Generative AI: Powerful AI that knows how to build

In the world of artificial intelligence, one of the most exciting developments is the rise of Generative AI. Unlike standard AI models, Generative AI doesn’t just analyze and make decisions based on data; it creates new content, opening a new frontier of opportunities for industries across the globe.

But what exactly is this technology, and how does it differ from traditional AI? Let’s dive in to uncover this fascinating concept.

Generative AI: A quick intro

Generative AI refers to a type of AI that creates new data instances based on user inputs. (prompts) Well, in simpler terms, think of an AI model that can produce a realistic image, compose music, write paragraphs of text, or even design proteins. This capability goes beyond the traditional data analysis of AI into the realm of creation.

A common example of Generative AI is a chatbot that doesn’t just reply to queries with pre-determined responses, but generates new, contextually appropriate answers. It’s like having a conversation with a person who can not only understand your questions but provide relevant, spontaneous responses.

The basis of Generative AI lies in deep learning models, specifically, Generative Adversarial Networks (GANs), and transformer models. GANs involve two neural networks: a generator that creates new data instances, and a discriminator that evaluates the created data for authenticity.

They compete in a kind of game, with the generator striving to produce more authentic-looking data, and the discriminator getting better at spotting the fakes. Over time, this dynamic helps the generator produce very realistic data.

Generative AI vs. traditional AI

To understand the real novelty of this tech, it’s important to distinguish it from traditional AI or general AI. The latter refers to AI systems that can perform any intellectual task that a human being can do – a form of AI that is yet to be fully realized.

On the other hand, traditional AI models, often based on machine learning, are excellent at pattern recognition and decision-making based on existing data. For example, they can recognize a cat in an image, make a recommendation based on your past purchases, or predict future sales based on historical data.

Generative AI, however, takes this a step further. Instead of simply recognizing or deciding, it creates. It’s the difference between an AI that can tell you a story it has learned and an AI that can write a new story, complete with plot twists and character development that it hasn’t been explicitly taught.

Top companies leading the way in Generative AI

OpenAI

OpenAI has undoubtedly earned its reputation as a leading Generative AI organization. Not only has it developed ground-breaking models like GPT-3 and GPT-4, but it also produces other AI technologies for language and content generation, such as ChatGPT Plus and DALL-E. With a staggering estimated valuation of around $29 billion, OpenAI has emerged as a significant force in pushing the boundaries of this wonderful concept.

Hugging Face: Best for community-driven AI development

If there’s a company that has built a community around AI development, it’s Hugging Face. With an estimated valuation of around $2 billion, the company provides platforms for open-source AI model development and hosts active Aenerative AI forums. Some of their notable products include BLOOM and the Expert Acceleration Program, fostering a thriving community that collaborates to drive AI innovation.

Alphabet: Best for scalability projects

As one of the world’s most valuable companies, Alphabet (Google’s parent company), excels in developing and deploying Generative AI models on a large scale. Products like Bard, Vertex AI, and Generative AI App Builder showcase Alphabet’s efforts to incorporate this model across various applications, including content generation and app development.

Anthropic: Best for Customizable Content Generation

Anthropic is making strides in content generation, editing, text classification, and summarization. Their products, Claude and Claude Instant, empower businesses to create customized content that caters specifically to their customers’ needs.

NVIDIA: Multiple fields

A key player pioneering the advancement of Generative AI is NVIDIA. They are powering this innovative field through an impressive suite of cloud services, pre-trained foundation models, and cutting-edge frameworks, optimized inference engines, and APIs. NVIDIA’s AI Foundations is a comprehensive set of cloud services that advances Generative AI in enterprises, enabling customization across several use cases.

NVIDIA’s offerings in this field are broad, spanning text (NVIDIA NeMo™), visual content (NVIDIA Picasso), and biology research (NVIDIA BioNeMo™). Each of these tools takes advantage of the power of the NVIDIA DGX™ Cloud—the AI supercomputer, enabling enterprises to unlock potential in various areas.

