As developers, we are always looking for ways to make our lives easier, and that often means bringing in third-party libraries and tools that abstract away the nitty-gritty details of specific tasks. Langchain is one such tool that aims to simplify working with AI APIs (in reality, it doesn’t). However, as we’ll discuss in this blog post, you might not need Langchain at all. In fact, using direct APIs, such as the OpenAI API, can often result in better performance and less complexity.
There has been a bit of talk about Lanchain lately regarding the fact it is creating a walled garden around AI apps and results in lock-in. In this post, we’ll debate the differences between Langchain and just using an official SDK. I assume you’re working with OpenAI, but we also have Anthropic and Hugging Face (amongst others) to consider.
To understand the differences, Langchain is a framework for building AI apps. If you are a developer wanting to throw something together quickly, it is brilliant for quickly knocking out AI API wrapper apps, especially the OpenAI GPT API.
Reading the latest update from StackOverflow’s CEO, I can’t help but feel a sense of disconnect. StackOverflow and the broader StackExchange network are facing a tidal wave of change with the rise of AI, and it seems like they’re just treading water.
For many of us, AI tools like ChatGPT have become go-to resources. They’re efficient, user-friendly, and, most importantly, not judgemental. On the other hand, StackOverflow has become notorious for its hostile environment, particularly towards newcomers. It’s as if you need to pass a test of fire to ask a question, and that’s if you’re brave enough to ask in the first place.
Something interesting has happened with the famed GPT-4 model from OpenAI lately, and it’s not just me that has noticed. Many people have been talking about how GPT-4 lately feels broken. Some say it’s nerfed, and others are saying it’s possibly just broken due to resource constraints. There was a discussion recently on Hacker News in this thread which received 739 comments.
All signs indicated that OpenAI had changed something significant with ChatGPT lately and its GPT-4 model. Users reported that questions relating to code problems were producing generic and unhelpful answers.
Designers and developers have had a very long and complicated relationship with Adobe. Over the years, we have seen scrappy upstarts come and take a bite out of Adobe’s lunch: inVision, SketchApp, Figma (which Adobe acquired in 2022) and countless others. Despite numerous attempts, Adobe is still standing.
Here we are in 2023, and another attack wave is being set upon companies like Adobe in the form of generative AI. Tools like DALL-E and Midjourney make generating images easy and even manipulating images without setting forth inside Photoshop. But, Adobe is not taking this lying down.
Introduction
In data science and machine learning, cosine similarity is a measure that calculates the cosine of the angle between two vectors. This metric reflects the similarity between the two vectors, and it’s used extensively in areas like text analysis, recommendation systems, and more. This post delves into the intricacies of implementing cosine similarity checks using TypeScript.
Understanding Cosine Similarity and Its Applications in AI
Cosine similarity measures two non-zero vectors of an inner product space. It is defined as the cosine of the angle between them, which is calculated using this formula:
In recent years, we’ve seen an unprecedented rise in the development and adoption of artificial intelligence (AI) tools, such as OpenAI’s ChatGPT. As AI becomes increasingly integrated into our daily lives, it’s essential to ask whether governments should step in and regulate these technologies.
While some argue that ChatGPT is a glorified sentence constructor and poses no real threat, others believe that regulation is necessary to prevent misuse and ensure ethical practices. In this article, we’ll explore both perspectives and attempt to determine whether AI regulation is needed.