ChatGPT is an artificial intelligence (AI) chatbot developed by OpenAI. It is built on top of OpenAI's GPT-3.5 and GPT-4 families of large language models (LLMs) and has been fine-tuned using both supervised and reinforcement learning techniques.
ChatGPT is an artificial intelligence (AI) chatbot developed by OpenAI. It is built on top of OpenAI's GPT-3.5 and GPT-4 families of large language models (LLMs) and has been fine-tuned using both supervised and reinforcement learning techniques.
In a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.
As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:
Demonstration example for the current Grand Prix contest for use of a more complex Parameter template to test the AI.
There is documentation. A recruitment consultant wants to quickly challenge candidates with some relevant technical questions to a role.
Can they automate making a list of questions and answers from the available documentation?
One of the most effective ways to cement new facts into accessible long term memory is with phased recall.
Hi Community!
Just want to share with you an exercise I made to create "my own" chat with GPT in Telegram.
It became possible because of two components on Open Exchange: Telegram Adapter by @Nikolay Solovyev and IRIS Open-AI by @Kurro Lopez 
So with this example you can setup your own chat with ChatGPT in Telegram.
Let's see how to make it work!
Let's say you have Python including variable-length arguments methods. How can you call it from ObjectScript?
deftest1(*args):return sum(args)
deftest2(**kwargs):
a1 = kwargs.get("a1",None)
a2 = kwargs.get("a2",None)
return a1+a2You can call this "a.py" from ObjectScript as below. For **kwargs argument, create Dynamic Object in ObjectScript and put it into methods with <variablename>... (3 dots) format.
set a=##class(%SYS.Python).Import("a")
write a.test1(1,2,3) ;; 6set req={}
set req.a1=10set req.a2=20write a.test2(req...) ;; 30In recent years, artificial intelligence technologies for text generation have developed significantly. For example, text generation models based on neural networks can produce texts that are almost indistinguishable from texts written by humans.
ChatGPT is one such service. It is a huge neural network trained on a large number of texts, which can generate texts on various topics and be matched to a given context.
The SQL editor in the contest environment promises these features
InterSystems SQL Reference. .png)
But this is the reality:
I see no chance to have a different user.
Or did I miss something?
Or is this just fiction from ChatGPT ?
Keywords: ChatGPT, COS, Lookup Table, IRIS, AI
Here is another quick note before we move on to GPT-4 assisted automation journey. Below are some "little" helps ChatGPT had already been offering, here and there, during daily works.
And what could be the perceived gaps, risks and traps to LLMs assisted automation, if you happen to explore this path too. I'd also love to hear anyone's use cases and experiences on this front too.
After seeing several article raving about how ground-breaking the recent release of ChatGPT is, I thought I would try asking it to help with a Caché newbie question: How do you find the version of InterSystems Caché?
To be honest, I was quite surprised at what the chat bot told me: