Market Map: Gen AI Companies with Foundational Models

Generative AI Market Size, Share, Industry Trends 2023-28

For the creator economy to succeed, platforms will need to adapt to the creators’ personalities so the creators have some form of connection with their fans when the content may have been mostly supported with AI platforms. Imagine a world where instead of spending days writing a blog post, a week creating a presentation, or several months on an academic paper, you can use generative assistant tools to complete your Yakov Livshits projects in minutes. These tools not only help us with our projects, but also support us in making better decisions. If you missed it, last month we released a top 60 market map for here… they say all good things need iteration and we are pumped to be supported by AWS for Startups to release a fully updated map. Subsequently, Google also rushed to market its own ChatGPT competitor, the interestingly named Bard.

generative ai market map

In this case, attention refers to mechanisms that provide context based on the position of words in text, which vary from language to language. The researchers observed that the best performing models all have these attention mechanisms, and proposed to do away with other means of gleaning patterns from text in favor of attention. Generative AI was in the background on last year’s list but in the foreground now. In addition to using proprietary NFX software and data for the first and internal draft of this market map, we also referred to Base10, Pitchbook, CB Insights, and Sequoia’s map.

In the Consumer Space, Models Develop Emotional Intelligence and Personalities.

AI-powered study and tutoring tools that offer not just answers but personalized explanations remain at the top of the chart. Workflow tools that save time — particularly teacher assistants and “copilots” that help create lesson plans, assignments and assessments — have also proliferated. Some are designed by former educators, informed by their own experiences and pain points. In addition to cataloging tools by content type and business function, the map also labels each according to the following five technical categories.

NFX’s Generative Tech Open Source Market Map – NFX

NFX’s Generative Tech Open Source Market Map.

Posted: Wed, 07 Dec 2022 23:26:54 GMT [source]

Some crowded fields might also exhibit a strong first-mover advantage, where early entrants with high user engagement accumulate more data to fine-tune their models and further improve their models and user experience4. At the same time, newer players have a hard time breaking in, making it harder to make successful later investments in the field. However, it is possible that the release of newer models might create opportunities for new entrants to break in. Beyond gaming, current-generation AI models are well suited for tasks that are highly repetitive but highly paid and those where imperfection is allowed with humans in the loop. Coding, marketing, and video editing are perfect tasks where AI could assist human experts, allowing them to do things faster and better.

Image Tools Optimize for Original and Diverse Methods to Generate Pictures

Bennett is originally from Portland, Maine, and received his bachelor’s degree from Colgate University. We continue to both release new services because customers need them and they ask us for them and, at the same time, we’ve put tremendous effort into adding new capabilities inside of the existing services that we’ve already built. What I believe is most important — and what we have honed in on at Zest AI — is the fact that you can’t change anything for the better if equitable access to capital isn’t available for everyone. The way we make decisions on credit should be fair and inclusive and done in a way that takes into account a greater picture of a person. Lenders can better serve their borrowers with more data and better math. Zest AI has successfully built a compliant, consistent, and equitable AI-automated underwriting technology that lenders can utilize to help make their credit decisions.

generative ai market map

Concerned about future-proofing your business, or want to get ahead of the competition? Reach out to us for plentiful insights on digital innovation and developing low-risk solutions. From chatbots to deep learning algorithms, the influence of AI is felt in numerous industries. One type of AI that has gained significant traction and is reshaping the landscape of creativity and innovation is generative AI.

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.

It’s no wonder why gamers are some of the most engaged and retentive audiences of any consumer vertical. and are both companies based in the San Francisco Bay Area working on search for consumers. IBM has responded to that reality by allowing clients to use its MLops pipelines in conjunction with non-IBM technology, an approach that Thomas said is “new” for IBM. Intuit has also used open-source tools or components sold by vendors to improve existing in-house systems or solve a particular problem, Hollman said. However, he emphasized the need to be selective about which route to take.

generative ai market map

This is notable because both companies are owned by Thoma Bravo, who presumably played marriage broker. Progress also just completed its acquisition of MarkLogic, a NoSQL database provider MarkLogic for $355M. MarkLogic, rumored to have revenues “around $100M”, was owned by private equity firm Vector Capital Management. The problem, of course, is that the very best public companies, such as Snowflake, Cloudflare or Datadog, trade at 12x to 18x of next year’s revenues (those numbers are up, reflecting a recent rally at the time of writing). At the time of writing, the venture market is still at a state of standstill.

Segmentation Analysis of the Generative AI Market

Perhaps the clearest takeaway for model providers, so far, is that commercialization is likely tied to hosting. Hosting services for open-source models (e.g. Hugging Face and Replicate) are emerging as useful hubs to easily share and integrate models — and even have some indirect network effects between model producers and consumers. There’s also a strong hypothesis that it’s possible to monetize through fine-tuning and hosting agreements with enterprise customers. Across app companies we’ve spoken with, there’s a wide range of gross margins — as high as 90% in a few cases but more often as low as 50-60%, driven largely by the cost of model inference. Top-of-funnel growth has been amazing, but it’s unclear if current customer acquisition strategies will be scalable — we’re already seeing paid acquisition efficacy and retention start to tail off. Many apps are also relatively undifferentiated, since they rely on similar underlying AI models and haven’t discovered obvious network effects, or data/workflows, that are hard for competitors to duplicate.

Google Nears Release of Conversational AI Software ‘Gemini’ – Slashdot

Google Nears Release of Conversational AI Software ‘Gemini’.

Posted: Fri, 15 Sep 2023 23:20:00 GMT [source]

These models are good enough today to write first drafts of blog posts and generate prototypes of logos and product interfaces. There is a wealth of value creation that will happen in the near-to-medium-term. But humans are not only good at analyzing things—we Yakov Livshits are also good at creating. Up until recently, machines had no chance of competing with humans at creative work—they were relegated to analysis and rote cognitive labor. But machines are just starting to get good at creating sensical and beautiful things.

Reask, a climate risk startup, raises USD$6.55 million to enhance AI-driven weather modeling

Y Combinator’s startup directory features over 100 generative AI startups making waves across every essential business function—from marketing, operations and customer support to engineering and infrastructure. Despite the obstacles, Intuit’s Hollman said it makes sense for companies that have graduated to more sophisticated ML efforts to build for themselves. “If you’re somebody that’s been in AI for a long time and has maturity in it and are doing things that are at the cutting edge of AI, then there’s [a] reason for you to have built some of your own solutions to do some of those things,” he said.

Matt also organizes Data Driven NYC, the largest data community in the U.S. We’ve long argued in prior posts that the success of data and AI technologies is that they eventually will become ubiquitous and disappear in the background. It’s the ransom of success for enabling technologies to become invisible. Is generative AI that once-every-15-years kind of generational opportunity that is about to unleash a massive new wave of startups (and funding opportunities for VCs)? Google kept its LaMBDA model very private, available to only a small group of people through AI Test Kitchen, an experimental app. The genius of Microsoft working with OpenAI as an outsourced research arm was that OpenAI, as a startup, could take risks that Microsoft could not.

  • Artificial Intelligence (AI) is a broad term that refers to any technology that is capable of intelligent behavior.
  • It is used to create realistic computer-generated graphics and special effects in movies and video games.
  • These diffusion models marry the best elements of GANs and transformers.
  • Over the past two decades, the firm has backed hundreds of exceptional entrepreneurs and helped build and scale companies to achieve 190 IPOs and acquisitions.
  • This includes autoencoders, generative adversarial networks, and others.