Since ChatGPT was launched in November 2022 by OpenAI, it’s become the fastest-growing application in history, acquiring over 100 million users by January 2023. Today, conversational AI is changing the way we work, study, consume information, and brainstorm ideas. And it’s getting better ...
I am the developer ofBeeHelp.netand it took me 3 weeks to (more or less) control the responses of the chat to certain questions. As you probably already know, the biggest problem when you want ChatGPT to respond to your visitor based on ...
Sure, ChatGPT might be able to bash out some SEO-optimised content but does it help fulfilyourpurpose or is the content meaningful and memorable to you? Probably not. We have the choice to use (and consume) AI, how and when we like it. So how does this relate to employee engagement?
No one could have imagined that AI foundation models would bring such fundamental changes to society at the end of 2022 with the release of ChatGPT by OpenAI. Before 2022, AI was used as a niche tool in specialized fields, such as computer vision and Internet recommendations, to help perceiv...
While this ‘no-human prompt’ feature might sound scary initially, it is actually quite useful to automate a workflow or handle complex tasks that would otherwise consume a lot of time. For example, you can use AutoGPT to set up a 24/7 customer helpline that can interact and provide rea...
Step-by-step instructions on how to build and test a ChatGPT plugin that returns current weather information using Microsoft ASP.NET Web API.
Training can be costly for large datasets. For example, I had to spend roughly $8 to fine-tune the Davinci model on 650 tweets. No access to ChatGPT as of this writing. OpenAI Pricing Plans Developers can try out the OpenAI API with the free tier, which includes a limited number of ...
{"location": {"type":"string","description":"The city name, e.g. San Francisco", }, },"required": ["location"], }, } } ]# First API call: Ask the model to use the functionresponse = client.chat.completions.create( model=deployment_name, messages=messages, tools=tools, tool_...
Administrative tasks, such as data entry, scheduling, and report generation generally consume a lot of time and human resources. However, with the advent of AI, these tasks can be automated and streamlined, boosting productivity. Using machine learning algorithms, AI can learn from data patterns ...
This, however, doesn't always work well. Take for example if you wanted to add all of the numbers between 1 and 100. With function calling, you'd need to make a call to the LLM for every number. That's an expensive request!