We integrated AI21's advanced language capabilities with Zapier and Make, two leading no-code/low-code tools designed to automate workflows across various applications. These integrations empower more 'citizen developers' to leverage AI21's state-of-the-art language models, regardless of their programming experience or expertise. By integrating AI21's J2 Completions and the Task-Specific APIs with Zapier and Make, we bring AI21's specialized language models into the hands of more users, providing solutions to numerous language-related tasks quickly and efficiently. So, why does this matter for AI21's potential customers? Zapier and Make, being low-code/no-code tools, have democratized the process of creating custom workflows and automation. This means that even individuals with minimal coding skills – often referred to as 'citizen developers' – can design and build complex automation workflows. By integrating AI21's advanced language models with these tools, we're offering these 'citizen developers' a significant competitive advantage. Imagine a customer support department of a small business looking to respond faster to customers, but facing a staffing crunch. They are using autoresponders and workflows with Zapier and similar tools today. But customers hate the canned "we'll get back to you soon." With the Contextual Answers API, the automation has a chance to send a useful reply. And if it does not, the problem can get elevated to a human being. That kind of useful decision-making integrates the best of simple boolean logic, wiring a workflow, and using the extraordinary generative text from AI21. Connecting AI21 APIs with the existing no-code automation and operations tools like Zapier and Make can 10x the available market for these technologies. We were surprised how quickly we were making interesting automations once we had the integration running.

Medium sized companies that are GCP customers have a problem. They hear about the great power of OpenAI and want to take advantage to leverage the technology for their businesses. But at the same time, they have significant proprietary data that they can't hand to just anyone, and they are concerned about the use of this information in the hands of startups they've never heard from. Howe can we solve this problem? The new releases in Vertex mean an opportunity to re-connect the dots of modern generative AI technology with the information they have today without ever leaving Google. Our implementation connects audio import of meeting recordings using Google Cloud Run and Google Speech-To-Text using the latest-generation Chirp model. We then load that data into Google CLoud Storage and apply it to a Vertex matching engine via the Gecko embeddings model. The data is queryable using a langchain-enabled Chainlit instance again running on Cloud Run which leverages both the latest Palm 2 chat interface and vector search from Matching Engine. Now instead of using Pinecone, Ada and GPT4, one can use an all-google approach for compliance and safety.

No-Code is a huge market because businesspeople want to apply advanced technologies to reduce costs, increase consistency, and deliver a new level of service to their customers, investors and other stakeholders. SuperAGI gives us greater leverage on LLM technology to take on greater actions. The mission of SuperAGI No-Code is to allow businesses to dictate how the autonomous agents should behave based on their business processes. By offering control and dynamism without requiring them to learn a whole new control plane, the Zapier integration lets business people create much greater value in a much shorter payback period. This integration can dramatically increase the addressable market for SuperAGI, and the profits that can be generated by business. This is an exciting opportunity that lets us move from research to economically meaningful applications guided by the people who understand them most - the business domain experts!

Chessboxing is the ultimate blend of brains and brawn, where competitors juggle checkmates and uppercuts in an alternating series of blitz chess and boxing rounds. This unique sport requires participants to strategize on the chessboard before immediately defending themselves in the ring. Chessboxing demands quick wits and a solid right hook, creating an unpredictable competition where a sudden shift in gears can make or break a player. Enter video AI, the game-changer that can take chessboxing to the next level. By analyzing matches frame by frame, AI provides critical insights into both mental strategies and physical techniques. Athletes can improve by targeting specific weaknesses, like rook gambits and jabs, to outsmart their opponents. Beyond player improvement, AI ensures fair play by catching fouls or rule breaches that may go unnoticed in the heat of the moment. It gives referees the tools to make objective calls, providing instant replays and analysis that uphold the integrity of the sport. For fans, video AI brings new excitement by breaking down each match, allowing viewers to appreciate the combination of strategic brilliance and boxing intensity. Real-time stats and analysis deepen understanding, making chessboxing even more thrilling and potentially drawing a wider audience.