Unlocking Business Success: Leveraging LLMs, Insights from Jaromir Dzialo, Exfluency

Introduction: Exfluency’s Hybrid Intelligence Solutions

Exfluency is a tech company that specializes in providing hybrid intelligence solutions for multilingual communication. Through the utilization of AI and blockchain technology, Exfluency offers modern language tools to tech-savvy companies, with the aim of making linguistic assets as valuable as any other corporate asset.

Developing Tech Trends in Multilingual Communication

– The dominance of AI, particularly ChatGPT, is a significant trend in the multilingual communication space.
– Companies in the language industry are either panicking or trying to catch up due to the significant technology deficit in this vertical.
– Innovation, especially AI-innovation, cannot be treated as a simple plug-in solution.

Benefits of Using Large Language Models (LLMs)

– Off-the-shelf LLMs like ChatGPT and Bard provide immediate solutions with impressively well-formulated answers.
– The true benefits of LLMs are realized when they are provided with immutable data to feed the models.
– Data quality plays a crucial role in maximizing the potential of LLMs.

Components of LLMs’ Language Learning

• Data: LLMs are trained on vast amounts of text data from various sources, enabling them to learn a wide range of language patterns, styles, and topics.
• Patterns and Relationships: LLMs analyze patterns and relationships within the data to understand grammar and semantics.
• Statistical Learning: LLMs use statistical techniques to generate contextually relevant text by estimating the probabilities of word sequences.
• Contextual Information: LLMs consider the entire context of a sentence or passage to produce accurate and appropriate responses.
• Attention Mechanisms: LLMs employ attention mechanisms to focus on relevant information while generating responses.
• Transfer Learning: LLMs use a technique called transfer learning to leverage their broad language knowledge while adapting to specific tasks.
• Encoder-Decoder Architecture: In certain tasks like translation or summarization, LLMs use an encoder-decoder architecture to process input and generate output text.
• Feedback Loop: LLMs can learn from user interactions and adjust their responses based on feedback, improving their performance.

Challenges of Using LLMs

– Users often become the product, as big tech companies profit from the data they provide.
– Open LLMs can provide seemingly well-formulated but potentially unreliable answers without proper references or links.
– Ensuring data security, confidentiality, and quality is a challenge.

Overcoming LLM Challenges with Blockchain

– Blockchain technology enables the creation of an immutable audit trail for data, ensuring control, confidentiality, and support with useful meta data.
– Storing data in databases allows for the inclusion of necessary source links to validate generated responses.

Utilizing Private, Anonymized LLMs for Multilingual Communication

– Ensure that data used with LLMs is immutable, multilingual, and of high quality.
– By doing so, LLMs can become a game changer in multilingual communication.

The Future of Multilingual Communication

– Language will embrace forms of hybrid intelligence, where AI-driven workflows will handle a significant portion of translation, leaving human experts to focus on finalizing translations.
– The balance between AI and human input will shift over time, with AI taking on an increasing workload while human input remains crucial.

Exfluency’s Plans for the Coming Year

– Exfluency aims to expand its technology into new verticals and build communities of subject matter experts to serve them.
– The company is also focused on its Knowledge Mining app, designed to leverage the hidden linguistic assets and information available.
– Exciting developments are expected in 2024.

By Jaromir Dzialo, CTO and Co-founder of Exfluency, a provider of affordable AI-powered language and security solutions, and originally published on the AI & Big Data Expo’s blog.