Data engineering Pryon: Turning chaos into clarity
Prompting With AI Personas Gets Streamlined Via Advent Of Million And Billion Personas-Sized Datasets
Among those myriad approaches was the use of personas, including individual personas and multiple personas, as depicted at the link here, and the much larger scale mega-personas at the link here. Personas are a powerful feature available in LLMs, yet few users seem to be familiar with the circumstances under which they should consider invoking the capability. Large-scale datasets of millions or billions of ready-to-go AI personas are now available. Closer to our time, AARON’s worthy successor is Botto, a “decentralized autonomous artist managed by a community,” as its creators describe it. Conceived in 2021 by German artist Mario Klingemann, entrepreneur Simon Hudson, and programmer Ziv Epstein, Botto uses an AI image generator similar to DALL-E or MidJourney. However, what makes it stand out among collectors is its “taste model”.
Instead, you can easily dip into massive-sized datasets with ready-made persona descriptions and then paste those depictions directly into your persona-stirring prompts. While generative AI has many advantages, it also comes with challenges and risks. For example, AI-generated content can be used to spread misinformation or create fake news. Generative AI models can sometimes reflect biases present in the training data, leading to unfair or inappropriate outputs. Since generative AI often learns from existing data, questions arise about the ownership of the content it creates. Another concern is about making sure that the quality and accuracy of AI-generated is on point.
This sounds obvious, but in sprawling IT ecosystems, data sprawls too. It lives in silos, on servers, in the cloud and sometimes in places no one thought to look. These users do not care about creating authentic content or engaging other people. If they apply the same passive attitude to their work, they will find themselves being replaced by AI agents in the future.
AI Personas Of Unnamed Compositions
The most common way to indicate an unnamed AI persona is simply to describe the characteristics of the pretense involved. You usually do this out of your own head, in the sense that you think about what factors are crucial and then compose those into your desired prompt. • AI-generated art could compete directly with human artists, reducing demand for commissions. One of the most significant fair use factors is the effect on the market for the original work. Generative AI threatens to disrupt creative markets by producing high-quality content at scale.
AI art: The end of creativity or the start of a new movement? – BBC.com
AI art: The end of creativity or the start of a new movement?.
Posted: Mon, 21 Oct 2024 07:00:00 GMT [source]
Anyone using a generative AI persona needs to keep their wits about them and realize that the conversation or engagement is nothing more than a mimicry or imitation. Though the AI appears to often convincingly fake the nature of the person, it is all still a computational simulation. One of the most popularly invoked personas entails generative AI pretending to be Abraham Lincoln. A teacher might tell a generative AI app such as ChatGPT to simulate the nature of Honest Abe.
AUGMENTED HUMANS: “AI, CHECK MY GRAMMAR”
While the technology holds immense potential, its current reliance on copyrighted works without permission makes fair use a weak defense. Generative AI is still in its early stages, and its full potential is yet to be realized. In the future, we can expect more realistic outputs, which means that AI-generated content will become even more indistinguishable from human-made content.
Fair use relies heavily on whether the use is transformative, meaning it adds new meaning, value or purpose to the original work. While human creativity often achieves this through intentionality—commentary, critique or parody—AI outputs rarely meet this standard. Whether that means automating workflows, making real-time decisions, or delivering predictive insights, this is where the rubber meets the road.
Meta is rolling out tools for people to create AI characters on Facebook and Instagram. As a writer and artist trained in the traditional way – thousands of hours of practice on paper, getting my writing torn apart (figuratively and literally) by editors – I understand how my brethren feel. Artist sources confided to VIP+ that the artist community has already been experiencing layoffs, falloffs in work and unusual decreases in compensation this year. Though hard to directly attribute to generative AI, its impact is also hard to ignore. A few independent AI studios are positioning to produce animated content assisted by generative AI. Asteria Film is focused on making films, while Invisible Universe and Toonstar are launching original animated character IP on social media.
‘It surprised me’: artist finds inspiration in what AI art gets wrong – Art Newspaper
‘It surprised me’: artist finds inspiration in what AI art gets wrong.
Posted: Mon, 06 Jan 2025 08:00:00 GMT [source]
• An AI-generated artwork blending styles from multiple creators may appear novel but lacks the purposeful transformation of human creativity. Think of it as building a map (commonly referred to a knowledge graph) that shows what your data inventory is and what it represents in relation to other data assets. However, many of the organisations rallying to seize this opportunity will be unsuccessful, with some analyst groups (Gartner) predicting a 50% failure rate for gen-AI deployments in the enterprise. The gulf between the expectations of massive competitive advantage and the reality of expensive & ineffective pilots failing can be bridged by effective data engineering.