Jasper: Best for marketers and writers

Jasper’s AI models focus on content generation and language modeling, making it a boon for marketers. With tools like Jasper Art and Jasper Chat, the company assists marketers in creating engaging content and managing customer interactions.

Microsoft: Best for business operations and productivity applications

Microsoft has seamlessly incorporated Generative AI into business productivity and operations, leveraging AI to generate content, aid in coding, enhance search capabilities, and fortify cybersecurity. Their AI-enhanced suite of products, including Microsoft 365 Copilot and GitHub Copilot, make daily business tasks more efficient and intuitive.

Cohere: Best for natural language processing

Cohere specializes in natural language processing and modeling, which are fundamental components of Generative AI. With products like Embed, Neural Search, Summarize, Generate, and Classify, they’re carving a niche in enterprise conversational AI. Their efforts are evident in their estimated valuation of around $6 billion.

Unleashing the power of Generative AI: How they can help us?

Text Generation: Imagine having an AI that can help with creating marketing copy, storylines, or even global translation in multiple languages. That’s the actual current power of Generative AI in text generation.

Summarization: Generative AI can also create summaries for news, emails, meeting minutes, and synthesize information, making information digestion quicker and easier.

Chatbots: We’ve already mentioned this, but it’s worth repeating. Generative AI can produce intelligent Q&A chatbots that provide real-time customer support.

Image and Video Generation: From creating high-resolution images for product design to generating high-fidelity videos for advertising and marketing, Generative AI is revolutionizing content creation.

3D Content and Protein Generation: Generative AI is even stretching into the field of biology. It can generate 3D assets with detailed geometry for character creation and predict 3D protein structures and properties.

Examples of real-life generative AI applications

The BioNeMo Project: A revolutionary leap

Perhaps one of the most significant leaps NVIDIA has made with generative AI is its BioNeMo project. BioNeMo is a software framework and service for creating AI models for healthcare, particularly in generating high-quality proteins for drug design and sustainable environmental solutions.

A concrete example of BioNeMo’s potential can be seen in the work of the startup Evozyne. Using NVIDIA’s implementation of ProtT5, a transformer model that’s part of NVIDIA BioNeMo, Evozyne created two proteins with significant potential in healthcare and clean energy. They were able to generate millions of sequences in just a few seconds, a truly impressive feat.

The ability to use generative AI in this capacity is just the beginning. As Evozyne’s co-founder Andrew Ferguson put it, “The technology is enabling us to do things that were pipe dreams 10 years ago.”

Generative AI in everyday life: Wombo Dream and Mini Studio

Generative AI is not just for tech companies and scientific research; it’s making its way into everyday life as well. Wombo Dream, for example, brings this model to the masses through their mobile app. Users can generate desired images using a text prompt and even share their creations with the Wombo community.

Mini Studio, on the other hand, harnesses the power of AI to stimulate children’s creative potential. Kids can transform their drawings into characters that star in narratives designed for social and emotional growth, all thanks to generative AI.

Conclusion: How will generative AI look in a few years?

As we have seen, Generative AI is more than just a buzzword — it’s a transformative technology that is revolutionizing industries, from marketing to healthcare, and even our personal lives. With companies like OpenAI, Google, Anthropic or NVIDIA, leading the charge, the horizon for AI-accelerated innovations is wide, and the potential is astounding.

Generative AI is about more than just generating content. It’s about enabling us to explore, create, and innovate like never before. As we look to the future, the possibilities are as limitless as our imagination, powered by the remarkable capabilities of Generative AI.

Whether we are striving for advancements in healthcare or simply hoping to enhance our creative potential, Generative AI holds the key. As we harness its power and potential, there’s no telling what we will achieve. As Andrew Ferguson poignantly stated, “Who knows where we will be in five years’ time.” Indeed, the future of Generative AI is a thrilling prospect, and we’re just getting started.