Generative AI for Powerful and Seamless Data Analysis

An image-generating app, in distinction to text, might start with labels that describe content and style of images to train the model to generate new images. Generative AI, as noted above, often uses neural network techniques such as transformers, GANs and VAEs. Other kinds of AI, in distinction, use techniques including convolutional neural networks, recurrent neural networks and reinforcement learning.

We’re even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand-in for real data protected by privacy and copyright laws. Generative AI has been around for years, arguably since ELIZA, a chatbot that simulates talking to a therapist, was developed at MIT in 1966. But years of work on AI and machine learning have recently come to fruition with the release of new generative AI systems. You’ve almost certainly heard about ChatGPT, a text-based AI chatbot that produces remarkably human-like prose. DALL-E and Stable Diffusion have also drawn attention for their ability to create vibrant and realistic images based on text prompts. Examples of foundation models include GPT-3 and Stable Diffusion, which allow users to leverage the power of language.

What are generative models?

DALL-E combines a GAN architecture with a variational autoencoder to produce highly detailed and imaginative visual results based on text prompts. With DALL-E, users can describe an image and style they have in mind, and the model will generate it. Along with competitors like MidJourney and newcomer Adobe Firefly, DALL-E and generative AI are revolutionizing the way images are created and edited.

The below graph shows the differential in traffic between the #1 and #2 players in each space. While there are some exceptions (e.g., companionship), for most categories there is less than a 2x gap—meaning the top company receives just double (or less) the number of visits as its next closest competitor. This is nowhere near insurmountable given companies on the list averaged 50% monthly growth over the past 6 months. General LLM chatbots represent 68% of total consumer traffic to the top 50 list. Alongside ChatGPT, this category includes Google’s Bard and Quora’s Poe, all ranked in the top 5.

Models

Generative AI art models are trained on billions of images from across the internet. These images are often artworks that were produced by a specific artist, which are then reimagined and repurposed by AI to generate your image. Generative AI is also able to generate hyper-realistic and stunningly original, imaginative content. Content across industries like marketing, entertainment, art, and education will be tailored to individual preferences and requirements, potentially redefining the concept of creative expression.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

One of the biggest concerns is the ethical implications of using this technology to generate content without proper attribution or consent. Another challenge is ensuring that the generated content is highly relevant to the user. Utilizing existent inputs, Yakov Livshits can produce novel text, codes, photos, shapes, movies, and much more in a few seconds. The global enterprise adoption of AI is expected to soar at a compound annual growth rate of 38.1% between 2022 and 2030. It is the right time for all business professionals to skill up and adapt themselves to Generative AI. Creating realistic pictures, films, and sounds, generating text, developing goods, and helping in developing medicines and scientific research are just a few examples of real-world uses for generative AI.

Learning by Doing

They have been employed in various creative applications, such as art generation, image synthesis, and data augmentation. GANs have also found applications in improving image quality, anomaly detection, and style transfer. The branch of artificial intelligence known as “generative AI” is concerned with developing models and algorithms that may generate fresh and unique content. Generative AI algorithms apply probabilistic approaches to produce new instances that mirror the original data, typically with the capacity to demonstrate creative and inventive behavior beyond what was explicitly designed. Identify and implement AI opportunities using human-centric AI-based approaches that outperform machine-centric approaches with fewer computing resources and data.

This breakthrough technology empowers businesses to offer tailored solutions to their customers, elevating user satisfaction and engagement to unprecedented heights. Yakov Livshits is a broad label that is used to describe any type of artificial intelligence that can be used to create new text, images, video, audio, code or synthetic data. Designs.ai is a comprehensive AI design tool that can handle various content development tasks. It’s goal is to “empower imagination through artificial intelligence.” It can produce voice-overs, videos, social media postings, and logos. The transformer-based language model is more complex than many existing language models, like OpenAI Codex, with 41.4 billion parameters.

He specializes in helping organizations use artificial intelligence and develop their big data, analytics, and AI capabilities. An award-winning professor and researcher, he has extensive experience of AI and analytics-driven transformations in industries such as banking, fintech, retail, automotive, telecoms, and pharma. The top 50 list is an almost Yakov Livshits even 3-way split between companies that (1) trained their own proprietary model, (2) fine-tuned an existing model, and (3) built a consumer UI on top of an existing model (e.g., “GPT wrappers”). However, it’s worth noting that of the top 10 products, half are built on their own model, while 4 are fine tunes—only one falls in the “wrapper” category.