Category: GPT

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Navigating the Future of AI

As we progress in a world that is quickly transforming due to the widespread adoption of artificial intelligence (AI), it is essential to gain a comprehensive understanding of the various AI systems and their capabilities by examining the evolution of different AI archetypes.

Keeping a close eye on the progress and sophistication of AI archetypes is essential for businesses looking to stay ahead in an increasingly competitive and technology-driven world. By tracking advancements in AI capabilities, companies can identify new opportunities and adapt their strategies accordingly to maintain a competitive edge.

In today’s post, I’ll be delving into various AI archetypes and providing examples of each, and exploring their potential influence on the future of business.

  1. Reactive AI: The Simplest Archetype

Reactive AI systems, also known as rule-based systems, have been in use since the early days of AI research in the 1950s and 1960s. These systems can only react to specific inputs and do not have the ability to learn from past experiences or store information.

Reactive AI does not have the ability to learn from past experiences or adapt their behavior. A classic example of reactive AI is IBM’s Deep Blue, the chess-playing computer that famously defeated world champion Garry Kasparov in 1997. Deep Blue analyzed millions of chess positions and made decisions based on its programming, but it couldn’t learn from its games or adapt its strategies beyond its initial programming.

Some basic robots, such as vacuum cleaners like the Roomba, can also be considered Reactive AI. These robots use sensors to detect obstacles and perform specific actions based on the input from their environment. They do not possess memory or the ability to learn from past experiences and cannot adapt their behavior.

Another type of reactive AI used in healthcare are expert systems. Expert systems are AI applications that mimic the decision-making abilities of a human expert in a specific domain. These systems use a knowledge base of facts and rules to make inferences and provide solutions to specific problems. For example, an expert system for medical diagnosis could use a predefined set of rules to suggest possible diagnoses based on the input symptoms but lack learning capabilities.

  1. Limited Memory AI: Learning from Experience

Limited memory AI, which can learn from past data and experiences, started gaining prominence in the 1980s and 1990s with the development of machine learning techniques, such as neural networks and reinforcement learning. These systems have a limited ability to learn from past experiences, allowing them to improve their performance over time.

Self-driving cars are a prime example of limited memory AI. They use data gathered from previous trips to improve their navigation, obstacle detection, and decision-making capabilities.

Voice-based systems like Alexa, Siri, and Google Assistant primarily fit within the Limited Memory AI archetype. Virtual assistants like Alexa, Siri, and Google Assistant rely on AI algorithms to generate responses based on their training data and some past experiences. They can learn from user interactions, improving their performance and tailoring their responses over time.

These systems use natural language processing (NLP) to understand and process voice commands, and machine learning algorithms to provide relevant information, perform tasks, or control connected devices. While these voice-based systems have advanced capabilities, they do not yet possess the level of understanding and modeling of human emotions, intentions, beliefs, and desires.

Generative AI can be considered limited memory AI archetype. Generative AI models, such as GPT-4 and DALL-E, are trained on large amounts of data and use this knowledge to generate content. These models are based on past experiences (the data they have been trained on) and can generate text, images, or even music that closely resemble human-generated content. While they do learn from their training data, their learning capabilities are limited to the scope of the data they have been exposed to and the specific tasks they have been trained for.

Digital humans, which are AI-powered virtual characters designed to resemble and interact like real humans, can fit primarily within the Limited Memory AI and possibly evolve towards Theory of Mind AI archetypes, depending on the sophistication of the underlying AI system.

Another area I have discussed previously is emotive robotics. When it comes to AI archetypes, emotive robots that rely on AI algorithms to generate responses based on their training data and some past experiences fit within the Limited Memory AI archetype. These robots can learn to some extent from their interactions and adapt their behavior accordingly. Examples include social robots, customer service robots, or companion robots that use AI to simulate human-like emotions and interactions.

  1. Theory of Mind AI: Understanding Human Emotions and Intentions

The Theory of Mind AI archetype represents systems capable of modeling human emotions, intentions, beliefs, and desires. These AI systems would be able to interact with humans more effectively, empathize, and even predict human behavior. Although we have yet to achieve this level of AI-human interaction, as generative AI systems become more sophisticated, they may begin to exhibit a deeper understanding of human emotions, intentions, and beliefs.

By generating content that is more contextually aware and emotionally intelligent, these AI systems could potentially move closer to the Theory of Mind AI archetype. Although generative AI is not yet at this level of human understanding, ongoing research and development in AI could enable future advancements in this direction. As these systems evolve, they will revolutionize industries such as customer service, mental health, and entertainment.

