NFX’s Generative Tech Open Source Market Map

They are also investing in research and development efforts to improve image and video synthesis, enabling applications such as virtual reality, gaming, content creation, and special effects. Besides this, various key players are focused on making generative AI more accessible to a broader range of users. They are developing user-friendly tools, platforms, and APIs that enable developers, researchers, and businesses to leverage generative AI capabilities. Moreover, they are engaging in partnerships and mergers and acquisitions to strengthen their foothold in the market. About WizelineWizeline, a global technology services provider, builds high-quality digital products and platforms that accelerate time to market.

generative ai market map

The graphic includes various categories of AI content generation, such as text apps Jasper and Some of the companies working on AI in gaming—contextualized against the other stages of video game development—are shown below. is optimizing AI to take on a variety of personalities of famous people or fictional characters and develop the fun, joyful and imaginative side of intelligent assistants. focuses on the user’s ability to shape the personality and attitude of the AI and train the model to be as creative as possible.

Generative AI: A Creative New World

In the next few paragraphs, we want to give you an overview of the model layer without overwhelming you with the technical specifics. Recently, Coatue and Lightspeed Ventures led a 101 million seed (!) round for StabilityAI, the company behind the popular Stable Diffusion model, essentially valuating the company at over $1 billion post-money. But the fact is that StabilityAI was just an open-source program at the time VC capital was injected.

generative ai market map

The company focuses on solving the challenge of reliable text generation within images, making it ideal for tasks like creating company logos or signage. Nvidia, the leading GPU manufacturer, has reported record Q2 revenue, surpassing expectations and achieving a 101% year-over-year increase. Nvidia is reinvesting its profits into rapid product development, including its Hopper architecture, to maintain its leadership position in AI and LLM technologies.


The conversation that I most end up having with CEOs is about organizational transformation. It is about how they can put data at the center of their decision-making in a way that most organizations have never actually done in their history. And it’s about using the cloud to innovate more quickly and to drive speed into their organizations.

generative ai market map

We are all routinely exposed to AI prowess in our everyday lives through voice assistants, auto-categorization of photos, using our faces to unlock our cell phones, or receiving calls from our banks after an AI system detected possible financial fraud. But, beyond the fact that most people don’t realize that AI powers all of those capabilities and more, arguably, those feel like one-trick ponies. AI circles had been buzzing about GPT-3 since its release in June 2020, raving about a quality of text output that was so high that it was difficult to determine whether or not it was written by a human. But GPT-3 was provided as an API targeting developers, not the broad public. ChatGPT immediately took over every business meeting, conversation, dinner, and, most of all, every bit of social media. Screenshots of smart, amusing and occasionally wrong replies by ChatGPT became ubiquitous on Twitter.

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.

The platform layer is just getting good, and the application space has barely gotten going. We can think of Generative AI apps as a UI layer and “little brain” that sits on top of the “big brain” that is the large general-purpose models. When we launched the AI 50 almost five years ago, I wrote, “Although artificial general intelligence (AGI)… gets a lot of attention in film, that field is a long way off.” Today, that sci-fi future feels much closer. This year’s AI 50 list shows the dominance of this transformative type of artificial intelligence, which could reshape work as we know it. Our content series “It All Starts with People” delves into the passions, motivations, and vision of the exceptional founders we have the privilege of partnering with around the world. Read the story of Abraham Burak and Bahadir Ozdemir, co-founders of Airalo, who are on a mission to make connectivity around the world accessible and affordable.

Game infrastructure improvements on the development-front like Adobe Flash and GameMaker Studio and the distribution-front like Steam and XBox Live. These tools together allowed smaller developer teams to build games efficiently while still reaching meaningful scale. Creating compelling game Yakov Livshits mechanics and assets became the focus, rather than developing the low-level systems to power their game environments or searching for a partner to publish their games to offset expanding development budgets. Modularization reduced costs through standardization of the game development stack.

For example, Gen-AI can be used to create new content, such as music or images, which can be used for a variety of purposes such as providing the creatives with more flexibility and imagination. It can also be used to improve machine learning algorithms by generating new training data. Overall, the impact of Gen-AI is sure to be significant, as it has the potential to enable the creation of new and useful content and to improve the performance of machine learning systems.

IoT in AI, Computer Vision, and Simulation – IoT For All

IoT in AI, Computer Vision, and Simulation.

Posted: Tue, 12 Sep 2023 15:23:41 GMT [source]

Generative AI (see Part IV) has been the one very obvious exception to the general market doom-and-gloom, a bright light not just in the data/AI world, but in the entire tech landscape. Many startups right now are sitting on solid amounts of cash and don’t have to face their moment of reckoning by going back to the financing market just yet, but that time will inevitably happen unless they become cash-flow positive. In 2022, Yakov Livshits startups raised an aggregate of ~$238B, a drop of 31% compared to 2021. As to the small group of “deep tech” companies from our 2021 MAD landscape that went public, it was simply decimated. As an example, within autonomous trucking, companies like TuSimple (which did a traditional IPO), Embark Technologies (SPAC), and Aurora Innovation (SPAC) are all trading near (or even below!) equity raised in the private markets.


A more than US$200B market, it hasn’t seen significant changes or disruptions in user experience or industry dynamics for over a decade. Which is why the emergence of new companies trying to optimize and transform the way that search works and capture significant shares of the market is important and exciting. “That is the biggest gap in the tech industry right now,” said Nicola Morini Bianzino, global chief client technology officer at EY. The auditing firm has thousands of models in deployment that are used for its customers’ tax returns and other purposes, but has not come across a suitable system for managing various MLops modules, he said. Nokleby, who has since left the company, said that for a long time Lily AI got by using a homegrown system, but that wasn’t cutting it anymore.

  • Nvidia, the leading GPU manufacturer, has reported record Q2 revenue, surpassing expectations and achieving a 101% year-over-year increase.
  • Talking about innovation gaps she referred to a hiking trip in Ireland and the frustration of switching between maps and other content.
  • Furthermore, the market has attracted significant investments and funding from both established companies and venture capitalists.
  • The concentration of startups in this area is a result of the specific capabilities of GPT-3 and similar language models.
  • And it’s arguably elitist (as those are the most bleeding-edge, best-in-breed tools, requiring customers to be sophisticated both technically and in terms of use cases), serving the needs of the few.