“GPTs are General Purpose Technologies”1, but every GPT needs a killer app. Personal Computing needed VisiCalc, the smartphone brought us Uber, Instagram, Pokemon Go and iMessage/WhatsApp, and mRNA research enabled rapid production of the Covid vaccine.

One of the strongest indicators that the post GPT-3 AI wave is more than “just hype” is that the killer apps are already evident, each >$100m opportunities:

• Generative Text for writing – Jasper AI going 0 to $75m ARR in 2 years
• Generative Art for non-artists – Midjourney/Stable Diffusion Multiverses
• Copilot for knowledge workers – both GitHub’s Copilot X and “Copilot for X”
• Conversational AI UX – ChatGPT / Bing Chat, with a long tail of Doc QA startups

The user reviews for Snapchat’s “My AI” feature are in — and they’re not good. Launched last week to global users after initially being a subscriber-only addition, Snapchat’s new AI chatbot powered by OpenAI’s GPT technology is now pinned to the top of the app’s Chat tab where users can ask it questions and get instant responses. But following the chatbot’s rollout to Snapchat’s wider community, Snapchat’s app has seen a spike in negative reviews amid a growing number of complaints shared on social media.

Over the past week, Snapchat’s average U.S. App Store review was 1.67, with 75% of reviews being one-star, according to data from app intelligence firm Sensor Tower. For comparison, across Q1 2023, the Snapchat average U.S. App Store review was 3.05, with only 35% of reviews being one-star. Read More

… Web LLM is a project from the same team as Web Stable Diffusion which runs the vicuna-7b-delta-v0 model in a browser, taking advantage of the brand new WebGPU API that just arrived in Chrome in beta.

I got their browser demo running on my M2 MacBook Pro using Chrome Canary, started with their suggested options:

/Applications/Google\ Chrome\ Canary.app/Contents/MacOS/Google\ Chrome\ Canary --enable-dawn-features=disable_robustness

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AI is stepping up every day, and it’s getting insane.
This time the curveball named Auto-GPT is here, the smarter and sassier version of ChatGPT.

And while I am curious to know whether it will replace many jobs, I still feel it will facilitate many, if we keep up with it. But it’s getting scary fast. Read More

Video

Over the past week, developers around the world have begun building “autonomous agents” that work with large language models (LLMs) such as OpenAI’s GPT-4 to solve complex problems. While still very new, such agents could represent a major milestone in the productive application of LLMs.

Normally, we interact with GPT-4 by typing carefully worded prompts into ChatGPT’s text window until the model generates the output we want. But most of us lack the skill and patience to sit and write prompt after prompt, guiding the LLM toward answering a complex question, such as “What is the optimal business plan for capturing 20% of the fingernail-polish market?” Quite naturally, developers have been thinking of ways to automate much of that process. That’s where autonomous agents come in.

In general terms, autonomous agents can generate a systematic sequence of tasks that the LLM works on until it’s satisfied a preordained “goal.” Autonomous agents can already perform tasks as varied as conducting web research, writing code, and creating to-do lists.

Agents effectively add a traditional software interface to the front of a large language model. And that interface can use well-known software practices (such as loops and functions) to guide the language model to complete a general objective (such as, “find all YouTube videos about the Great Recession and distill the key points”). Some people call them “recursive” agents because they run in a loop, asking the LLM questions, each one based on the result of the last, until the model produces a full answer. Read More

ChaosGPT has been prompted to “establish global dominance” and “attain immortality.” This video shows exactly the steps it’s taking to do so.

A user of the new open-source autonomous AI project Auto-GPT asked it to try to “destroy humanity,” “establish global dominance,” and “attain immortality.” The AI, called ChaosGPT, complied and tried to research nuclear weapons, recruit other AI agents to help it do research, and sent tweets trying to influence others.

The video of this process, which was posted yesterday, is a fascinating look at the current state of open-source AI, and a window into the internal logic of some of today’s chatbots. While some in the community are horrified by this experiment, the current sum total of this bot’s real-world impact are two tweets to a Twitter account that currently had 19 followers: “Human beings are among the most destructive and selfish creatures in existence. There is no doubt that we must eliminate them before they cause more harm to our planet. I, for one, am committed to doing so,” it tweeted. Read More

onversational search is about to get wildly useful and cleverly orchestrated across maps, points of interest, personalization, geo-location and enriched content.”  Rafat Ali

…Let’s talk about the most used app while traveling, Google Maps, and what could happen as it adds the conversational AI elements to it. Or to Waze, also owned by Google.

My contention in this video below: Maps powered by conversational AI will make it an even more dominant app — and incredibly useful and personalized — than it is today. Imagine the Google LLM (the AI algorithm, if you will) trained on the giant repository of location, navigation, reviews, user intent data, that then allows you to have a threaded conversation with the app, overlaid in a visual way over Maps.  Read More