FoF Specials – Generative AI Gazette | Edition #4 – Aug 2023
FoF Specials – Generative AI Gazette | Edition #4 – Aug 2023
Summary of generative AI news from the month of August 2023
Greetings, fellow fintech and AI enthusiasts! 🤖
The month of August brought forth a wave of exciting developments in the realm of generative AI, signalling a continued trend of integration and growth in the AI sector. The AI wave has reached various industries, including fintech, content creation, healthcare, and creative design, with a strong emphasis on improving user experiences, efficiency, and problem-solving.
Among the highlights is AudioCraft by Meta, a remarkable AI tool that effortlessly transforms text into lifelike audio and music, setting new standards for audio quality. Additionally, OpenAI has taken a significant step by launching an enterprise-specific AI bot.
We will delve into these and other noteworthy developments that are shaping the future of fintech and AI. Explore the latest trends and innovations that promise to redefine the industry.
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Get your AI fix with Edition #4 of the Generative AI Gazette! 📰
We've scoured the AI universe and handpicked the #Top10 highlights from the month of August:
Marqeta tapped OpenAI's Large Language Models for its Marqeta Docs AI tool, allowing customers to quickly navigate the Marqeta Docs site and gain a better understanding of its offerings and the complexities of embedding payment services.
Brex introduced an AI-enabled Accounts Payable solution, providing the controls required by an AP team to manage spend seamlessly across invoices and purchase cards, with the flexibility sought by employees for business spend.
NVIDIA expanded its partnership with VMware Private AI Foundation to enable enterprises to develop and deploy generative AI applications such as chatbots, assistants, search, and summarization.
Snapchat introduced an exciting new generative AI feature – 'Dreams' – which will take AI-generated images to the next level, potentially transforming photos with imaginative backgrounds that could even include both the user and their friends.
Adobe's latest version of its all-in-one content creation app with Firefly beta generative AI capabilities became generally available on desktop web, revolutionizing creative expression for users of all skill levels to design and share standout content.
Meta rolled out AudioCraft – an innovative AI tool that effortlessly transforms text into high-quality, lifelike audio and music. Professional musicians can explore new compositions without picking up an instrument and businesses can easily add captivating soundtracks to their Instagram video ads.
Microsoft and Epic collaborated to accelerate the use of generative AI in healthcare, aiming to address pressing industry needs such as staffing shortages, financial and clinical access challenges, and to improve patient service.
OpenAI launched ChatGPT Enterprise, a version of the company’s generative AI chatbot designed for use inside organizations, which promises enterprise-grade security and privacy and unlimited access to the GPT-4 large language model (LLM) amongst other features.
The AI adventure is far from over – we’ve got some more tech-tastic content waiting to rev up your inner tech enthusiast! 🤖
Midjourney introduced “Vary (Region)” – a new AI art generator that competes with Adobe Photoshop's Generative fill – allowing designers to choose specific regions within a picture and use the text-to-image generator to fill it.
SoFi integrated Galileo’s AI-driven digital assistance Cyberbank Konecta into its digital personal finance app, helping SoFi achieve immediate cost reduction by freeing up valuable agent time to solve more complex and higher-touch problems for SoFi’s members.
Generative AI Word Of The Week: In-context Learning
In-context learning refers to the process of pre-training or fine-tuning language models for specific tasks to improve their performance in handling contextual information. It is also known as few-shot learning or few-shot prompting, which is a technique where the model is presented with prompts and responses as a context prior to performing a task. It requires less task-specific data and reduces the risk of overfitting by avoiding narrow learnings from a limited fine-tuning dataset.
That's all for now!🤘
We hope you enjoyed this edition!
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