LLMs: Building a Less Artificial and More Intelligent AI Human

One of the most exciting developments in artificial intelligence-powered technology is the emergence of Large Language Models (LLMs) and Artificial Intelligence Avatars (AI Avatars) coming together to create conversational AI humans.

The market for AI avatars has an estimated value of $156.19 billion by 2032 (The Brainy Insights). Many companies, including Samsung’s STAR Labs and startups like DeepBrain AI and Synthesia, are continuously innovating their artificial intelligence (AI) technology and improving their AI humans to create engaging and enjoyable AI experiences.

By 2026, half of B2B buyers will interact with a digital human in a buying cycle. — Gartner, 2022 Hype Cycle Report

Conversational AI avatars are already changing how businesses and organizations engage with customers and users.

Continue reading to discover:

• The concept of LLMs (Large Language Models)
• The development of AI Avatars
• Creating human-like conversational AIs
• The impact of conversational AI avatars on interactions between customers and companies

What is a Large Language Model (LLM)?

The introduction of ChatGPT on November 2022 marked a pivotal moment in the popularization and widespread acceptance of Generative AI and Large Language Models (LLMs). OpenAI demonstrated to the public how LLMs and AI technology can help companies and individuals automate tasks, stimulate creative thinking, and even aid in software coding — marking a new era of AI utilization.

AI is like electricity. Just as electricity transformed every major industry a century ago, AI is now poised to do the same. – Andrew Ng, the founder of Google Brain and former Vice President of Baidu

At its core, LLMs are a type of artificial intelligence that handles various tasks involving natural language processing (NLP). These tasks include generating and categorizing text, providing conversational responses, and translating text between languages.

Large Language Models (LLMs) are exceptional in their ability to comprehend and replicate human language naturally. They can understand context, construct natural responses, and even emulate conversational nuances, resulting in interactions that resemble how real humans communicate with each other.

Large vs Small LLMs

The term 'large' refers to the number of parameters (weights and values) that the LLM can adjust and change as it trains. The largest LLMs like Open AI’s GPT-3, GPT-4 and Google’s PaLM 2, LaMDA, BERT, Bard, and Meta’s Llama 2 contain hundreds of millions to billions of parameters. Research teams like Technology Innovation Institute’s Falcon 40B, UC Berkeley’s Vicuna, Koala, as well as Stanford University’s Alpaca ****also have released their own large language models.

Despite the rise of massive LLMs, recent trends have shifted towards smaller, more accessible, and customizable models such as Ada, Atlas, and Cohere.

Smaller language models are not only more cost-efficient, but they are also much more accurate in achieving domain-specific business tasks. This is because they are trained and optimized on carefully-vetted data that addresses the exact use cases that users and businesses care about, rather than being trained on all publicly available data — which includes both good and bad data.

It’s not enough to just scrub the internet to train LLM.??Quality data counts - we all are going back to this truth — Thomas Wolf, co-founder and CSO of Hugging Face

Custom LLMs

Users and businesses who want more control over responses can customize the data an LLM pulls from to modify their behavior and output. There are two main ways to achieve this:

1. Embedding. Large language models use embeddings to project textual data, such as words or sentences, into a high-dimensional vector space. This allows the LLM to capture semantic relationships and contextual nuances by categorizing texts into labels or categories, such as positive or negative, spam or not spam, news or opinion, and so on (Microsoft).
2. Fine-tuning. Fine-tuning large language models refers to the process of refining a pre-trained AI language model by training it on a narrower, task-specific dataset. This process helps the model improve and perform better when creating precise and relevant content, while still keeping its original abilities. Fine-tuning is like giving someone specialized training to become an expert in a specific field after they already have general knowledge.

What are AI Avatars?

Digital humans are interactive, AI-driven representations that have some of the characteristics, personality, knowledge, and mindset of a human. — Gartner 2023

Avatars are virtual representations of users or objects in digital environments. Traditional avatars are always under the control and management of humans and cannot perform actions that are not programmed in advance. On the other hand, AI avatars and AI humans can interact with real people without relying on human agency or direction. They can also understand and make decisions themselves based on the context of the world around them.

Over the past few years, AI humans have made significant strides in appearing and sounding incredibly lifelike. DeepBrain AI claims their AI avatars look and act 96.5% similar to humans, and you can see how realistic Samsung’s STAR Labs digital humans look in the picture below.

Key elements of AI Avatars:

1. Hyper-Realistic Appearance: Digital humans are becoming increasingly more realistic and lifelike. While they are often created in a studio and then synthesized by a machine learning program, it is now becoming faster and easier to create digital avatars using just photos or self-filmed videos alone.
2. Natural Body Movements. AI avatars use an algorithm called Generative Adversarial Network (GAN) to create smooth and natural mouth and body movements. AI Humans can even sync their lip movements realistically to any audio or text input.
3. Low Latency Responses: DeepBrain AI reported a latency rate of less than 1 second between human input and avatar output. Conversational AI avatars are able to respond to queries with minimal delay, resulting in a conversational flow that is natural and realistic.
4. Text-to-Speech (TTS). Text-to-speech (TTS) technology has come a long way since early voice assistants. Nowadays, TTS can produce extremely realistic voices in all languages. When combined with lip-syncing, it can generate a convincingly real, speaking digital human replica.

What are Conversational AI Avatars?

In 2023, AI avatar and LLM technologies converged to create powerful conversational AI humans. Teams from DeepBrain AI, Soul Machine, Uneeq, and D-ID have already started making conversational AI avatars, and the results have been all-around impressively natural and successful.

