Generative AI – In the Fintech world, Generative AI is set to revolutionize processes, from personalized financial advice and risk assessment to the development of innovative investment strategies.
The year 2024 will mark the integration of Generative AI into the core fabric of Fintech platforms, enhancing user experiences, automating complex tasks, and unlocking new dimensions of efficiency. As we know generative AI has surged into the forefront of global technology and business discussions in late 2022 and 2023, setting the stage for significant anticipated impacts on the entire business landscape. As we look ahead to 2024, the answer to whether it will live up to the extensive hype is a resounding yes.
While the current dominance of ‘Large Language Models’ is expected to persist, there is a discernible shift towards the demand for smaller, more cost-efficient models. These models are envisioned to become increasingly compact, enabling them to operate on low-footprint installations, including edge devices and smaller enterprise architectures.
Happy New Year – 2024
As we step into 2024, it heralds the dawn of a transformative era for Fintech with the ascendancy of Generative AI. This year is poised to witness the full bloom of Generative AI’s potential, transcending the boundaries of conventional applications. The financial technology landscape will experience a paradigm shift, driven by the creative capabilities and unprecedented insights offered by Generative AI models.
The Technology Journey
After spending 23 years in the tech world, with 15 of those dedicated to FinTech, let me pour my heart out about 2024. Imagine this amazing journey of tech growth—Industry 5.0 unfolding like a magical story. Think about the game-changers:
Google Translate in 2006, Siri in 2011, and the enchanting ChatGPT joining in December 2021. It’s like we’ve moved from simple tools to these mind-blowing AI models, painting a vivid picture of the dynamic Industry 5.0.
- Concerns in the AI Rise: Now, here’s where the story takes an emotional turn. The rise of powerful AI models, like mighty heroes, stirs up worries and tough choices. The link between immense power and ethical questions adds a deep, touching layer to the tale.
- ChatGPT’s Core Magic: At its heart, ChatGPT uses captivating technology called Generative Pre-trained Transformer (GPT) from OpenAI. This enchanting tech lets ChatGPT understand what we say, respond like a champ, and talk just like us humans.
- Emotional Boost in FinTech 4.0 Fusion: Now, picture the fusion of Industry 5.0 and FinTech 4.0, creating waves in financial tech. These advancements act like superheroes for FinTech, turning customer interactions into heartfelt chats and financial services into personalized notes. But, in this magical world, we need to be the superheroes, making sure we use these technologies in a good way for the complicated world of financial innovation.
Think about it—the jump from Google Translate to ChatGPT is like witnessing magic unfold in language tech. It’s a story shaped by tech wizards using natural language tricks and machine learning. Heroes like Siri and Alexa paved the way for the amazing ChatGPT. Balancing tech progress with our core values will create a future where Industry 5.0 and FinTech 4.0 fit perfectly with our heartfelt values.
What 1GB holds Assuming an average of 5 characters per word plus a space (6 characters), 1GB corresponds to approximately 178,956,970 words, equivalent to around 894,784 pages at 200 words per page.
Generative AI - Introduction
GPT (Generative Pre-trained Transformer) – is a specific instance of a Large Language Model (LLM) developed by OpenAI, known for its transformer architecture and pre-training approach.
- Characteristics – GPT models are a subset of LLMs and are distinguished by their transformer architecture. The “Generative Pre-trained Transformer” reflects the pre-training methodology where the model learns from vast amounts of diverse text data before fine-tuning for specific tasks.
- Each version of GPT (such as GPT-3) represents a distinct iteration with advancements in scale and capabilities.
LLM (Large Language Model) – LLM broadly refers to language models characterized by their extensive size, typically containing billions or trillions of parameters.
- Characteristics – Encompasses a range of language models, including but not limited to GPT, that are designed to handle complex natural language understanding tasks.
- Large size contributes to improved performance on various language-related applications.
This clarifies that GPT falls within the category of Large Language Models, and they share characteristics related to extensive size and advanced language processing capabilities.
Google Translate took 78 months to reach 100 million users, TikTok took 9 months, and ChatGPT took about 2 months.
Era of Generative AI in Fintech
In year 2024, a significant and noteworthy development is poised to unfold. We are anticipating the integration of generative AI models with high-quality information sourced from Knowledge Graphs, forming a strategic alliance that resembles a technological superhero. This powerful combination is positioned to effectively combat potential errors, ensuring a notable enhancement in the overall reliability and accuracy of the generated outputs.
- AI Platform Evolution: Anticipate the emergence of new AI platforms tailored for companies, featuring user-friendly tools for harnessing generative AI capabilities without extensive technical expertise.
- Democratization of Generative AI: Witness a transformative shift as access to generative AI becomes more widespread. Companies can effortlessly create interconnected networks of models, each finely tuned for specific tasks, without the need for advanced technical skills.