As digital humans evolve and their AI systems become more sophisticated, they may increasingly fit within the Theory of Mind AI archetype. Advanced digital humans would be able to understand and model human emotions, intentions, beliefs, and desires, resulting in more natural and effective interactions with people. This could lead to digital humans being used in a wide range of applications, such as virtual therapy, and entertainment.

As emotive robots evolve and their AI systems become more sophisticated, they may increasingly fit within the Theory of Mind AI archetype. Advanced emotive robots would be capable of understanding and modeling human emotions, intentions, beliefs, and desires, resulting in more natural and effective interactions. These robots could be used in a variety of applications, such as therapy, caregiving, and education, where understanding and expressing emotions are essential for effective communication.

  1. Self-Aware AI: The Philosophical Frontier

Self-aware AI is a thought-provoking theoretical concept, envisioning AI systems endowed with consciousness, self-awareness, and an understanding of their own existence. These AI systems would have the capacity to make autonomous decisions, set their own goals, and even potentially exhibit creativity. While self-aware AI remains in the realm of science fiction, it offers a fascinating area of exploration that could ultimately redefine our understanding of intelligence and consciousness.

As someone captivated by the potential of self-aware AI, I’ve seen its influence on the creative works of numerous science fiction authors, filmmakers, and futurists. These fictional portrayals often depict AI systems with consciousness, self-awareness, and a comprehension of their own existence. A few of my favorite movies showcase prime examples, such as HAL 9000 from 2001: A Space Odyssey, Skynet from the Terminator series, and the Machines from the Matrix trilogy.

  1. Artificial General Intelligence (AGI): The Holy Grail of AI Research

AGI, refers to AI systems that can match or surpass human intelligence across a wide range of tasks. AGI would be capable of adapting to new situations, solving problems, and thinking abstractly, much like humans do. Although AGI remains a theoretical goal in AI research, its potential impact on society is enormous, from revolutionizing scientific discovery to transforming the global economy.

We’ve come a long way from the early days of reactive AI, now finding ourselves at the intersection of Limited Memory and Theory of Mind AI. With the rapid pace of change, we’re on the cusp of bridging the gap between reality and what was once only found in science fiction.

Follow Tom Edwards @BlackFin360 and stay tuned to the BlackFin360 blog for the latest on AI, future-forward predictions, analysis of the latest emerging technologies, and their implications for the future.

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Harnessing the Power of GPT for CPG & Retail

From 2016 onward, I have frequently discussed the accelerated development of artificial intelligence (AI) and its pivotal role in revolutionizing sectors like pharmaceuticals. Today, our focus shifts to leveraging the capabilities of GPT, or Generative Pre-Trained Transformer, in the consumer packaged goods (CPG) and retail domains. In this post, we will delve into the ways GPT can transform customer interactions and redefine the playing field for CPG and retail brands.

My AI avatar has thoughts about which of the 8 points listed below is the most relevant.
  1. Personalized Communication at Scale

The strength of GPT lies in its ability to understand and generate human-like text. This capability allows CPG and retail brands to create highly personalized messaging for their customers. By leveraging AI-powered language models, marketers can craft tailored content for different segments, demographics, and even individual customers, ensuring that every interaction feels unique and genuine. This level of personalization can lead to improved customer loyalty, higher conversion rates, and increased overall brand value.

  1. Enhanced Customer Support

Customer service plays a critical role in the success of CPG and retail businesses. GPT can be utilized to augment customer support teams by providing instant and accurate responses to common inquiries, reducing wait times, and freeing up human agents to focus on more complex issues. Furthermore, with continuous learning and improvement, GPT can adapt and fine-tune its responses to provide an increasingly seamless customer experience over time. Especially if an organization enhances GPT with 1st party data through transfer learning and ring-fencing via an API.

  1. Streamlined Content Creation

Creating high-quality content can be time-consuming and resource-intensive. GPT has the potential to streamline this process by generating product descriptions, promotional materials, and even social media posts, all while maintaining brand voice and consistency. By automating content creation, brands can achieve significant cost savings, improve efficiency, and allocate resources more effectively, especially with the release of GPT-4 and its multi-modal capabilities.

  1. AI-driven Insights and Decision-Making

GPT can analyze vast amounts of data and extract valuable insights that inform marketing strategies and decision-making processes. By understanding customer preferences, sentiment, and trends, CPG and retail brands can make data-driven decisions, optimize their product offerings, and uncover new growth opportunities. With GPT’s natural language understanding capabilities, these insights can be communicated in a way that is easily digestible for decision-makers.

