In the world of AI, there's an ever-evolving carousel of buzzwords and technical terms; whose meanings themselves are still expanding as AI grows and changes. Some are combinations of terms that industry professionals may already be familiar with, but given renewed meaning. We've collated a glossary of terms you can use to decode key concepts and words currently being used in the AI development sphere.
Hallucinations: Occasionally generative AI may come up with fictionalised results, also known as hallucinations. Although rare, hallucinations are a reminder that AI isn’t infallible, and reinforces that checking over content yourself is integral for accuracy.
Conversational AI: AI that creates content with empathy and creativity. While there are still tasks that are better suited to the human skillset, AI has been innovated to operate in such a way that it can mimic having a brainstorm with a colleague. A conversation, if you will!
Large Language Models (LLM's): In the beta phase of AI application development, almost all generative automation programs subscribe strictly to rules of grammar, syntax and general language conventions. In doing this, though, LLM's miss out on writing devices that lend content readability, such as tone, context and inference.
Algorithm: You're probably well-acquainted with how algorithms work in the context of social media, but how about in AI? Algorithms in AI will be designed not just for targeting timing and relevance of content or decisioning (see below) but additionally for quality control. An algorithmic ranking system for decisioning prompts will help to monitor the tasks that require human interaction and those that are best left to the skillset of AI.
Robotic Process Automation: AI tools that compartmentalize mass volumes of data automatically. These tools aim to lessen or eliminate the reliance on manual tasks like creating spreadsheets.
Decisioning: AI platforms like Salesforce’s EinsteinGPT, set to release soon, will provide action prompts for customer interactions and content-creation using data. EinsteinGPT, for example, will be able to utilise conversation histories and meeting notes among other sources of data to give instant suggestions.
Chain-of-thought prompts: An example of how decisioning would be offered to you. It's a sort of cause-and-effect-style AI prompt template; for example, it could automatically suggest customized responses to a customer's query based on stored banks of information. So, the query could be "How do I implement your software with my other applications and the AI would be able to generate an instant response and send it out for you?".
Personally-Identifying-Information (PII): Basic though it seems, PII can often be overlooked. AI still in its beta phase is developing the hardy security measures required to run safely and protect the privacy of its users.
Integrations: In the context of automation, integrations are a network of systems that combine AI with your various business processes. An example of this is Salesforce’s EinsteinGPT, which aims to be implemented across all Salesforce products. This unites Customer360 tools with automation technology, accelerating and simplifying features of each application - like efficiently sorting data entries.
API: stands for ‘application programming interface’ and applies to any platform used to integrate business modules.
Automated Workflows: Similar to Robotic Process Automation, automated workflows refer to the manual tasks that AI can alleviate or reshape entirely. This could include providing AI-generated templates for content creation.
What is the future of AI, and how can you stay on top of it? That’s a massive question and one that might be hard to tackle on your own. With companies finding ways to work smarter and not harder with the help of AI, it’s integral not to take a one-size-fits-all approach. How do you know what functions are suitable for your business and those that are best left to human interaction? Stay tuned for further content regarding AI, or browse our blog library for previous editions on automation, such as the benefits and challenges of using it in customer service.
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