Hi this is Piti from Analytics India magazine and in today's episode we will be talking about GPT3 open AI's latest AI language model. So let's get right to it. GPT3 is the most powerful language model ever built. Let's compare. The model has 175 billion parameters. To put that figure into perspective, its previous model GPT2 which was considered state of the art and shockingly massive when it was released last year had 1.5 billion parameters which was soon eclipsed by Nvidia's Megatron with 8 billion parameters followed by Microsoft's Turing energy that had 17 billion parameters. Now open AI turns the table by releasing a model that is 10 times larger than Turing energy. GPT3 is largely being recognized for its language capabilities. When properly primed by a human it can write creative fiction. Researchers say that GPT3 sample are not just close to a human level. In fact they are creative, witty, deep, meta and often beautiful. They demonstrate an ability to handle abstractions like style parodies, ride poems etc. They also said that chatting with a GPT3 feels very similar to chatting with a human. It can also generate functioning code. In the latest news, Sharif Shameem, the founder of Debil, a startup which enables developers to build apps with minimum effort has leveraged GPT3 to generate codes. All Shareen had to do was enter the text that captures the essence of the product and the generator dishes out code. According to Shareen, he only had to write two samples to give GPT3 context for what he wanted to do. It then properly formatted all of the other samples. For example, he asked for a button that looked like a watermelon and it gave him just that. Shameem also went ahead and said that he built a to-do list app simply by describing it to GPT3. GPT3 generated the react code for a fully functioning app within seconds. I'll provide the link to the article in the description box below where you can go ahead and watch the video. GPT3 can also compose thoughtful business memos. Researchers say that they fact GPT3 with the first half of how to run an effective board meeting. And in a few minutes, it wrote up a three step process on how to recruit board members adding up to any essay. Basically, adding relevant knowledge. GPT3's possible uses can be only limited to our imagination. At its core, GPT3 is an extremely sophisticated text predictor. A human gives it a chunk of text as input and the model generates his best guess as to what the next chunk of text should be. It can then repeat this process, taking the original input together with a newly generated chunk, treating that as a new input and generating a subsequent chunk until it reaches a length limit. But how does GPT3 go about generating these predictions? The answer to that question is that it has ingested effectively all of the text available on the internet. The output it generates is language that it calculates to be a statistically plausible response to the input it is given based on everything that humans have previously published online. Amazingly rich and nuanced insights can be extracted from the patterns latent in massive data sets far beyond what the human mind can recognize on its own. This is the first premise of modern machine learning. Having trained on a data set of half a trillion words, GPT3 is able to identify and dazzlingly rift on the linguistic patterns contain but GPT3 is not perfect. It lacks the ability to reason abstractly. Basically it lacks true common sense. For example, consider the following exchange with GPT3 courtesy of Kevin Lacker. How many eyes does a giraffe have? A giraffe has two eyes. How many eyes does my foot have? Your foot has two eyes. How many eyes does a spider have? A spider has eight eyes. How many eyes does a sun have? The sun has one eye. This example does not mean that GPT3 is not a useful tool or that it will not underpin many valuable applications. On Twitter, open AI CEO Sam Altman made a statement. The GPT3 high is way too much. AI is going to change the world but GPT3 is just an early glimpse. And with that, we come to the end of this video. Don't forget to subscribe to analytics India magazine and follow this segment for everything related to data science. See you soon. Bye!