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The AI Gold Rush

The AI Gold Rush

🙂 Pieter Levels new AI project 📝 Overview of the AI writing landscape 📖 A videobook 🧃 Product marketing with AI

Ben Tossell
October 28, 2022

We did it! Over 2k subs in 3 weeks of this daily email. Thank you all so much 🥹. And welcome, to the 162 new folks joining the action since yesterday.

The weekend's here and I'm going to London to be a social butterfly.

Let's get to it. I'll see you Monday!

Prompt: List the topics in today’s email:

🙂 Pieter Levels new AI project📝 Overview of the AI writing landscape📖 A videobook🧃 Product marketing with AI

🫦 BEN'S BITES

Tony Tassell (hey, similar to Tossell!), wrote a piece in the FT about the rise of AI-generated images - what is now possible and what is coming 🔮.

Sony’s new camera uses a dedicated AI processor to identify and track subjects. It’s only $3,800 😳.

Pieter Levels is at it again, this time with an AI Avatar project. Upload some photos of yourself, train a model on it and then generate 30 AI avatars of your own face in different styles. I don’t need to pay $30 to see my mugshot in different styles… but people are paying.

A great overview of the AI writing landscape. This post looks to the future and touches on; price, regulation and ethics.

AI-generated audio summaries of podcasts.

👋 Too many links?! I created a database for all links mentioned in these emails. Refer 1 friend using this link and I'll send over the link database.

A new model for Structure-based Drug Design with Equivariant Diffusion Models

Yesterday we saw Spide-verse and Arcane-tuned models, and today there are; Disney, Dark Academia, Archer, Cyberpunk and tons more being released.

Broken Neural Scaling Laws. This research proposes a much more accurate approach.

Gradio Crash Course - Fastest way to build & share Machine Learning apps, by Assembly AI.

Introducing The Stack - a 3TB dataset of permissively licensed code in 30 programming languages. If you want your code excluded from the training, there is an opt-out form and data governance plan.

Daniel Gross built a videobook. It generates images as it reads the story to you. Demo here and code here.

Scale built a way for marketers to AI-generate UNLIMITED and INFINITELY CREATIVE images of products for - ad creatives - brand campaigns - social media. It's in early access. And no, coconut is horrid - I'm a Pamplemousse kinda guy 😉

Google acquires Twitter-backed AI avatar startup Alter for $100 million.

Generate and fine-tune music on Musika.

DALL-E released collections! a way to share your creations with the world and let others see what you made. Midjourney has had this for a while, good to see DALL-E finally release this. An example collection.

Yohein built a private mobile & web app, with no code, that pulls in all school-related emails for kids and summarizes and shows action items. Gmail (filter) → Zapier (tags and gpt3 summarise) → Airtable → Softr.

Eric Schmidt and his wife, Wendy, have announced their AI in Science Postdoctoral Fellowship to accelerate the next scientific revolution, with a cool $148M in funding. Imperial College and San Diego are two of the universities chosen.

The race is on to find the applications of generative AI that will make a mark on the world. “AI's New Creative Streak Sparks a Silicon Valley Gold Rush”.

Apple is now hiring for AI/ML residencies for summer 2023. Job listings are here.

A multiplayer experiment for Stable Diffusion, SD infinity - coming soon. Similar to the SD canvas I shared yesterday.

This study extends Maestro, a speech-text joint pretraining framework for automatic speech recognition (ASR), to speech-generation tasks.

A large-scale Chinese text-to-image diffusion model, which progressively upgrades the quality of generated images - ERNIE-ViLG 2.0.

Post Parrot - A free marketing tool that generates post titles that drive engagement on Reddit. These were the suggestions I got:

A few pages from a Midjourney-produced printed manga, AbsXcess.

Intel announces up to $10 billion in cost reductions through 2025, after poor performance.

Here are some pain points while using AI for drug development; smaller datasets, complex data, complicated data labelling, data bias, lack of data standards, lack of biological data and regulation.