You can think of LLMs as the brains behind conversational digital humans, while AI avatars serve as the vessel or body. Together, they perform better than regular AI chatbots by mimicking the entire process of human communication, including nonverbal cues like facial expressions and body language.

Conversational digital humans are also equipped with powerful capabilities such as memory, emotions, and creativity to fully emulate human cognition and engagement. This technology offers endless possibilities for businesses seeking to create engaging and personalized experiences for their customers.

LLMs Bring AI Humans to Life

One of the most exciting aspects of using LLMs with conversational AI is the ability to create and customize their personas and personalities.

You can design a "customer service representative who makes cringe-inducing dad jokes," or a "friendly, bubbly café cashier who loves true crime." Companies can even give their brand mascot a persona for customers to engage in face-to-face conversations!

Startups like Inworld AI and Character.ai are already using LLMs to make multi-dimensional AI avatars with interesting personalities, backstories, and even flaws. Combined with conversational AI avatars, businesses can make special and fun experiences for users.

Imagine going to a Disneyland kiosk and getting directions from your favorite Disney character. Or having an AI version of your CEO welcome and talk to you on your day of work!

Additional Advantages of Conversational AI Avatars

Conversational AI humans offer a comprehensive range of advantages and benefits from both LLMs and AI avatars… and then some! Here are some key highlights:

Welcoming and Personable Presence

As our lives become increasingly digital, conversational AI avatars provide a warm and inviting interface for interaction. By adding an element of humanity into AI, these AI avatars create a more engaging and personalized user experience.

Round-the-Clock Availability

AI humans can efficiently manage high volumes of inquiries simultaneously, ensuring personalized service at all times.

Break Down Language Barriers

Conversational AI humans fluently understand and speak multiple languages on demand. According to Uneeq, their digital humans can understand 74 languages and speak 43 of them.

Omnichannel support

Conversational AI avatars can be configured to remember all prior touchpoints and interactions, ensuring a consistent communication journey for users and customers. They are also accessible across all digital platforms, from the web and mobile devices to kiosks and even within metaverse environments.

This combination of human avatars and LLMs is re-writing the rule book on traditional human-computer interaction and opening new avenues for enhanced customer experiences, transformative education and training, immersive simulations, personalized content creation, and cross-cultural communication. — Eric Jang, Founder and CEO of DeepBrain AI

Conversational AI Humans in Customer Experience (CX)

CX-focused business initiatives prioritize meaningful customer interactions over simple transactions. With conversational AI avatars, customers can engage in extensive conversations, pose multiple inquiries, and find it easier to discuss matters they might hesitate to raise with a human agent.

AI humans offer support for customers who desire unique, more engaging, and impactful customer service. The following section delves into the practical applications and positive impacts conversational digital humans have already made in various industries.

1. Financial Consultation:

AI avatars are reshaping finance, as well, shown by DeepBrain's AI Bank Tellers at KB Bank. These avatars streamline routine banking inquiries, allowing their real-life human coworkers to focus on more complex tasks.

Uneeq's "Digital Dani" simulates expert financial discussions from UBS, a banking institution in Switzerland. Digital Dani provides clients with the convenience of on-demand expert financial advice.

2. Educational Support:

In the education sector, conversational AI humans can become reliable, always-available AI tutors. DeepBrain AI extends its portfolio into education with real-time AI tutors at Kyowon Co. who help students in learning through interactive lectures and Q&A sessions.

Conversational AI humans such as Soul Machines Mya and Emma guide students through their academic journey at Maryville University. These digital mentors assist with applications, share insights about campus life, and offer career and academic guidance.

3. Hospitality:

DeepBrain's AI Concierges at Novotel showcases the use of AI human technology in hospitality. Available 24/7, these AI avatars answer all travel and service queries, enabling guests to fully enjoy their stay.

Similarly, Soul Machines’ "Digital Iris" offers support to travelers at Dallas Fort Worth Airport, enhancing their journey and reducing travelers’ stress with real-time information and updates.

4. Media Engagement:

Conversational AI humans are redefining fan-celebrity interactions. By partnering with America’s Got Talent judge Howie Mandel, DeepBrain AI is bridging the gap between celebrities and fans. Creating a celebrity AI twin helps foster a more personal connection by allowing fans to interact and converse with a digital version of their favorite star.

Uneeq's "Digital Einstein" takes this concept further, allowing users to engage with a recreated version of the renowned physicist, Albert Einstein, unlocking his wisdom and humor.

5. Healthcare and Wellness:

Conversational AI is enhancing health and wellness services. DeepBrain AI has partnered with Roche, a Swiss multinational healthcare company, to create an AI health advisor. The AI Doctor offers 24/7 support for health and Roche-related inquiries.

Uneeq's "Digital JK" with Groov assists users in achieving better sleep patterns, contributing to improved mental health.

6. Enriching Lives:

The impact of conversational AI avatars extends even to the afterlife. DeepBrain's "Re;memory" memorial service recreates loved ones into AI avatars, providing solace and connection to help their family heal and keep their memory alive.

Only the beginning….

The emergence of AI avatars and conversational AI humans represents a significant leap forward in technological development. It opens up new and limitless possibilities for businesses aiming to create more personalized and engaging experiences for their customers. It is both exciting and daunting to wonder what the future holds, but one thing is sure — AI human technology is just getting started.

As we move forward, it is essential to note that LLM and AI avatar technology is still in its infancy and has yet to reach its full potential. With advancements in machine learning and natural language processing, we can expect to see even more sophisticated AI avatars and conversational AI humans in the near future. These advancements will undoubtedly lead to new innovations and capabilities, changing the way we live and work in ways we can only begin to imagine.