19. september 2023

The Role of New Technologies in the Marketing Landscape

Recording Investors POV: Mapping the Applied Generative AI Landscape

It is possible to get detailed and complex visuals by entering simple commands with it. ChatGPT is a generative AI system trained on millions of Yakov Livshits data to give human-like responses to given prompts. It was designed to communicate with you, answer your questions or act upon your commands.

Another example is Google’s DeepDream, which uses generative AI to create abstract and surreal images by analyzing existing images. In 2021, OpenAI released Codex, a model that translates natural language into code. You can use codex for tasks like “turning comments into code, rewriting code for efficiency, or completing your next line in context.” Codex is based on GPT-3 and was also trained on 54 million GitHub repositories. OpenAI’s GPT models are a flavor of transformers that it trained on the Internet, starting in 2018.

DataDecisionMakers

AudioLM uses a hybrid tokenization scheme and a SoundStream neural codec to improve fidelity. The model achieved a 51.2% success rate from human raters and an audio classifier with 98.6% accuracy was trained to detect synthetic speech generated by AudioLM. Currently, AudioLM is only available for research purposes and is not publicly available. Whisper, developed by OpenAI, is a versatile automatic speech recognition system that supports multilingual speech recognition, speech translation, and language identification. It has been trained on 680,000 hours of multilingual and multitask supervised data using Python 3.9.9 and PyTorch 1.10.1, and the codebase is expected to be compatible with Python 3.8–3.10 and recent PyTorch versions.

The application layer in generative AI streamlines human interaction with artificial intelligence by allowing the dynamic creation of content. This is achieved through specialized algorithms that offer tailored and automated business-to-business (B2B) and business-to-consumer (B2C) applications and services, without users needing to directly access the underlying foundation models. The development of these Yakov Livshits applications can be undertaken by both the owners of the foundation models (such as OpenAI with ChatGPT) and third-party software companies that incorporate generative AI models (for example, Jasper AI). Generative AI streamlines language translation by boosting its accuracy and efficiency. It facilitates real-time translation in various languages by integrating deep learning algorithms and data analysis.

Generative AI landscape by numbers

With its vast array of applications and intense competition, the future of generative AI promises to shape industries, foster creativity, and revolutionize how we interact with technology. Striking a balance between ethical AI practices and cutting-edge advancements will be instrumental in harnessing the full potential of generative AI for a better, more interconnected world. The generative AI competitive landscape is marked by intense competition among major tech giants, startups, and academic institutions.

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.

Compute cost optimization is also essential since generative models, especially large language models, are still expensive to both train and serve for inference. Big players in the industry are working on optimizing compute costs at every level. The Jurassic-1 model by AI21 Labs generates human-like texts and performs complex tasks like question answering, text classification, and others.

Image Generation: Dall-E MidJourney Stable Diffusion DreamStudio

AI21 Labs specializes in Natural Language Processing to develop generative AI models that can understand and generate text. The Tel Aviv-based startup was founded in 2017 by Yoav Shoham, Ori Goshen, and Amnon Shashua. In 2019, the startup raised $9.5 million, and in October 2020; it launched Wordtune which was an AI-based writing app. This was followed by Walden Catalyst investing $20 million in AI21 Labs in November, soon after which the company completed a $25 million series A round led Yakov Livshits by Pitango First. Anthropic vouches for Claude to be an honest, helpful, and harmless AI system, and much less likely to produce harmful outputs than present chatbots, which have been known to be toxic, biased, use offensive language and hallucinate. According to Anthropic, Claude cannot access the internet and is designed to be self-contained and trained to avoid sexist, racist, and otherwise toxic outputs, along with preventing human engagement in illegal and unethical activities.

The shift to foundational models and few-shot learning will be interesting to observe, as it could impact the importance of large, fine-tuned datasets that previous business models relied on. We are excited for healthcare specific data tooling that will help companies leverage these new technologies. With the large shortage of healthcare workers, AI-based recruiting tools (WinnowHealth, ReverenceCare, IntelyCare) are focusing on increasing marketplace liquidity. We’re excited about how these companies can uplevel and incentivize their workforce using AI technologies. Although the application of generative AI systems isn’t as clear to us, this space is crucial to addressing a core issue in healthcare. In the last ten years, we’ve seen incredible progress in algorithms, data access, and computing power.

Customizable language models specific to sectors, such as customer service, are also being developed. Diffusion models are a type of generative AI model that can be used for a variety of tasks, including image generation, image denoising, and inpainting. The new era of language models are Transformer-based, which is a type of deep learning architecture for natural language processing (NLP) tasks. The most well-known transformer-based LLMs are the GPT family, developed by OpenAI.

• Generative AI is revolutionizing the way we live, work, and interact with the world around us.
• Open finance has supported more inclusive, competitive financial systems for consumers and small businesses in the U.S. and across the globe – and there is room to do much more.
• Transformers have become a cornerstone for natural language processing and are currently the most popular architecture for generative AI models.
• Consequently, the initial effort or “activation energy” required is quite high for health systems.
• The new generation of AI Labs is perhaps building the AWS, rather than Uber, of generative AI.

Streaming platforms use AI algorithms to suggest relevant content based on viewers’ preferences, enhancing user experience. Moreover, generative AI powers interactive storytelling and game development, creating immersive virtual worlds and dynamic gaming experiences. A recent entrant into the realm of open-source foundation models is Stable Diffusion. Starting from random noise, Stable Diffusion models gradually transform it into meaningful data, such as an image or a piece of text. Despite their computational intensity, recent improvements have made these models increasingly accessible and applicable across various domains.