Sahin, F. (n.d.). Navigating the risks: Harnessing AI and large language models responsibly in business. PwC. https://www.pwc.ch/en/insights/regulation/AI-and-large-language-models-in-business.html

What are the different AI language models in AI Dungeon? (n.d.). What Are the Different AI Language Models in AI Dungeon? https://help.aidungeon.com/faq/what-are-the-different-ai-language-models