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Beyond Imagination: The Rise and Evolution of Generative AI Tools


Generative AI has revolutionized the way we create and interact with digital content. Since the launch of Dall-E in July 2022 and ChatGPT in November 2022, the field has seen unprecedented growth. This technology, initially popularized by OpenAI’s ChatGPT, has now been embraced by major tech players like Microsoft and Google, as well as a plethora of innovative startups. These advancements offer solutions for generating a diverse range of outputs including text, images, video, audio, and other media from simple prompts.

The consumer now has a vast array of options based on their specific output needs and use cases. From generic, large-scale, multi-modal models like OpenAI’s ChatGPT and Google’s Bard to specialized solutions tailored for specific use cases and sectors like finance and legal advice, the choices are vast and varied. For instance, in the financial sector, tools like BloombergGPT (https://www.bloomberg.com/), FinGPT (https://fin-gpt.org/), StockGPT (https://www.askstockgpt.com/) or BeeBee.AI (https://www.beebee.ai/) or in the domain of legal advise, tools like Law Chat GPT (https://lawchatgpt.com/) or LegalFly (https://www.legalfly.ai/), offer niche solutions with heightened accuracy.

To give an idea of what is available on the market, here is a short overview of some notable solutions available:

As you can see this list is already enormous, but this is just a small subset of all available solutions. Additionally the offer grows almost on a daily basis, making it hard to keep track of what is available on the market. This shows on one hand the enormous interest of high-potential startup founders and VCs in the topic of generative AI, but at the same time also shows the immaturity of the market.

The enormous choice in AI tooling to support digital content creation makes it hard for organizations to select the right tooling, as the needs and preferences of every worker are quite different. Additionally for organizations it can be hard to remain cost effective. With most tools offering professional access at around 15-20€ / month / user, the bill starts increasingly rapidly when you start using multiple tools by multiple employees. Obviously productivity gain (and thus cost reductions) can be enormous when used well, but often gimmick usage today remains the primary usage. Some consolidation in the sector is therefore likely to happen in the coming years.

As we witness the rapid expansion of this domain, three key trends are becoming increasingly evident:

  • Rise of multi-modal, generic, multi-purpose models: Models like OpenAI’s GPT-4 and Google’s Bard are evolving to understand and generate diverse types of content. This versatility might soon enable a single model to match the capabilities of various specialized tools.

  • Integration and Embedding: More and more, AI tools are being integrated into existing productivity and business software, instead of stand-alone tools (or websites). Notable examples include

  • Creation of Custom AI Subsets: New developments are allowing users to tailor large, multi-purpose models to their specific needs, combining the best of both worlds, i.e. the broad capabilities of an LLM model with specialized focus on one specific topic. OpenAI’s recent announcements of GPTs allowing to anyone to create a tailored version of ChatGPT and Assistants API (https://platform.openai.com/docs/assistants/overview) are very clear and powerful steps in this direction.

These three trends favorize the big tech players, as they have the means to support these complex trends, i.e.

  • Google with solutions like Bard, PaLM API, Vertex AI and Duet AI, but also with Google Assistant.

  • Microsoft via its partnership with OpenAI and the integration of chatGPT in Bing, but also with Microsoft Copilot and Azure OpenAI

  • Amazon with several solutions, like Amazon Ads, which contains a new AI feature for making advertisements and Amazon Marketplace, which offers an AI feature for sellers to write more effective product listings, but also on AWS with solutions like Amazon Bedrock, Amazon SageMaker, Amazon CodeWhisperer, Amazon Kendra, Amazon Lex, Amazon Polly…​ And obviously there is also Amazon Alexa, as a virtual assistant.

  • Apple: apart from Apple’s assistant Siri, Apple is currently lagging a bit behind in the battle of generative AI solutions. Nonetheless in October of this year, Apple announced it will be investing $1 billion a year in generative AI products. Obviously Apple has already some generative AI features, like Photos (use of generative AI to enhance quality of photos), Visual Lookup or Autocorrect. Rumors say that Apple will be coming up with an "Apple GPT" solution towards the end of 2024.

  • IBM: IBM has been investing for quite some time already in AI, with solutions like IBM Watson (Assistant) and Watsonx platform.

  • Meta: Meta has also missed a bit the game, as it was investing heavily in the Metaverse, but in March of this year the company announced that its "single largest investment" is now in advancing its AI strategy. For this Meta is focusing on building out its open-source large language model Llama 2. Interesting to mention is that Microsoft is also investing heavily in this model. Additionally Meta introduced in September of this year Meta AI, which is an AI chatbot assistant integrated in Instagram, WhatsApp and Messenger.

  • NVIDIA: one name which is often overlooked, but which has the potential to overthrow the other big names is NVIDIA. NVIDIA is currently mostly known as the dominant GPU chip provider, which boomed as its chips are ideal for the heavy calculations for AI training. In the meantime Nvidia is becoming more and more an end-to-end company, offering also software solutions. Their AI Platform software, called NVIDIA AI Enterprise with its large language model NVIDIA NeMo and image and video AI generative solution NVIDIA Picasso, are already best in class and their strong link with the underlying hardware might give them a competitive advantage compared to other tech players.

The ultimate goal obviously of all companies is to come to a Virtual AI assistant, which pro-actively helps you will all your tasks, both personal and professional.
Obviously the above big tech companies are all working towards this, but there are also some specialized start-ups investing in this. E.g. Otter (https://www.unite.ai/goto/otter), Lindy (https://www.lindy.ai/), Leon (https://getleon.ai/), Kore.AI (https://kore.ai/), Leena AI (https://leena.ai/), Moveworks (https://www.moveworks.com/), Hyro (https://www.hyro.ai/) or Yellow.ai (https://yellow.ai/) offer very creative solutions in this field as well.

The pace at which generative AI is evolving is breathtaking. The potential applications and advancements in just a few years are staggering to contemplate. While this presents an exciting frontier, it also poses challenges in selecting the right tools and ensuring cost-effective implementation. Nonetheless, the journey into the realm of generative AI is one filled with immense possibilities and is undoubtedly shaping the future of digital content creation.

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