Search Results for "what"

...This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI.

...We've renamed from "llmclient" to "ax" to highlight our focus on powering agentic workflows. We agree with many experts like "Andrew Ng" that agentic workflows are the key to unlocking the true power of large language models and what can be achieved with in-context learning. Also, we are big fans of the Stanford DSPy paper, and this library is the result of all of this coming together to build a powerful framework for you to build with.

This repo is an implementation of a context-aware AI Agent for Sales using LLMs and can work across voice, email and texting (SMS, WhatsApp, WeChat, Weibo, Telegram, etc.). SalesGPT is context-aware, which means it can understand what stage of a sales conversation it is in and act accordingly. Moreover, SalesGPT has access to tools, such as your own pre-defined product knowledge base, significantly reducing hallucinations.

BDI4JADE is an agent platform based on the BDI architecture implemented in pure Java. Therefore, Java features can be exploited; and it facilitates the integration of existing technologies, what is essential in the context of enterprise applications.

...It can accept a text or URL (text takes a prescedence over the URL). If you input URL, it goes to a page, and learns its text from HTML format. This program is intelligent as it predicts what you may want to search next, based on your personal trends. After searching the suggestions, you can choose to reset or train it further. Programs that have similar idea are: Google AdWords, SERPWoo's Keyword Finder, Wordpot, and others. Difference is, this program is intelligent and it accepts your input data and then predicts keywords based on your likes or dislikes. ...

Please click on "BROWSE ALL FILES" to open a README! What is this program? This program is meant to search the texts and suggest sentences that might follow any inputted sentence. It was meant to help composing the writings. How was it made? First, I made a chatterbot to understand the concept of "predicting" the next sentence (worked as good as the Cleverbot), then I made this program that is aided by an user to compose the new writings.

This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else? Status: PreAlpha, so any help shall be welcome. Made for LINUX. GNU General Public License version 3.0 (GPLv3)

In imitative learning, an agent will attempt to match what is observed to their memory. By visualizing the incorrectly matches "scenes", this project will allow algorithm developers to gain a better understanding of what causes their algorithms to fail.