OpenCopilot- AI Sidekick For Everyone
Plus: Google teaches LLMs to personalize, AI creates 3D experiences from phone video.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 89th edition of The AI Edge newsletter. This edition brings you OpenCopilot, an AI sidekick for your SaaS products.
And a huge shoutout to our incredible readers. We appreciate you!😊
In today’s edition:
🚀 OpenCopilot- AI sidekick for everyone
🧠 Google teaches LLMs to personalize
✨ AI creates lifelike 3D experiences from your phone video
📚 Knowledge Nugget: Local Llama by
Let’s go! 🧠
OpenCopilot- AI sidekick for everyone
OpenCopilot allows you to have your own product's AI copilot. With a few simple steps, it takes less than 5 minutes to build.
It integrates with your underlying APIs and can execute API calls whenever needed. It uses LLMs to determine if the user's request requires calling an API endpoint. Then, it decides which endpoint to call and passes the appropriate payload based on the given API definition.
Why does this matter?
Shopify has an AI-powered sidekick, while Microsoft (Windows Copilot, Bing Copilot) and GitHub (GitHub Copilot) have copilots. The above innovation empowers every SaaS product to have its own AI copilots tailored for its unique products.
Google teaches LLMs to personalize
LLMs are already good at synthesizing text, but personalized text generation can unlock even more. New Google research has proposed an approach inspired by the practice of writing education for personalized text generation using LLMs. It has a multistage and multitask framework consisting of multiple stages: retrieval, ranking, summarization, synthesis, and generation.
In addition, they introduce a multitask setting that further helps the model improve its generation ability, which is inspired by the observation that a student's reading proficiency and writing ability are often correlated. When evaluated on three public datasets, each covering a different and representative domain, the results showed significant improvements over various baselines.
Why does this matter?
Customizing style is essential for many domains like personal communication, dialogue, marketing copies, stories, etc., which is hard to do via pure prompt engineering or custom instructions. The research attempts to address this and highlights how we can take inspiration from how humans achieve tasks to apply it to LLMs.
AI creates lifelike 3D experiences from your phone video
Luma AI has introduced Flythroughs, an app that allows one-touch generation of photorealistic, cinematic 3D videos that look like professional drone captures. Record like you're showing the place to a friend, and hit Generate– all on your iPhone. No need for drones, lidar, expensive real estate cameras, and a crew.
Flythroughs is built on Luma's breakthrough NeRF and 3D generative AI and a brand new path generation model that automatically creates smooth dramatic camera moves.
Why does this matter?
This marks a significant leap in democratizing 3D content creation with AI and making it cost-efficient. It opens up new possibilities for storytelling and crafting stunning digital experiences for users across various industries.
Knowledge Nugget: Local Llama
For businesses, local LLMs offer competitive performance, cost reduction, dependability, and flexibility. This article by
provides practical guidance on setting up and running LLMs locally using a user-friendly project.Moreover, Llama-2 and its variants are the go-to models, and the community continually refines them. The article highlights some things to note when running Llama models locally, including memory and model loader challenges.
Why does this matter?
This helps make AI accessible to individuals and businesses while avoiding limitations and high expenses associated with commercial APIs. Locally deploying LLM also helps businesses have more over the model, customize it, integrate with existing systems, and enable full utilization of its capabilities.
What Else Is Happening❗
📢Big brands are increasingly using AI-generated ads, including Nestlé and Mondelez (Link)
🧠AI2 (Allen Institute for AI) drops biggest open dataset yet for training language models (Link)
📱Ex-Machine Zone CEO launches BeFake, an AI-based social media app (Link)
📚Montana Digital Academy is rolling out a new course on AI for high school students (Link)
🔍Wall Street turns to AI to solve WhatsApp compliance nightmare (Link)
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🧐Monday Musings: Open challenges in LLM research
It's truly remarkable how many brilliant minds are working on the same goal: making LLMs better.
In this intriguing article, the author deep dives into 10 major research directions that have emerged in the AI landscape after speaking with people who work from both industry and academia.
From tackling hallucinations in LLMs to optimizing context construction, incorporating multimodal data, and designing new model architectures and GPU alternatives, this article explores the most exciting frontiers of LLM research today.
Check it out and let us know what research direction you are most excited about and what solutions you find the most promising for these challenges.
(Source)
That's all for now!
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