- Multi-Agent Generative Ecosystems: Expect the development of true multi-agent generative ecosystems, a paradigm shift in the broader AI landscape. This evolution is set to redefine how artificial intelligence operates, particularly impacting Fintech.
- Fintech’s Intelligent Transformation: With generative AI leading the charge, Fintech firms will leverage intelligent algorithms for predictive analytics, enabling more informed decision-making processes in this dynamic and innovative landscape.
As I look ahead to the coming year, promising a harmonious convergence of technology and finance, I anticipate that 2024 will be recognized as the Year of Generative AI in Fintech. This heralds the ushering in of a new era characterized by intelligent, adaptive, and innovative financial services.
FinTech’s Generative AI
In the dynamic landscape of FinTech, Generative AI adds intricate threads to the evolving tapestry of artificial intelligence. While Narrow AI excels in precision, General AI envisions adaptability, and Super AI lies on the speculative horizon.
- Explainable AI for Trustworthy Decisions: In FinTech, prioritizing transparency with Explainable AI is crucial for building trust in decision-making processes, ensuring reliability.
- Dynamic Systems with Experiential AI: Embracing continuous learning, Experiential AI in FinTech facilitates the development of dynamic systems, adapting and evolving as the financial industry increasingly integrates artificial intelligence.
Balancing technological progress with ethical considerations is not just a choice but a responsibility, shaping a future where Generative AI enhances, rather than compromises, our collective financial well-being.
Why it matters: The progress in generative AI is pointing towards a future where tech is easier to use, more flexible, and doesn’t break the bank. This means companies can do more cool stuff with generative AI quickly and get even more value from it in the long run. It’s like technology is becoming your super helpful sidekick, making things simpler and more amazing!
Conclusion – The advent of large language models, exemplified by GPT, is revolutionizing natural language processing and text creation, especially in the realm of FinTech. These models, equipped with the ability to absorb extensive data and generate text resembling human language, offer tremendous potential within the financial technology landscape. Whether it’s elevating customer service standards, streamlining content creation in financial communications, or enhancing software development for FinTech solutions, large language models prove to be influential tools driving innovation and efficiency in the financial sector.
If you have queries or wish to delve deeper into large language models in FinTech, feel free to connect with me. Don’t forget to like and subscribe for future updates and insightful FinTech content. Thank you for your interest!
Feedback & Further Questions
Besides life lessons, I do write-ups on technology, which is my profession. Do you have any burning questions about big data, AI and ML, blockchain, and FinTech, or any questions about the basics of theoretical physics, which is my passion, or about photography or Fujifilm (SLRs or lenses)? which is my avocation. Please feel free to ask your question either by leaving a comment or by sending me an email. I will do my best to quench your curiosity.
Points to Note:
It’s time to figure out when to use which “deep learning algorithm”—a tricky decision that can really only be tackled with a combination of experience and the type of problem in hand. So if you think you’ve got the right answer, take a bow and collect your credits! And don’t worry if you don’t get it right in the first attempt.
Books Referred & Other material referred
- Open Internet research, news portals and white papers reading
- Lab and hands-on experience of @AILabPage (Self-taught learners group) members.
- Self-Learning through Live Webinars, Conferences, Lectures, and Seminars, and AI Talkshows
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The payment landscape is evolving rapidly and industry insights suggest that AI will accelerate that transformation into 2024. AI-powered payment solutions will offer faster, more secure, and seamless transactions, while machine learning algorithms analyze user behavior to personalize the payment experience
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Artificial intelligence is growing rapidly, comparable to the significant advancements seen during the initial introduction of smartphones. Innovations like ChatGPT, DALL-E, and Midjourney are changing the way creative individuals and businesses think about their marketing plans. In the near future, everyday users will also be able to enjoy these advantages. Apple’s initiative to bring generative AI to all its smartphones is a major stride in making AI accessible to a large audience. With integration into Siri, consumers are anticipated to have AI capabilities on their mobile devices by 2024, as predicted by industry experts.
Generative AI is poised to transform financial services in 2024, and financial services firms must start the process of building a generative AI assistants today. Generative AI assistants are coming to financial services. I’m thrilled to have found this site and can’t get enough of what they deliver.
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However, despite the considerable excitement surrounding generative AI, there remains uncertainty regarding when consumers can expect to access a ChatGPT-like service within their financial services website and mobile app.
Generative AI in Fintech, suggests a pivotal moment in the intersection of two cutting-edge fields: artificial intelligence and financial technology. Innovation in Fintech is clearly a progress of generative AI into fintech and it represents a significant leap forward in innovation within the financial services sector. By leveraging advanced algorithms to generate data, insights, and predictive models, fintech companies can enhance decision-making processes, automate tasks, and deliver more personalized services to customers. AILabPage you are doing excellent work