TWIL: March 26, 2023
The world of AI and machine learning is constantly evolving, and the latest developments are pushing the boundaries of what is possible. From ChatGPT to GPT-4, Azure ML to MONAI, the possibilities for using AI to solve complex problems are growing. In this blog post, we’ll explore the latest advances in AI and ML, and discuss how they are being used in the medical field. We’ll also look at how developers can use these tools to create powerful applications.
Episode 1836: The Inflection Point of Large Language Models with Grant Barrett
ChatGPT, BingAI, and Google Bard are the latest examples of large language model machine learning – are we at an inflection point in technology? Carl and Richard talk to Grant Barrett of A Way with Words about the power of these new technologies to solicit reactions from many folks, including many tech journalists. Grant talks about how language conveys a sense of intelligence even when there is none to be had and the problems created by those assumptions. It is still the early days for these chatbots – will they rapidly improve or fade into another AI winter?
Episode 1837: Developer Velocity in the Cloud with Bryan Foster
How can the cloud help developer velocity? Carl and Richard talk to Bryan Foster about the complexities of modern software development – and how different cloud technologies can help move faster and not be afraid to break a few things along the way! Bryan talks about using Azure Deployment Environments to make it easy for developers to stand up resources for their apps – and just as quickly shut them down when done. This leads to a broader conversation around the governance of CI/CD pipelines and the role of the cloud, even to the point of using DevBox to have an entirely virtualized development environment!
The Azure Podcast
Episode 455: Azure ML in the real world
In this episode we chat with Andrés Padilla and Meer Alam about practical use of AI and ML systems. Examples of this are discussed around autonomous drone / delivery models and the various components in Azure that make this a seamless, scalable and sustainable experience.
Introducing GPT-4 in Azure OpenAI Service
Today, we are excited to announce that GPT-4 is available in preview in Azure OpenAI Service. Customers and partners already using Azure OpenAI Service can join the waitlist to access GPT-4 and start building with OpenAI’s most advanced model yet. With this milestone, we are proud to bring the world’s most advanced AI models—including GPT-3.5, ChatGPT, and DALL-E 2—to Azure customers, backed by Azure AI-optimized infrastructure, enterprise-readiness, compliance, data security, and privacy controls, along with many integrations with other Azure services.
Learn how to work with the ChatGPT and GPT-4 models (preview)
The ChatGPT and GPT-4 models are language models that are optimized for conversational interfaces. The models behave differently than the older GPT-3 models. Previous models were text-in and text-out, meaning they accepted a prompt string and returned a completion to append to the prompt. However, the ChatGPT and GPT-4 models are conversation-in and message-out. The models expect input formatted in a specific chat-like transcript format, and return a completion that represents a model-written message in the chat. While this format was designed specifically for multi-turn conversations, you’ll find it can also work well for non-chat scenarios too.
Sparks of Artificial General Intelligence: Early experiments with GPT-4
In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT4 is part of a new cohort of LLMs (along with ChatGPT and Google’s PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting.
‘Sparks of AGI’ – Bombshell GPT-4 Paper: Fully Read w/ 15 Revelations
Less than 24 hours ago a paper was released that will echo around the world. I read all 154 pages in one sitting. The paper suggests GPT 4 has ‘sparks of Artificial General Intelligence’. This is not just hype, I go through 15 examples detailing just what exactly the unrestrained GPT 4 is capable of. Insane highlights include the monumental ability to use tools effectively – this is an emergent capability not found in ChatGPT. I detail the kind of tools it has already demonstrated it can use, from using external APIs to being a true personal assistant, from a Fermi answerer to a Mathlete and a handyman. This paper may well change your thoughts on the state of AGI.
We’ve implemented initial support for plugins in ChatGPT. Plugins are tools designed specifically for language models with safety as a core principle, and help ChatGPT access up-to-date information, run computations, or use third-party services.
ChatGPT Retrieval Plugin
This is a plugin for ChatGPT that enables semantic search and retrieval of personal or organizational documents. It allows users to obtain the most relevant document snippets from their data sources, such as files, notes, or emails, by asking questions or expressing needs in natural language. Enterprises can make their internal documents available to their employees through ChatGPT using this plugin.
AI chatbots compared: Bard vs. Bing vs. ChatGPT
The chatbots are out in force, but which is better and for what task? We’ve compared Google’s Bard, Microsoft’s Bing, and OpenAI’s ChatGPT models with a range of questions spanning common requests from holiday tips to gaming advice to mortgage calculations.
Let’s build GPT: from scratch, in code, spelled out.
We build a Generatively Pretrained Transformer (GPT), following the paper “Attention is All You Need” and OpenAI’s GPT-2 / GPT-3. We talk about connections to ChatGPT, which has taken the world by storm. We watch GitHub Copilot, itself a GPT, help us write a GPT (meta :D!) . I recommend people watch the earlier makemore videos to get comfortable with the autoregressive language modeling framework and basics of tensors and PyTorch nn, which we take for granted in this video.
GitHub Copilot X: The AI-powered developer experience
Our R&D team at GitHub Next has been working to move past the editor and evolve GitHub Copilot into a readily accessible AI assistant throughout the entire development lifecycle. This is GitHub Copilot X—our vision for the future of AI-powered software development. We are not only adopting OpenAI’s new GPT-4 model, but are introducing chat and voice for Copilot, and bringing Copilot to pull requests, the command line, and docs to answer questions on your projects.
Multimodal 3D Brain Tumor Segmentation with Azure ML and MONAI
Since December 2021, we have released several examples to support Medical Imaging with Azure Machine Learning, and the response we received was overwhelming. The interest and inquiries reinforce how AI is quickly becoming a crucial aspect of modern medical practice. Today, we introduce a new medical imaging asset for 3D brain tumor segmentation, a solution that tackles a challenging use case in the field of oncology.
Have a splendid week!