Best Multimodal AI Tools for 2024

Multimodal AI, which combines different data modes like text, images, speech, and video to understand information, is rapidly advancing. As this technology develops, multimodal AI models are becoming better at complex real-world tasks across industries. In this post, we will explore the top 5 most promising multimodal AI tools that are likely to make major impacts this year.

1. Google Gemini: Leads in Performance Benchmarks

Unveiled in the end of 2023, Google's Gemini model aims to excel at a breadth of multimodal abilities. Gemini comes in multiple versions optimized for efficiency, scale and ultra-high performance.

Early benchmark results indicate Gemini’s potential:

• Gemini Ultra surpassed state-of-the-art scores in MMLU language understanding evaluations.

• Across 32 benchmarks, it outdid GPT-4 in 30 - a stunning achievement.

• Gemini is the first AI system to beat human experts in massive multitask language understanding assessments.

With strengths in reasoning, communication, and rapidly assimilating concepts from different modalities, Gemini’s applications could be game-changing.

2. ChatGPT: Gets a Multimodal Upgrade

ChatGPT exploded in popularity thanks to its eloquent text-generation capabilities. Now with GPT-4V, it can ingest text, images, and voice data to produce responses using a combination of mediums.

Users can get answers via text or listen to replies generated by five AI voices. Built off DALL-E 3, it can also generate images to accompany texts.

As the chatbot boasting over 100 million weekly users as of late 2023, expect its new features to have widespread impacts. ChatGPT is leading the integration of LLMs into our everyday information searches.

3. Inworld AI: Creates Hyper-Real Digital Characters

Inworld AI allows developers to build AI-powered virtual characters to populate digital worlds. Its NPCs move beyond chatbots - they integrate multiple data types to act with autonomy, emotion and dynamic memories.

Key strengths include:

• Expressive capabilities drawing on voice, face/body visualization and languages

• Persistent memories of past events and interactions

• Complex social behaviors guided by modular AI architectures

As the metaverse gains momentum, expect models like Inworld AI to make virtual characters increasingly human-like and immersive.

4. Meta ImageBind: Understands the World Multimodally

Announced in middle of 2023, Meta’s ImageBind processes data across six modalities — text, audio, visual, motion, depth and thermals. This equips AI with enhanced perceptual abilities and multimodal reasoning.

Use cases include:

• Creating images from audio clips and vice versa

• Searching for multimodal content matches

• Robots understanding environments via sensors

This tool shows the expanding capabilities of AI for cross-modal perception, a stepping stone toward more human-like cognition.

5. Runway Gen-2: Multimodal Video Generation

Need a video generating solution? Runway Gen-2 lets users create custom videos with text, image or video inputs. Applications include:

• Text-to-video

• Image-to-video

• Video style transfer learning

Advanced editing functions also enable modifying subjects, attributes and aspects within generated videos.

As online video consumption grows exponentially, multimodal video generation tools stand to make production faster, cheaper and more accessible to all.

The Future Is Multimodal

From human-like VR characters and sensor-enabled robotics to video production and enhanced search, these models demonstrate the early promise of multimodal AI. As researchers continue pushing boundaries, tools leveraging multiple modalities are likely to drive many of AI’s most groundbreaking innovations in 2024 and beyond. The progress seen already indicates that multimodality helps AI better understand - and shape - our multifaceted world.