Best Multimodal AI Tools should seamlessly combine different sensory inputs such as text, images and audio in order to expand and deepen their understanding. These tools use advanced natural language processing, computer vision and audio processing technologies to develop a holistic and nuanced understanding of any data encountered. Content generation and sentiment analysis are among their many outstanding capabilities, offering users a richer and more context-sensitive user experience.
These AI tools have the capability to process and interpret information across multiple modalities, making them suitable for various applications such as virtual assistants, language translation services, image recognition and multimedia content creation. As they advance further they could transform how we engage with and leverage artificial intelligence in everyday life.
Here is List of Best Multimodal AI Tools
- Runway Gen-2
- Meta ImageBind
- Inworld AI
- Google Gemini
- Snorkel AI
- IBM Watson Studio
10 Best Multimodal AI Tools for 2024
1. Runway Gen-2
Runway Gen-2 is a multimodal AI model capable of producing videos using text, image or video input as inputs. Gen-2’s user-friendly interface enables them to use text-to-video, image-to-video and video-to-video conversion methods in order to generate their own original video content.
Users also have the ability to replicate an existing image or prompt in video form, enabling them to emulate its style as inspiration for new pieces of content creation. If there’s an image they like, replicating its compositional style allows them to replicate its style for themselves in new material.
Gen-2 offers users with the capability of editing video content. By using text prompts, a user can isolate and modify subjects within a video, as well as customize for higher fidelity results. Gen-2’s multimodal approach to generative AI provides enough versatility for you to experiment and begin creating videos from scratch.
2. Meta ImageBind (Best Multimodal AI Tools)
Meta ImageBind is an open-source multimodal AI model capable of processing text audio visual movement thermal and depth data; Meta claims this is the first AI model combining information across six modalities.
Example: Provide ImageBind with audio from a car engine and an image or prompt of a beach, and it will use this combination to create new art.
The model itself can be utilized for various tasks, including creating images from audio clips and searching multimodal content (text, audio and image) as well as equipping machines with the capacity for understanding multiple modalities.
Meta stated in their announcement blog post: ImageBind provides machines with a holistic understanding that links objects in photographs to how they sound, their 3D shape, their warmth or coldness and movement patterns.
This multimodal AI model has various applications, most notably its ability to empower machines with sensors to accurately perceive their surroundings.
3. Inworld AI
Inworld AI is a character engine designed for developers who wish to create non-playable characters (NPCs) and virtual people for digital worlds and metaverse environments. Users can utilize LLms software for character development to populate digital worlds or metaverse environments with these characters.
One of the key aspects of Inworld AI is its multimodal AI capabilities, enabling NPCs to communicate using natural language, voice recordings, animations and emotions.
Developers using multimodal AI can craft intelligent NPCs. Not only are these NPCs autonomous but they have distinct personalities and will respond emotionally when specific trigger conditions arise, not forgetting to store memories from past events.
Inworld AI provides a multimodal solution for those wishing to utilize LLMs in order to create immersive digital experiences.
GPT-4V or GPT-4 with vision is a multimodal version of ChatGPT that enables users to enter both text and images. Users can now combine text, voice, and images when responding to prompts.
ChatGPT can respond to users in up to five different AI-generated voices, giving users the option of engaging the chatbot through voice interactions (although voice only available on Android and iOS apps).
ChatGPT users also have the ability to generate images directly within ChatGPT using DALLE-3, with 100 million weekly active users as of November 2023 utilizing GPT-4V variant. As one of the largest multimodal AI tools on the market, GPT-4V variant is one of ChatGPT’s key offerings.
5. Google Gemini (Top Multimodal AI Tools)
Google Gemini is a natively multimodal LLM that can recognize and generate text, images, video, code and audio. Gemini comes in three main variants – Ultra, Pro and Nano.
Gemini Ultra is the largest LLM available. Gemini Pro was built to scale across multiple tasks while Gemini Nano provides efficiency for on-device tasks – making it perfect for mobile device users.
Gemini has shown promising performance since its introduction, according to Demis Hassabis, co-founder and CEO of Google DeepMind. On 30 of 32 benchmark tests it outperformed GPT-4.
Gemini has also become the first language model to outperform human experts on massive multitask language understanding (MMLU), and achieved an industry-leading score on multimodal task benchmarking (MMMU).
6. Snorkel AI
Snorkel AI is a revolutionary platform designed to streamline the creation of labeled training data for machine learning models. Snorkel AI uses “weak supervision” to enable users to quickly generate large-scale training datasets by combining various labeling sources such as heuristics, external knowledge bases, and existing models for labeling data at scale. This approach allows the training of models on large volumes of data without manual annotation, thus meeting one of the primary challenges in machine learning.
Snorkel AI stands out due to its flexibility and adaptability, making it perfect for tasks spanning various data types and domains – from natural language processing to computer vision. By streamlining labeling processes more quickly, it empowers data scientists and developers to create robust machine learning models more quickly – opening new avenues of innovation and discovery in their respective fields.
Deepgram is a leading provider of speech recognition technology that uses advanced machine learning algorithms to transcribe and analyze audio content with remarkable precision. Deepgram stands out in the market by offering real-time, scalable and multilingual speech processing that meets the demands of multiple industries, such as customer service, healthcare and finance.
Not only can their platform convert spoken words into text, but it also provides insights into context, sentiment, and meaning of conversations. Deepgram’s focus on deep learning and neural network-based models enables it to continuously enhance its transcription capabilities, making it a valuable solution for businesses and organizations that require cost-effective yet high-quality solutions for processing spoken language applications.
8. SenseTime (Top Multimodal AI Tools)
SenseTime is an innovative artificial intelligence company renowned for its cutting-edge computer vision technologies. Specializing in facial recognition, image/video analysis and autonomous driving solutions, SenseTime has emerged as a key player in AI. Advanced algorithms developed by this company enable precise identification and analysis of visual data, making it a useful resource for applications like security surveillance, retail analytics and smart city initiatives.
SenseTime’s dedication to innovation can be seen through its research and development efforts, constantly pushing the envelope on what’s possible in computer vision. By helping industries improve safety, efficiency, and convenience with their AI visual intelligence solutions, SenseTime plays an integral part in shaping its future.
Clarifai is a leading AI company renowned for its expertise in visual recognition and image analysis. By employing deep learning and machine learning techniques, Clarifai delivers solutions that enable businesses and developers to extract meaningful insights from images and videos. This platform excels at image classification, object detection, and facial recognition; making it well-suited to many different uses such as content moderation, personalized user experiences and data organization.
Clarifai offers developers user-friendly APIs and pre-trained models to integrate powerful visual recognition capabilities easily into their applications. Their commitment to stay at the forefront of AI innovation also positions Clarifai as an invaluable resource when seeking robust and scalable image and video analysis solutions in today’s rapidly developing artificial intelligence environment.
10. IBM Watson Studio
IBM Watson Studio provides an efficient platform for developing, training, and deploying machine learning models. At Watson Studio, our focus is to enable data scientists, developers and business analysts. With one central platform for working with data and developing AI solutions. Watson Studio supports various data types and machine learning frameworks, allowing users to experiment with various algorithms and models.
Furthermore, Watson Studio facilitates collaborative projects through features for version control, project sharing and team collaboration. IBM Watson Studio makes machine learning accessible for organizations looking to utilize AI-driven initiatives through data, with robust tools for data preparation, model training and deployment. As an essential resource in their data-driven initiatives.