Top Alternatives to OpenAI

AI can not only boost our analytic and decision-making abilities but also heighten creativity, - Harvard Business Review

Nowadays, Generative AI has become a hot topic in the tech industry. Barely surprising, as it creates novel content ranging from code to images and even human-like speech. One notable example is ChatGPT, an already famed chatbot from OpenAI that attracted 1 million users within a week of its release in late 2022.

However, beyond the hype, not only tech giants, but also many startups adopt Generative AI to expand into various areas, such as search engines and motion capture animation. It is noteworthy that most of these startups have received little or no equity financing, meaning there is still a huge opportunity for investors to enter the market early and capitalize on this game-changing technology.

The Generative AI market is estimated at $10.79 billion in 2022. It is expected to reach approximately $118.06 billion by 2032, growing at a CAGR of 27.02% during the forecast period from 2023 to 2032. This tendency opens up significant opportunities for businesses and investors to benefit from this new technology.

Source: precedenceresearch

This article will explore the Generative AI models from Open AI and its analogues, discuss the Generative AI market,and consider how Generative AI is useful in various industries.

Exploring Generative AI Capabilities with OpenAI

Generative artificial intelligence or Generative AI is a type of AI technology. The prerequisite for its development was, first of all, the generation of new content. Generative AI systems utilize generative models, such as large language models, to create new content based on the training dataset used to build them. It creates text, images, and other media in response to user requests. What's more, Generative AI applications produce entirely new content, such as converting natural language to code, creating 3D assets from 2D images, or creating human voices from scripts.

Over the past decade, artificial intelligence research has become a real breakthrough. It mainly happened due to the groundbreaking research of large technology companies, especially OpenAI.

OpenAI is an AI research organization. It was founded in 2015 by top tech industry leaders like Elon Musk and Sam Altman. OpenAI specializes in developing artificial intelligence technologies, including machine learning and natural language processing models.

Generative Models Developed by OpenAI

OpenAI is at the forefront of developing generative models that can transform various industries. These models use large-scale neural networks to create unique content based on input requests. Here are some of the main generative models by OpenAI:

• GPT-2 (Generative Pre-trained Transformer 2) is an unsupervised AI large language model announced in February 2019. It has a generative pre-trained transformer architecture, was trained on a dataset of 8 million web pages and has 1,5 billion parameters. The GPT-2 model can translate text, answer questions, summarize short passages and generate coherent and realistic human-like text.
• GPT-3 (Generative Pre-trained Transformer 3) is a large language model released in May 2020. The model was trained using generative pre-training and has 175 billion parameters. GPT-3 model is applied to various applications and chatbots for translation, summarization, question-answering and content creation. It is capable of natural language processing and can generate high-quality humanoid text. OpenAI offers developers GPT-3 API, which allows them to integrate natural language processing capabilities into apps.
• GPT-4 (Generative Pre-trained Transformer 4) is a multimodal large language model released in March 2023. As a transformer, it was pre-trained to predict the next token and tuned with human and AI feedback. The version of ChatGPT based on GPT-4 is an improvement on the previous GPT-3.5 based. Unlike previous models, GPT-4 can accept images and text as input.
• The OpenAI Codex is a generative model that uses natural language processing to generate code for over a dozen programming languages, especially Python. Codex was announced in 2021. It is a descendant of GPT-3, fine-tuned for use in programming applications, further trained on code from 54 million GitHub repositories. And it is also the AI behind the GitHub code autocomplete tool Copilot.
• DALL-E is a transformer generative model capable of creating digital images from textual input, released in 2021. The model uses a 12-billion-parameter version of GPT-3.
• CLIP (Contrastive Language-Image Pre-training) is a generative model that can link natural language and images in a way that allows the model to generate text descriptions of a given image.
• MuseNet is a generative model that can create new musical compositions in different styles. It was announced in 2019.
• Whisper is a speech recognition model for general purposes, announced in 2022. It is trained on a large audio dataset and can perform multilingual speech recognition, language identification and speech translation.
• ChatGPT is a well-known member of the GPT family of language models. It is an artificial intelligence chatbot built on top of GPT-3.5 and GPT-4 models and released for broad authority in November 2022. Although the primary function of a chatbot is to mimic a human conversationalist, ChatGPT can write and debug computer programs, write business pitches, essays, and lyrics, compose music, teleplays, fairy tales, answer test questions, etc.

Generative AI Market Overview

While tech giants like Google, IBM and AWS are working to build their Generative AI technologies, they need to catch up to agile AI startups, which are much easier to take risks to fill these niches. Investments in startups, including AI startups, have grown by $5 billion from 2020 to 2022.

