This Week in AI, August 7: Generative AI Involves Jupyter & Stack Overflow • ChatGPT Updates

Generative AI Comes to Jupyter & Stack Overflow • ChatGPT Updates
Picture created by Editor with Midjourney


Welcome to this week’s version of “This Week in AI” on KDnuggets. This curated weekly publish goals to maintain you abreast of essentially the most compelling developments within the quickly advancing world of synthetic intelligence. From groundbreaking headlines that form our understanding of AI’s position in society to thought-provoking articles, insightful studying sources, and spotlighted analysis pushing the boundaries of our information, this publish supplies a complete overview of AI’s present panorama. This weekly replace is designed to maintain you up to date and knowledgeable on this ever-evolving area.


The “Headlines” part discusses the highest information and developments from the previous week within the area of synthetic intelligence. The knowledge ranges from governmental AI insurance policies to technological developments and company improvements in AI.

💡 Generative AI in Jupyter

The open supply Mission Jupyter crew has launched Jupyter AI, a brand new extension that brings generative AI capabilities straight into Jupyter notebooks and the JupyterLab IDE. Jupyter AI lets customers leverage giant language fashions by way of chat interactions and magic instructions to elucidate code, generate new code and content material, reply questions on native recordsdata, and extra. It was constructed with accountable AI in thoughts, permitting management over mannequin choice and monitoring of AI-generated output. Jupyter AI helps suppliers like Anthropic, AWS, Cohere, and OpenAI. It goals to make AI accessible in an moral option to improve the Jupyter pocket book expertise.

💡 Announcing OverflowAI

Stack Overflow introduced OverflowAI, their integration of AI capabilities into their public Q&A platform, Stack Overflow for Groups, and new merchandise like IDE extensions. Options embody semantic search to search out extra related outcomes, ingesting enterprise information to bootstrap inside Q&A quicker, a Slack chatbot accessing Stack Overflow content material, and a VS Code extension surfacing solutions in builders’ workflows. They goal to leverage their group’s 58M+ questions whereas guaranteeing belief by way of attribution and transparency round AI-generated content material. The purpose is to make use of AI responsibly to boost builders’ effectivity by connecting them with options in context.

💡 ChatGPT Updates

Over the previous week, a number of small updates have been rolled out to boost the ChatGPT expertise. These updates included the introduction of immediate examples to assist customers start chats, urged replies for deeper engagement, and preferences for utilizing GPT-4 by default for Plus customers. Further options resembling multi-file uploads within the Code Interpreter beta for Plus customers, a brand new stay-logged-in perform, and a collection of keyboard shortcuts have been additionally launched to enhance usability.


The “Articles” part presents an array of thought-provoking items on synthetic intelligence. Every article dives deep into a particular subject, providing readers insights into varied facets of AI, together with new methods, revolutionary approaches, and ground-breaking instruments.

📰 I Created An AI App In 3 Days

The creator experimented with ChatGPT prompts to create an AI-powered cowl letter generator net utility known as Tally.Work in simply 3 days, utilizing for the frontend and the OpenAI API for producing textual content. It takes a consumer’s resume and job description as inputs and outputs a personalized cowl letter. The purpose was to construct an app with a big potential consumer base. Although AI-generated textual content is not good but, it could actually assist create a helpful first draft. The creator believes AI will remove many tedious duties like cowl letters, and hopes this undertaking helps result in extra attention-grabbing AI apps sooner or later. General it exhibits how rapidly somebody can use no-code instruments and AI APIs to construct and launch an app thought.

📰 Three challenges in deploying generative models in production

The article discusses three foremost challenges in deploying generative AI fashions like GPT-3 and Steady Diffusion in manufacturing: their large measurement resulting in excessive compute prices, biases that may propagate dangerous stereotypes, and inconsistent output high quality requiring tuning. Options embody mannequin compression, coaching on unbiased knowledge, post-processing filters, immediate engineering, and mannequin fine-tuning. General it outlines how firms should rigorously tackle these points to efficiently leverage generative fashions whereas avoiding potential downsides.


The “Instruments” part lists helpful apps and scripts created by the group for many who wish to get busy with sensible AI purposes. Right here you can find a variety of software sorts, from giant complete code bases to small area of interest scripts. Be aware that instruments are shared with out endorsement, and with no assure of any type. Do your personal homework on any software program previous to set up and use!

🛠️ Robot Writers Room

This repository demonstrates utilizing AI to brainstorm and refine story concepts collaboratively with a human. Quite than changing the human, the AI acts as a inventive companion, suggesting concepts and doing analysis. At every step, the human can settle for, reject, or modify the AI’s recommendations. One of many foremost challenges in writing is arising with concepts. This undertaking goals to assist writers overcome author’s block by offering a inventive companion to bounce concepts off of.

🛠️ Gdańsk AI

Gdańsk AI is a full stack AI voice chatbot (speech-to-text, LLM, text-to-speech) with integrations to Auth0, OpenAI, Google Cloud API and Stripe – Net App, API and AI


The “Analysis Highlight” part highlights vital analysis within the realm of AI. The part consists of breakthrough research, exploring new theories, and discussing potential implications and future instructions within the area of AI.

🔍 ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

The paper introduces ToolLLM, a framework to boost the tool-using talents of open-source giant language fashions. It constructs a dataset known as ToolBench containing directions involving 16,000 real-world APIs throughout 49 classes. ToolBench is mechanically generated utilizing ChatGPT with minimal human involvement. To enhance reasoning, the authors suggest a depth-first search choice tree technique that enables fashions to guage a number of reasoning traces. In addition they develop an computerized evaluator ToolEval to effectively assess tool-use capabilities. By fine-tuning LLaMA on ToolBench, they acquire ToolLLaMA which demonstrates sturdy efficiency on ToolEval, together with generalizing to unseen APIs. General, ToolLLM supplies a option to unlock subtle software use in open-source LLMs.

🔍 MetaGPT: Meta Programming for Multi-Agent Collaborative Framework

This paper introduces MetaGPT, a framework to enhance giant language mannequin collaboration on complicated duties. It incorporates real-world standardized working procedures into prompts to information multi-agent coordination. Roles like ProductManager and Architect produce structured outputs matching business conventions. A shared surroundings and reminiscence allow information sharing. On software program duties, MetaGPT generated extra code, paperwork, and better success charges than AutoGPT and AgentVerse, displaying its capability to decompose issues throughout specialised brokers. The standardized workflows and outputs goal to cut back incoherence in conversations. General, MetaGPT demonstrates a option to seize human experience in brokers to deal with intricate real-world issues.


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