A trick to create ChatGPT templates using the new share feature
Faster GPT-4 and Longer context window (Up to 1 million tokens) on OpenAI's near-term roadmap
In today’s email:
🧠 A trick to create ChatGPT templates using the new share feature.
🔥 Faster GPT-4 and Longer context window (Up to 1 million tokens) on OpenAI's near-term roadmap
🎥 Step-by-step tutorial to build a Midjourney v5.1 prompt
🛠 Various AI-related tools and platforms, including Elai, OpenChat, Roll ai, Hyper, Graphy, Recraft, Bolt AI, Rask, and more.
Highlights💡
OpenAI’s plans according to Sam Altman [Link]
OpenAI is heavily GPU limited at present
The near-term roadmap includes faster GPT-4, Longer context window (Up to 1 million tokens are plausible), and A stateful API (a version of the API that remembers the conversation history)
Plugins “don’t have PMF” and are probably not coming to the API anytime soon
OpenAI will avoid competing with their customers — other than with ChatGPT
Regulation is needed but so is open source
The scaling laws still hold (making models larger will continue to yield performance)
Did you know you could do this? (Think of using shared chats as templates or memories for new chats)
no f#%king way
I didn't know I could do this???
🔹 Copy the chat link of a chat in ChatGPT
🔹 Paste it into a new chat with web browsing enabled
🔹 It'll pick up what was written in the other chatbrb, marketing brain exploding right now 🫠
— Taylor Peterson 💫 (@spacecasetay)
3:15 PM • May 31, 2023
Learn AI like it’s 2023 [Link]
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Let’s Verify Step by Step - OpenAI's new impressive blog and Paper [Paper], [Blog]
TLDR: We’ve trained a model to achieve a new state-of-the-art in mathematical problem solving by rewarding each correct step of reasoning (“process supervision”) instead of simply rewarding the correct final answer (“outcome supervision”)
Large language models often produce logical mistakes, called hallucinations, in complex multi-step reasoning.
The study compares two methods of training reward models to detect hallucinations: outcome supervision and process supervision.
Process supervision, which provides feedback for each step in a chain of thought, leads to significantly better performance compared to outcome supervision.
Process supervision has alignment advantages as it rewards aligned thinking and encourages interpretable reasoning.
Outcome supervision may reward unaligned processes and is harder to scrutinize.
Process supervision incurs a negative alignment tax in the math domain, meaning it performs better while being more aligned.
If the results generalize, process supervision could offer a more performant and aligned method compared to outcome supervision.
Midjourney v5.1 Tutorial - How to Build a Prompt - Including Prompts + Beginner Friendly
Tools & Links 🛠️
Elai - Create AI videos from just text [Link]
Roll.ai - Create professional, studio-quality remote videos in minutes, with just an iPhone. [Demo], [App Store]
UC Berkeley AI Hackathon - June 17th - 18th @ UC Berkeley [Apply here]
DietPrompt - Motivational speeches, only for you. [Link]
Listen to Alisa's motivational speech
Recraft AI - Generate vector art, 3D images, and more [Link]
Bolt AI - Instant access to ChatGPT on any Mac app [Link]
Rask AI - Localize videos. Fast. Fun. With AI [Link]
DeepLearning AI launched a new mini-course in collaboration with OpenAI: Building Systems with the ChatGPT API [Link]
Concept - Apple is expected to unveil the long-rumored Reality Pro at WWDC on Monday. This is what we think it looks like based on patents, reports, and more [Link]
Japan Goes All In: Copyright Doesn’t Apply To AI Training [Link]
Meta Quest Gaming Showcase is back for 2023! Tune in on Thursday, June 1, at 10:00 am PT for the exclusive game reveals and more. [Watch here]
Unclassified 🌀
Morning Brew - Get smarter in 5 minutes (it's free) [Link]
Fiverr - Find the right freelance service, right away [Link]
AI Is Not an Arms Race [Link]
Go from 'we' to 'me' in just one click
Thanks to Photoshop's new AI feature you can go from 'we' to 'me' in just one click."
— Lorenzo Green 〰️ (@mrgreen)
5:59 AM • May 31, 2023
