10 GenAI trends and predictions

You will be able to designate specific folders where you will be able to query a chatbot. Fine-tuning an LLM like ChatGPT on your data.

• Dropbox has announced Dropbox AI
• Google has announced Tailwind
• Box has announced Box AI

Why?

• Be able to complete research and write as a student
• Create a proposal or plan based on other document inputs

More sophisticated chatbots will be integrated into the customer-facing and built internally into companies' various databases: HR information, Customer Experience (NPS), Knowledge bases, Product information, Business Intelligence, and Brand integration.

Many people suffer from stress and unhappiness. A company can save costs by integrating some mental health bots to help them deal with stress and conflict that is endemic to most companies.

Copilots are helper applications that sit beside or are integrated into an application to extend its capabilities.

Without a doubt, any tool that revolves around writing, imagination, and video must incorporate AI integration to remain relevant and competitive. It is imperative to include the word, "AI "as an additional source of income to maximize your monthly recurring revenue (MRR).

• Grammarly GO
• Notion AI
• Canva AI (text to image)
• Vimeo (AI script generation)
• Miro (Miro AI generates mind map diagrams from text prompts)
• Office 365 CoPilot
• Google Duet
• Blog Writing: WordPress
• NotePD 😏

Images

Google Ads and Facebooks Ads incorporate built-in AI text and image generation.

Code

GitHUB Copilot

Beyond the Generative AI, you have various layers of business:

Infrastructure, Foundational Models, Applications, Verticals/Industries

Each of the businesses within these layers could benefit. For example, LLM needs a lot of data to build ML models, as do industries that need to develop their models. Data may be sparse or inaccessible, which could drive the Synthetic Data market.

Other examples of companies I have seen are prompt optimizers (Prompt Perfect), platforms to optimize LLM and model performance (Weights and Biases). Host for models and demos (Hugging Face, Human Loop, Google Vertex)

Right now we have GenAI models that separated. GPT-4 is already a multimodal system that can recognize pictures and carry out reasoning task (such as why this picture funny). Image if we have model that carry out all task ideating, building images, reasoning and generate text, audio and video)

Expect more autonomous frameworks and tools with AI at their product's core. Consider GPT Engineer a fully autonomous code-writing application. You give it a set of goals, and it runs off to create an application for your

GPT engineer extends autonomous agents to build a practical deliverable.

I suspect seeing a user interface for no-code platforms pick up. The interface is relatively primitive with text and voice-only input. People work better with graphical interfaces.

If you consider the components out there Chatbot, Chatbot Agents, Chatbot Autonomous agents there must be a way of bringing these components together with a better interface such as LangChain UI (which is an orchestration framework)

It seems that we are witnessing the initial stages of an emerging trend. The EU and US Congress are engaging in discussions about implementing improved regulations and transparency. It is highly likely that the development of effective regulations will lead to the creation of specialized tools to facilitate and monitor their implementation.

I propose a new data quality dimension designating a record generated with AI. This will provide transparency on the origin of the content, whether human-created or machine creates. The metric will be the percentage value of records made with AI vs. ones generated by humans.

• Build an entire explainer video using text prompts
• Full-length real estate staging videos, ads, TV shows and movies entirely produced in AI (text to video), Live action to Animation (Check out Wonder Dynamics)