various tasks while engaging in human-like conversations
The use of artificial intelligence (AI) is growing rapidly. San Francisco-based OpenAI recently made its latest creation, the ChatGPT chatbot, available for free public testing. It’s designed to mimic human speech in response to user feedback, and can instantly respond to everything from physics to birthday party ideas, writing essays, poems and jokes to health diagnoses. After ChatGPT’s release, hundreds of screenshots of ChatGPT chats circulated on Twitter, and its early fans were amazed at the results. We look at why everyone is obsessed with it, and whether it can actually lead to a skilled job.
ChatGPT is scary good, says Elon Musk
“ChatGPT is freaking good. We are not far from dangerously powerful artificial intelligence,” Elon Musk recently tweeted. Meanwhile, Musk also has a history with the company that created ChatGPT. OpenAI was founded as a nonprofit in 2015 by Silicon Valley investors Sam Altman and Elon Musk, and has attracted funding from several organizations, including venture capitalist Peter Thiel. In 2019, the group established a related for-profit entity to attract foreign investment. Musk resigned from OpenAI’s board in February 2018, but remained a donor.
ChatGPT applications
According to OpenAI, ChatGPT uses a machine learning technique called learning from human feedback (RLHF) that can mimic conversations, respond to follow-up questions, admit mistakes, object to wrong positions, and reject inappropriate requests. It can be used in real-world applications such as digital marketing, online content creation, and answering customer service questions. “What’s the best burger recipe?” In ‘Making a Piano Piece in the Style of Mozart’, users asked ChatGPT some strange questions and they successfully answered them.
Is your job in jeopardy?
After people became aware of ChatGPT and its uses, social media users said that they were putting people’s jobs at risk. However, ChatGPT has limitations, so we have to hold our horses. Based on a statistical model trained on billions of text samples downloaded from all over the Internet, the method makes probabilistic predictions about which pieces of text will go together in a sequence, generating answers in very simplified terms that make it prone to giving. wrong
the answers.
– Gaurav Kadam