Among the most recent AI-funded companies are those focused on chatbot companies and machine learning. Take, for example, the OpenAI deal, which raised a $10 Billion investment from Microsoft in January 2023. The central part of the deal is that Microsoft will provide OpenAI with the Azure computing power needed to run the AI systems.

Clearly, Generative AI startups have become the newest big players in the tech world.

Source: CBINSIGHTS

For now, in the world of Generative AI, six companies have achieved unicorn status (worth $1 billion or more):

• OpenAI
• Hugging Face
• Lightricks
• Jasper
• Glean
• Stability AI.

The new members of the unicorn club are Jasper and Stability AI after their over $100 million mega rounds in the fourth quarter of 2022.

Source: CBINSIGHTS

As for the categories in which Generative AI has received significant development, these are Generative Interfaces. This category skyrocketed in 2022, with funding growing nearly 8 times year-over-year and reached $520 million.

Companies that fall into the Generative interface category focus on developing a new generation of human-machine interfaces. Their goal is to make interacting with a computer more conversational, like communicating with people. They utilize generative models in different industries to execute natural language commands and create applications with powerful features such as web search, private search (on company servers and apps), productivity, and knowledge management.

The map below shows the application landscape of the Generative AI companies and startups market.

Source: CBINSIGHTS

Here we see that companies in the field of Generative AI are mainly spread due to their core specialization:

• Text generation. Applied in marketing, sales, support services (chat/email), knowledge management and general writing.
• Video content. Used for video editing and generating personalized videos.
• Image content. Used for image generation, media and advertising purposes.
• Code creation. Applied in code generating, documentation, web app builders, and text-to-SQL conversion.
• 3D model generation.
• Speech generation.
• Other areas: gaming, music, audio, biology and chemistry.

Tools with the Same or Similar Functionality as OpenAI

Currently, OpenAI tools for natural language processing have gained wide popularity not only among technical specialists or businesses but also among Internet users. However, exploring alternative tools that offer similar functionality is always a good idea. Perhaps they better suit your needs or provide better value for money.

Here are some of the alternative tools to OpenAI you might want to know:

• Midjourney. Midjourney is a Generative AI program and service built and hosted by an independent research lab called Midjourney Inc. The program allows users to generate images from natural language descriptions or "prompts". This feature is similar to other OpenAI's DALL-E.
• Bard. Bard is a Generative AI conversational chatbot specifically designed by Google to compete with OpenAI's ChatGPT. It is based on the large language model LaMDA. Bard is designed to be an assistant in productivity and creativity. It understands the context of the conversation and responds humanly, may generate code, scripts or lyrics. However, since the launch in March 2023, users are still evaluating the capabilities of the chatbot and giving rather mixed reviews. The model is still experimental, and its answers may be inaccurate.
• Hugging Face. Hugging Face is a company that develops machine-learning tools for natural language processing, including the famous Transformers library. The library allows users to create, train and deploy NLP models through a simple interface. Hugging Face also provides a platform for sharing machine learning models and datasets, facilitating user collaboration.
• Glean. Glean is an intelligent work assistant platform. It uses deep-learning models to interpret natural language queries in the context of specific organizational characteristics, including departments and individual users. The platform seamlessly integrates with a range of enterprise applications and platforms, making it easier to access business information sources.
• Jasper. Jasper is an AI content platform designed for business and marketing content generation. It works well for social media, blogs, advertising, emails, and website content.
• Cohere. Cohere is a Canadian startup that offers natural language processing models. Their NLP solutions are designed to support business operations. Its AI models can be used for text generation, identifying toxic content in posts, or performance improvement of search engines.
• Opus. Opus is an open-source initiative that aims to develop high-quality translation models. It can convert text to video assets and make games, movies or simulations. Developers can easily integrate it into their applications.
• Andi. Andi is a search bot powered by Generative AI that helps users to search for information on the web, summarize and explain it. Andi provides users with answers. It is like having a conversation with an intelligent friend.
• Diagram. Diagram is a design tools development company. It provides prototyping and other Generative AI design features to its customers.
• Replit. Replit is a SaaS startup and an online integrated development environment that allows users to create online projects and write code.
• Stability AI. Stability AI is an open-source Generative AI startup for image and video generation. It is known for his innovative Stable Diffusion text-to-image model.

Here are just a few examples of the many tools available for machine learning and artificial intelligence. Each tool has its own strengths and weaknesses, and the best choice will depend on the specific task or application.

Why Integration or Using Generative AI in Business is Important

According to a February 2023 survey, nearly 25% of US business leaders reported $50,000 to $70,000 in savings by incorporating ChatGPT into their operations. In addition, 11% of respondents said they had saved over $100,000 since implementing ChatGPT into their workflow. These results point to the significant savings potential of ChatGPT for businesses, demonstrating the effectiveness of Generative AI tools for businesses.

Integrating Generative AI into business operations can provide some benefits:

• Automate repetitive tasks. Generative AI can automate repetitive or time-consuming tasks. It frees up employees for more complex and strategic tasks.
• Improved efficiency and productivity. By automating tasks, Generative AI can help companies complete tasks faster, increase productivity, and reduce costs.
• Generation of new ideas and solutions. Generative AI can be used to generate new ideas to solve business problems. You can get a fresh look and be one step ahead of the competition.
• Personalization of customer experience. Generative AI personalizes the customer experience by generating customized recommendations, offers, or content based on customer data and behavior.
• Improving the decision-making process. Generative AI can provide recommendations based on processing large data sets.

Below, we've compiled some of the business challenge areas where Generative AI can bring business value.

Overall, integrating Generative AI into businesses can help them to operate efficiently and improve the customer experience or decision-making. However, ensuring that AI is responsible, ethical, and in line with business values and goals is crucial.

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Examples of Integration and Use Cases of Generative AI in Various Industries

Generative AI drives startup innovation, automates tasks, and delivers personalized customer experiences. Open-source tools and APIs have made it easier for new players to enter the market. Examples include Generative AI for patent writing, drug development, search engines, and game design. Nowadays, it is adopted in various industries. Here are some specific examples:

Healthcare

Generative AI technologies are utilized for protein design, medical conversation summary and wellness music design. Protein and Drug Design: a Generative AI platform that helps create novel protein sequences and molecular structures. They reduce the time it takes to develop a single protein from months to weeks. It can also generate synthetic medical images for diagnostic purposes. Conversation Summary: helps tailor text summaries to medical conversations. Wellness Music: Uses artificial intelligence to design soundscapes for wellness (sleep, focus and relaxation).

Legal

Companies are developing tools to help lawyers. Patent Generation: converts patent claims to application projects. Creates diagrams, flowcharts and summaries from patent claims. Case Search and Summarization: build AI tools that look for information related to a case and help with drafting, scan open source data sets about wrongdoing (such as privacy or health violations) and assist lawyers in building a case.

Gaming and metaverse

Startups utilize AI to create various texts, adventure games, virtual worlds, and video game non-player characters NPCs. Text Adventure: AI helps to develop a text adventure game, generating open storylines. Virtual Worlds: assist in creating 3D objects, scenes and animations to build the virtual world. Video game NPCs: helps to develop video game NPCs to make the game more immersive.

Education

Startups utilize AI to understand textual content, help students find answers, and automatically generate quizzes and questionnaires. Test and quiz generation: analysis of educational materials for automatic generation of quizzes and questions. Tools for personal learning: downloads academic research papers, then AI explains confusing paragraphs, builds chats where students can ask questions, and AI finds the correct answers.

Finance

Generative AI can be used to analyze financial data and generate forecasts. It helps in decision-making and reducing risk. For example, banks can use AI to detect fraudulent transactions and anomalies in customer behavior.

Fashion

Companies use AI to design clothes and create synthetic models for marketing and virtual fittings. This includes creating full-length virtual models that can be used for e-commerce purposes.

Architecture

AI is used to design construction sites, architecture, and floor plans. It is also used to create schematic designs for architects and account for zoning, capital cost, and daylight.

Marketing

Generative AI creates personalized customer content, product descriptions, social media posts, and marketing email. This technology can help improve engagement and conversion rates.

These are just a few options of how Generative AI can be used in various industries. We can expect even more innovative use cases to emerge as technology advances.

Summing up

Generative AI has opened up innovative development opportunities for companies. With the power of Generative AI, businesses can increase efficiency, automate repetitive tasks, generate new ideas and solutions, and stay competitive.

OpenAI is one of the leaders in Generative AI model development. Among its generative models are GPT-2, GPT-3, Codex and others. However, other AI startups also work in this field. They are more flexible in decision-making and take risks easily. They have already built Generative AI tools for industries such as healthcare, law, games, education, finance, fashion, architecture, marketing etc.

Currently, enterprises have various generative AI tools to meet their needs and provide the best value for money. At the same time, everyone must consider ethical considerations such as transparency, accountability and non-bias when implementing the possibilities of generative AI in their activities.