dk189
Joined 6 years ago
Joined 6 years ago
On Shannon airgapped in your VPC, if it works for you, you might not need us. A normal model will refuse or hedge on offensive tasks, we post-trained ours to just run the authorised stuff. For this one narrow job, a specialist that'll actually attack beats a generalist that won't.
At Algomo, we believe that the potential extends even further. We see language models as the foundational 'intelligence' driving autonomous AI agents in customer service.
Autonomous AI agents?
Standard conversational language models work by taking text input and producing text output. You ask a question, and the language model responds with ‘static’ information from a knowledge base. You can think of them as a ‘conversational search engine.’
LLM-based agents, however, are a step ahead. They not only take text as input but can also interact with 'modules' such as memory, call other specialized LLMs, utilize functions (tools & APIs), and even integrate human judgement. Essentially, they can strategize and execute solutions to any presented problem. Application in Customer Service
Autonomous AI agents can literally redefine the interaction landscape between businesses and their customers. For instance, an agent can integrate into a company's CRM system, using its memory module to recall past interactions and personalize responses. It can employ specialized LLMs to handle technical queries or access APIs for real-time order tracking, or product information, ensuring customers receive accurate and timely information. Even more impressively, these agents can autonomously escalate complex issues or ask feedback from human agents, combining AI efficiency with human empathy.