A quick guide on Generative AI

What is generative AI?

What are foundation models?

What types of foundation models are currently in the market?

• Text-to-text: These natural language processing models can summarize text, extract information, respond to questions, and create content such as blogs or product descriptions. An example is sentence auto-completion.

• Text-to-embeddings: These FMs compare user search bar input with index data and connect the dots between the two. The result is more accurate and relevant results.

• Multimodal: These emerging foundation models can generate images based on a user's natural language text input.

• Text: Summarizing or automating content creation
• Generative AI can summarize lengthy documents, articles, or reports into concise versions, making it easier to digest information quickly.
• Generative AI can also automate content creation by generating articles, blog posts, and social media content based on specific inputs or themes, thus saving time and effort for writers and marketers.

• Images: Generating images, creating avatars etc.
• Generative AI can generate realistic images from textual descriptions, helping in creating custom illustrations, avatars, and even art. This capability is useful in graphic design, advertising, and entertainment.
• Generative AI can also enhance existing images by adding details, changing styles, or filling in missing parts, thereby improving visual content quality.

• Audio: Summarizing, generating, or converting text in audio
• Generative AI can convert text to speech, enabling the creation of audiobooks, voice-overs, and virtual assistants.
• It can also generate music, create sound effects, and enhance audio recordings by removing noise or adding elements. Additionally, AI can summarize spoken content into text, making it accessible for further analysis and usage.

• Video: Generating or editing videos
• AI can generate videos from scratch based on scripts or storyboards, which is useful for animation, marketing, and educational content.
• It can also edit existing videos by enhancing quality, adding special effects, or changing backgrounds. Moreover, AI can automate video summarization, making it easier to highlight key moments in lengthy recordings.

• Code: Generating code, optimizing code
• Generative AI can assist in writing and optimizing code, helping developers by suggesting code snippets, fixing bugs, and ensuring best practices. It can also automate repetitive coding tasks, speeding up development processes.
• Additionally, AI can generate documentation and test cases, improving overall software quality and maintainability.

• Chatbots: Automating customer service and more
• Improving customer engagement with seamless omnichannel access to virtual agents across different collaboration tools and channels
• Empowering customers to quickly find answers and complete transactions on their own by implementing conversational voice and text-based chatbots
• Discovering business insights out of real-time or recorded conversations to detect emerging trends

• ML platforms: Applications and ML platforms
• AI can enhance machine learning platforms by automating model training, hyperparameter tuning, and data preprocessing. It can also generate synthetic data for training models, improving their accuracy and robustness.
• Furthermore, AI can assist in deploying and monitoring machine learning models, ensuring they perform optimally in production environments.

• Search: AI-powered insights or vector search
• Generative AI can enhance search engines by providing AI-powered insights and answering queries with context-aware responses.
• It can also enable vector search, which uses deep learning to find similar items based on their content rather than keywords. This capability improves search accuracy and relevance, especially for complex or ambiguous queries.

• Gaming: Generative AI gaming studios or applications
• AI can create entire game worlds, characters, and storylines, enhancing the creativity and scope of games. It can also generate realistic behaviors for non-playable characters (NPCs), making games more immersive and engaging.
• Additionally, AI can automate testing and optimization processes, ensuring games run smoothly and efficiently.

• Data: Synthesizing, designing, collecting, or summarizing data
• Generative AI can synthesize realistic data for training machine learning models, ensuring they generalize well to real-world scenarios. It can also design and collect data in a structured and efficient manner, improving data quality and availability.
• Furthermore, AI can summarize large datasets, highlighting key insights and trends for better decision-making.

Use cases by industry

Healthcare

• Medical research: Patient-to-trial matching, multi-modal data analysis

• Clinical efficiency: Longitudinal patient records for full patient picture, automate medical image interpretation

• Operational efficiency: Auto-generate referral letters, clinical coding, and prior authorization

• Patient experience: Patient outcome prediction, personalized patient discharge instructions and treatment plans

• Digital health: Patient care concierge, remote care management

Life sciences

• Research and discovery: Protein folding, protein design

• Clinical development: Optimizing trial protocols, patient cohorts, and sites

• Manufacturing: Predictive maintenance, resource optimization

• Commercial and medical affairs: Patient outcome prediction, content generation

• Patient support: Patient care concierge, patient-to-trial matching

Financial services

• AI-managed portfolios: Create highly tailored investment strategies and portfolios aligned to specific financial goals and risk profiles

• Increase the business value of unstructured content: Create on-demand structured data products from large unstructured data sources such as emails, document repositories, and filings

• Drive product innovation and automate business processes: Develop new tools, such as stock screening using natural language search, for end-users

• Intelligent advisory: Automatically translate complex questions from internal users and external customers into their semantic meaning, analyze for context, and then generate highly accurate and conversational responses

• Transform financial documentation: Quickly draft investment research, loan documentation, insurance policies, regulatory communications, requests for information (RFI), and business correspondence

Manufacturing

• Operational efficiency: Text generation for contracts and SOPs, customer service and agent assistants, research and summarization for supply-chain optimization

• Reduce time and cost of production: Agents and search for plant maintenance, operations, and research

• Product design optimization: Generate and enhance new product design, market and customer research to support market development

• Real-time equipment diagnostics: Ingest historical data and diagnose equipment failures in real time to recommend maintenance actions

• Training content generation: Generative conversational agents can be trained on product manuals, troubleshooting guides, and maintenance notes to deliver swift technical support to workers, reducing downtimes

Retail

• Better customer experience: Provide shoppers with a more natural, personalized experience at scale, use natural language to narrow products down to what the customer is specifically looking for

• Data insights: Consume large amounts of data like sales, returns, or product reviews to summarize trends

• Optimized operations: Make better merchandising decisions, automate the generation of product categories and decisions, track vessels through scraping public vessel or freight locations and associate it with ordered freight to gain real-time visibility of goods

• Enhanced marketing: Generate SEO-optimized copy for landing pages, blogs, and social media posts, generate product images or models without having to use photography

Media and entertainment

• Text: Narrative generation from sports statistics and news, script summarization, reading and writing assistance

• Images and videos: Render-from-rough storyboarding from sketches, rendering scenes from untextured 3D models

• Audio: Music generation, automated dialogue replacement, script reading, localization