What Y Combinator’s Latest Generative AI Landscape Map Says

This has not helped MAD companies much, as the overwhelming majority of companies on the landscape are B2B vendors. First to cut spending were scale-ups and other tech companies, which resulted in many Q3 and Q4 sales misses at the MAD startups that target those customers. Plugins are software add-ons (modules or components) that extend the functionality of existing software. Generative AI can enhance these plugins, improving a wide range of software, including web browsers, word processors, and image editors. For instance, a music production plugin might use generative AI to create new melodies or harmonies, while a web browser plugin might generate summary notes of a webpage.

We are excited to continue watching this space as we think many learnings here will be applied to other burgeoning categories of generative AI products. It would be exciting to see these products Yakov Livshits extend to code suggestions, as innovative teams can quickly adapt (Knowtex). Not surprisingly, the functional areas currently benefiting from generative AI are typically text-based.

Website Generation from Text

These companies, with their existing distribution channels, are well-positioned to quickly add and deploy new tools. It will be exciting to see if additional competitors emerge as AI adoption accelerates and healthcare companies seek to incorporate it. We were surprised to find relatively few companies in this space, given how important both security and compliance are for healthcare organizations. Codoxo AI Compliance focuses on alerting, whereas Syntegra offers security and compliance solutions. The potential for LLMs to synthesize complex regulatory data into APIs makes this an intriguing area for innovation, as not many companies have been built in this space.

generative ai landscape

Whether you’re a homeowner looking to revamp your backyard or a professional landscaper in search of new ideas, the DreamzAR app has everything you need to create a landscape that you’ll love. Enterprises using these kinds of chatbots need to be aware of how this kind of misinformation could direct customers to carry out possibly dangerous repairs, resulting in their Yakov Livshits brand being damaged. Successful enterprises will develop countermeasures to mitigate the likelihood of misinformation and identify ways in which generative AI can deliver real value to customers and the bottom line. The recent introduction of ChatGPT thrust generative AI into the limelight, raising public awareness of its potential for business, productivity and art.

Generative AI industry use cases

Since then, of course, the long-anticipated market turn did occur, driven by geopolitical shocks and rising inflation. Central banks started increasing interest rates, which sucked the air out of an entire world of over-inflated assets, from speculative crypto to tech stocks. Public markets tanked, the IPO window shut down, and bit by bit, the malaise trickled down to private markets, first at the growth stage, then progressively to the venture and seed markets. Meanwhile, the last few months have seen the unmistakable and exponential acceleration of generative AI, with arguably the formation of a new mini-bubble. Beyond technological progress, AI seems to have gone mainstream with a broad group of non-technical people around the world now getting to experience its power firsthand.

Generative AI Market Size, Landscape, Industry Analysis, Business … – Digital Journal

Generative AI Market Size, Landscape, Industry Analysis, Business ….

Posted: Thu, 14 Sep 2023 00:24:28 GMT [source]

EleutherAI also released GPT-J-6B in June 2021, which is a 6 billion parameter language model, making it the largest open-source GPT-3 like model at the time. Additionally, they combined CLIP with VQGAN to develop a free-to-use image generation model, which guided the foundation of Stability AI. EleutherAI also trains language models in other languages, such as Polyglot-Ko, which were trained in collaboration with the Korean NLP company TUNiB.

Model providers invented generative AI, but haven’t reached large commercial scale

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.

Fine-tuning involves unlocking an existing LLM’s neural network for additional layers of training with new data. End users or companies can seamlessly integrate their own proprietary or customer-specific data into these models for targeted applications. ChatGPT, used by hundreds of millions of people across the globe, stands as a prominent example of generative AI. It can produce human-like text by responding to input prompts, utilizing the Transformer architecture.

It deploys an encoder-decoder transformer model that uses 30-second chunks of input audio converted to log-Mel spectrograms, which are then passed to an encoder. The decoder predicts the corresponding text caption and intermixes special tokens to perform various tasks. Whisper provides an open-source model and inference codes for speech processing research and new application development.

Landscape Design with Photos meets AI Landscape Design Stylist

They are easy to use, providing user-friendly interfaces for content generation. They are often affordable or even free to use, scalable to accommodate many users and incorporate strong security measures for user data protection. These applications may exhibit bias, depending on the data they were trained on, and there could be privacy concerns as these apps may collect and use user data in ways unknown to users.

The use of Azure Cosmos DB – Microsoft’s NoSQL database within Azure – by OpenAI for dynamically scaling the ChatGPT service underscores the need for databases that are both highly performant and scalable in the realm of generative AI. Some prominent Generative AI applications include OpenAI’s GPT-4, Anthropic’s Claude, Cohere’s language AI platform, SEO.ai, Viz.ai, Shield AI’s Hivemind AI pilot, Observe.AI, AI21, Midjourney, People.ai, and Nektar.ai. Yes, Generative AI can produce high-quality visuals from textual descriptions, execute automatic video summarization by selecting keyframes, and is used for style transfer in creative design applications. Shield AI is a company focused on developing the Hivemind AI pilot, which enables drones and aircraft to operate autonomously without GPS, communications, or a pilot. This allows for swarms of drones to perform military operations and provide persistent aerial dominance across sea, air, and land, without risking the safety of human pilots. The Hivemind AI pilot reads and reacts to the battlefield, allowing for intelligent decision-making without preset behaviors or waypoints.

Synthetic Training Data Generation

The Pathways system allows for scaling a model across Google’s thousands of Tensor Processing Unit chips. The company plans to cap the profit of the investors at a fixed multiple of their investment (noted by Sam Altman as currently ranging between 7x and 100x depending on the investment round date and risk). As per the WSJ OpenAI was initially funded by $130m of charity funding (Elon Musk tweeted he contributed $100m) and has since raised at least $13bn led by Microsoft (where OpenAI makes use of Azure cloud credits). With the Microsoft partnership, OpenAI’s ChatGPT, along with Microsoft’s own search AI, created an improved version of Bing and transformed Microsoft’s Office productivity apps.

Geotab transforms connected transportation in Australia with … – PR Newswire

Geotab transforms connected transportation in Australia with ….

Posted: Mon, 18 Sep 2023 04:40:00 GMT [source]

This is especially pertinent to generative AI, where applications can take user inputs, process them via a proprietary AI model, and deliver an output within a single, seamless application. Bursting upon the scene in late 2022, within months generative AI quickly began radically reshaping the tech sector. In fact it’s no exaggeration to say that the “generative AI landscape” and the “overall tech landscape” are essentially merging into a singly entity, as generative AI technologies find their way into a growing list of tech tools and solutions. The majority of today’s generative AI models have time-based and linguistic limitations.

  • Clear objectives will guide the integration process and measure the AI’s impact on marketing outcomes.
  • This delivered surprising capabilities and “zero shot” performance at completing new tasks the model hadn’t been trained for.
  • OpenAI’s revolutionary chatbot ChatGPT has been all over the news in recent months, triggering technology giants such as Google and Baidu to accelerate their AI roadmaps.
  • In some cases, AI powers the robotic process automation applications used to automate a variety of tedious and repetitive business processes.