Generative AI also helps design new drugs by simulating chemical reactions. It is also used to create synthetic medical data for research purposes. Furthermore, a lot of fashion brands use generative AI to create unique clothing designs, too.
Of course, there will be people who fully automate their writing using Gen AI. The petition is well-intentioned, but it is hard to convince people to pull back on using Gen AI (especially when it is free). The two-year-old ChatGPT is now the 9th most popular website in the world, and had 3.7 billion visits in October 2024, according to online tracker Similarweb.
It’s not just about storage; it’s about finding the data they need, exactly when they need it. Ingestion and pre-processing capabilities are key to creating this mapping index automatically, parsing noisy, unstructured data into semi-structured & structured and searchable formats. Starting a gen-AI project without knowing where your data is or what it represents, it’s like trying to write a book without knowing the alphabet. Time invested in understanding the topology of where your data lives, the ontology of what it looks like and clearly defined end-user applications to become ‘AI Ready’, will pay dividends.
An added advanced approach would be to use an online tool to dig into the dataset, pull out the AI persona descriptions, and feed them directly into generative AI. This could be a third-party tool, or you can have generative AI potentially do so for you if the AI app has suitable capabilities to allow this functionality. AI researchers have realized that users and other AI analysts might find immensely useful a dataset of AI persona descriptions. All you need to do is search the dataset to find what you are interested in as an AI persona. Voila, you then copy the description and paste the depiction into a prompt in generative AI. Readers might recall that I previously posted an in-depth elicitation of over fifty prompt engineering techniques and methods, see the link here.
However, its rise has sparked significant debates around copyright law, particularly regarding the concept of fair use. Agentic orchestration can enable systems to take the synthesised insights and act on them autonomously or with minimal human input. These engines bridge the gap between theory and practice, ensuring that your data doesn’t just sit idle – it drives measurable outcomes. The company says that rapid access to authoritative content jumpstarts stalled workflows, cuts down on repetitive tasks and democratises access to knowledge.
Hello, data engineering
A recent Google-Ipsos survey across 21 countries found that 80 per cent of Gen AI users use it for communications and writing. Please read the full list of posting rules found in our site’s Terms of Service. In order to do so, please follow the posting rules in our site’s Terms of Service. You can see that the AI pretended to simulate the aspects of that chosen AI persona.
Most datasets used to train generative AI models include copyrighted materials without the creators’ consent. Creators have the right to control how their work is used, and the absence of their consent undermines ethical and legal defenses. Generative AI models are trained on massive datasets, often containing millions of works. While individual pieces may contribute minimally, the sheer scale of usage complicates the argument for fair use.
Ian Yong Hoe Tan is a strategic communications lecturer at the Wee Kim Wee School of Communication and Information, Nanyang Technological University. He has more than two decades of experience working in the media and technology industries. If you haven’t already started doing so, choose your favourite social media platform and publish excerpts of your work, share daily thoughts, comment on the world, review the latest shows, and so on. For instance, I have started writing a book on marketing and I’m posting draft chapters weekly to get crowdsourced feedback from LinkedIn and Facebook friends.
- Instead, you can easily dip into massive-sized datasets with ready-made persona descriptions and then paste those depictions directly into your persona-stirring prompts.
- If they apply the same passive attitude to their work, they will find themselves being replaced by AI agents in the future.
- Asteria Film is focused on making films, while Invisible Universe and Toonstar are launching original animated character IP on social media.
- Generative AI threatens to disrupt creative markets by producing high-quality content at scale.
This content can take various forms, such as text, images, videos, music, or even code. It’s no secret that more and more creatives are turning to artificial intelligence to produce their works, using technologies like text-to-image models and generative systems that create “living” artworks. However, some artists have gone further, involving AI not as a mere passive tool but as an active subject in the creative process. Thus, the first “robotic” artists, powered by artificial intelligence, have been born. While this may sound like science fiction, their story began several decades ago.
I showed her how ChatGPT could clean up her written work with a simple prompt like “check grammar”. She was surprised to see how many grammar errors ChatGPT caught and fixed. I also use the same prompt to help me catch typos in my own writing; it’s like having a newsroom editor by my side. It may interest you to know that many believe that generative AI tools will become more affordable and widely available, empowering more people to use them. Also, entirely new industries and applications may emerge that are driven by generative AI innovations. “The LoRA acts as a kind of filter or lens to output images that are more brand or IP accurate.