  1. Revolutionizing Analytics for Deeper Customer Understanding

In the age of data-driven marketing, understanding customer behavior and preferences has never been more critical. GPT’s powerful natural language processing capabilities can be harnessed to enhance analytics by interpreting unstructured data, such as customer reviews, social media interactions, and online discussions.

By analyzing this information, GPT can uncover patterns, trends, and insights that were previously hidden, providing a more holistic view of the customer journey. This deeper understanding empowers CPG and retail brands to create highly targeted marketing campaigns via predictive CRM, optimize product assortments, and deliver more relevant, engaging experiences to their customers.

By combining GPT’s advanced analytics with traditional data sources, brands can unlock new levels of customer intelligence and drive strategic decision-making across the organization.

  1. Boosting Voice Assistant Integration for Frictionless Shopping Experiences

As voice assistants become increasingly popular, their integration into CPG and retail experiences has emerged as a crucial factor for success. GPT’s exceptional language generation capabilities can be leveraged to enhance voice interactions, creating more natural, fluid, and engaging conversations with customers.

By developing AI-driven voice applications, CPG and retail brands can provide frictionless shopping experiences, making it easier for customers to discover, research, and purchase products using their preferred voice assistant devices. This level of convenience and ease-of-use not only contributes to customer satisfaction but also drives customer loyalty and repeat business, positioning brands at the forefront of the ever-evolving retail landscape.

  1. Empowering In-Store Experiences with Augmented Reality and GPT

The integration of AI-powered technologies like GPT and Augmented Reality (AR) can elevate in-store experiences for customers, creating a seamless blend of the physical and digital. GPT can be utilized to generate contextually relevant content that enhances AR applications, offering product information, personalized recommendations, and promotional offers to customers as they navigate through the store. This combination of technologies provides an immersive, interactive experience that not only improves customer engagement but also drives sales and increases brand loyalty.

  1. Enhancing Customer Engagement with Digital Humans and GPT

The fusion of digital human avatars with GPT’s advanced language capabilities can create a new paradigm for CPG and retail customer engagement. By combining realistic, emotionally expressive avatars with GPT’s ability to generate natural, human-like conversation, brands can deliver truly immersive and personalized interactions that resonate with customers on a deeper level.

These digital avatars can serve as virtual brand ambassadors, customer service representatives, or even personal shopping assistants, catering to customer needs and preferences with a human touch. The marriage of digital human avatars and GPT’s conversational AI helps bridge the gap between technology and human connection, fostering stronger relationships with customers and elevating the overall brand experience in the CPG and retail space.

By embracing GPT and other AI-driven technologies, CPG and retail brands can unlock a world of opportunities for enhancing existing data, customer engagement, streamlining operations, and staying ahead of the competition. As we continue to witness the convergence of marketing and technology, it is essential for forward-thinking businesses to invest in these innovations and capitalize on the transformative potential they offer.

Follow Tom across social platforms @BlackFin360

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Generative AI & ChatGPT


I have been working on and speaking about the topic of AI since 2016. Over the years, I have researched across generational cohorts, and what is consistent across every age is the primary behavioral driver for why individuals will adopt and engage with intelligent systems, which is ease & convenience.

Generative AI, or artificial intelligence capable of creating new content and ideas, is one of the most rapidly growing technologies today. It has already made waves in the world of literature, art, music, and more. But what impact will it have on our future?

Generative AI has the potential to completely revolutionize how we create content. In its simplest form, it can be used to generate new stories or lyrics based on existing themes. The possibilities are far-reaching when it comes to creating entirely original works that would never been conceived without generative AI.

In this video, I discuss the rise of Generative AI and its implications for pharmaceutical marketing, creativity, prompt engineering, and key considerations tied to visual and text-based large language models DALL-E, GPT, and OpenAI’s chatbot, ChatGPT.

Other topics include insight about ChatGPT Professional, Google vs. Microsoft, and discuss ethics, bias, and other key points to consider when thinking about the application of ChatGPT and other transformer models for business.

It’s clear that generative AI holds a great deal of promise for humanity and its future—but only if used responsibly and ethically. With powerful technologies like these come big responsibilities.

Follow Tom Edwards across social @BlackFin360

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2023 Trend Report

Over the last decade, BlackFin360 has consistently focused on trend forecasting. As we venture into 2023, the rapid convergence of technology takes center stage in both the business world and our everyday lives.

Our growing reliance on technology has been embraced, as it provides ease and convenience in return. We are now poised to advance to the next level of intelligence augmentation through various AI forms, revolutionizing internal processes, customer experiences, and the way we work, learn, and sift through the ever-increasing volume of content we consume daily.

The boundaries between the physical and digital realms are becoming increasingly indistinct as we reshape our understanding of reality, whether it be fully immersive, spatially cognizant, or via lifelike holograms. As the excitement surrounding the metaverse transitions into practical applications beyond mere entertainment, I envision a path towards genuine value creation.

Moreover, the past few years have seen significant behavioral changes. Emerging from a pandemic, our yearning for connection and our demand for personalization, engagement, and control infuse a human touch into a digital world dominated by ones and zeros.

Lastly, the pharmaceutical and healthcare industries are on the verge of profound transformation. The surge in patient-focused advertisements encouraging patients to influence prescribers’ decisions signifies this shift. As a result, the healthcare landscape is evolving to meet expectations of accessible care and the creation of experiences that enable multi-faceted storytelling.

All of this leads to the two foundational elements for the 2023 trend report. Human / Experience. (Message me for the key to view the full Trend Report).

THE HUMAN LAYER

The Human layer dives into all facets of control and empowerment of consumers, patients, caregivers, and HCPs with key examples and organizations enabling ease and convenience.

1 – Consumer Control – As humans, our behaviors are increasingly being shaped by technology, leading us to expect greater control. This section delves profoundly into the world of user-generated content and the emergence of algorithms centered on affinity and personal preferences.

2 – Community Engagement – In the aftermath of the pandemic, we’ve experienced a revitalized appreciation for belonging and community, spanning both digital and physical realms. This section explores the concepts of blended connections, online communities, genuine interactions, and inclusiveness.

3 – Care Anywhere – The notion of point of care is expanding to encompass any location with a camera and an internet connection. This section delves into intelligent devices, ranging from health-monitoring wearable tattoos to smartwatches that track Parkinson’s symptoms. There has been a considerable shift in FDA approvals and investments towards digital therapeutics (DTX). These digital-focused experiences provide patients with medical interventions through clinically evaluated, evidence-based software applications.

4 – Customizable Avatars – Avatars are evolving into representations of ourselves, whether they are photorealistic or stylized. Our capacity to personalize digital embodiments that effortlessly interact across diverse experiences is becoming the standard. This development, coupled with advancements in volumetric video capture, enables connection points that were previously unattainable for integrating oneself into digital surroundings.

5 – Decentralization & Transparency – The convergence of consumers’ quest for control and the inherent decentralization of Web 3.0 is paving the way for new approaches to brand loyalty and adherence programs. With an increased emphasis on data privacy and targeted content, consumers will seek mutually beneficial data exchanges that satisfy both parties’ needs.

THE EXPERIENCE LAYER

Here is a video walking through the Experience Layer portion of the 2023 trends.

The Experience layer blurs the lines between physical and digital reality with key examples and organizations ushering us into a digitally enhanced world.

6 – Extending Reality – Despite the relatively slow growth in consumer interest, augmented, virtual, and mixed reality technologies persist in their development. This section delves into the latest innovations in gaming, enterprise metaverse solutions such as Mytaverse, medical metaverse newcomers, and smart lens applications.

7 – Digital Humans – Synthetic humans are steadily supplanting conventional videos and chatbots. In the pharmaceutical industry, Digital Humans emerged as the top trend in presentations at the end of 2022. They offer the capability to expand a field sales force and establish an emotionally engaging starting point for navigating intricate patient journeys with key opinion leaders (KOLs). The potential to create connection points and avatar-focused content on a large scale is expected to further gather momentum in 2023.

8 – Holograms – The concept of establishing a presence without physical attendance is gaining traction, thanks to companies like Proto and ARHT Media. These firms enable multiple presenters to appear live before audiences as realistic holograms and engage in full interaction, creating a sense of connection even when not physically present.

9 – Scaling with AI – Artificial Intelligence is set to enable hyper-personalization and automation on a massive scale. This section examines the AI technologies that have influenced Hollywood and will shape the way we create experiences in 2023. It delves into the realm of generative AI, providing a comprehensive understanding of the role and workings of a prompt engineer.

10 – Hyper Realism – Hyperrealistic design is increasingly obscuring the boundaries between our digital and physical environments. This section explores its applications in retail experiences and cutting-edge healthcare technology, such as Level Ex, showcasing how these innovations are reshaping various industries.

The complete trend report is 70+ pages of examples of key concepts and the companies that are setting the stage for the next iteration of experiences we will begin to incorporate to transform all aspects of business incrementally.

View the full 2023 Human Experience Trend Report.
(Message me for the key to view the full Trend Report)

A very special thank you Adam Housley for your support in this endeavor.

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