Peter Gao

I like machine learning and ice cream. Co-founder and CEO at @aquariumlearn. Previously early employee at @cruise, interned at @khanacademy and @Pinterest.

[Daft @daftengine]

🚨 LAUNCH WEEK IS HERE 🚨

Watch Sammy, Co-Founder & CEO of Eventual, kick off an exciting week. We’ve rebranded. Rebuilt. Reimagined Daft. https://t.co/7viq8pCO1A
🧠 Faster docs
⚡️ Cleaner UX
📦 Ready for AI workloads at scale

Try out Daft today: pip install daft

[Peter Gao @pgaooo]

I'm excited to announce that Aquarium is joining Notion!

https://t.co/gnHRw4so8V

[Peter Gao @pgaooo]

We’re excited to announce that Tidepool can now run within Snowpark Container Services!

https://t.co/kHKkRSjh5E

[Peter Gao @pgaooo]

I'm sad to announce that we’re shutting down Illume, our computer vision data curation product. Given our limited resources as a startup, we've decided to focus our attention on developing our LLM product going forward.

https://t.co/3U249WraOD

[Peter Gao @pgaooo]

Tidepool now supports warehouse native integrations into Snowflake, making it even easier for teams on Snowflake to get insights from text data. Excited to be a part of the Snowflake app ecosystem!

https://t.co/r0S1ZPdmEy

[Peter Gao @pgaooo]

Launching Tidepool Warehouse Native! Now you can get started with analysis of your text within minutes and automatically sync Tidepool’s outputs back to your data warehouse, all without storing sensitive data outside of your cloud environment.

https://t.co/yZXFUhwFE6

[Peter Gao @pgaooo]

Providing examples is a useful tool for prompting LLMs, but did you know that the specific choice of examples has a dramatic impact on performance? Our own Lucy Cheng made a guide on how to pick examples to get the highest accuracy...

https://t.co/UoUVRwqqwU

[Peter Gao @pgaooo]

We made a new walkthrough video for Tidepool! Tidepool is an analytics tool for large text datasets. Categorize and surface patterns in unstructured text data like user prompts to LLMs, user feedback, social media posts, and more.

https://t.co/nGxFHhEKLw

[Peter Gao @pgaooo]

@patricklu10 Text data. Unless when you say SQL rows, you mean text stored in SQL rows? :P

[Peter Gao @pgaooo]

We just launched our new website for Tidepool! Tidepool is a data analytics tool for text data. It imposes structure on unstructured text so you can derive insights from text with your existing BI stack. Ping me if you want to try it!

https://t.co/PsaKSFZpYK

[Peter Gao @pgaooo]

LLMs are enabling new ways to design UIs! Charlene walks through some of the most impactful examples of how LLMs are changing the ways we interact with computing.

https://t.co/q5kI62bN3N

[Peter Gao @pgaooo]

Tidepool lets you derive some useful business insights from text data you already have! I wrote a walkthrough of the Yelp Review dataset to show how you can understand attributes of text data and their correlation to a metric of interest.

https://t.co/QLZPeap73A

[Peter Gao @pgaooo]

We've learned a lot of neat tricks while prompt engineering LLMs for Tidepool. To share some of these learnings, we wrote a guide on how to do JSON chain-of-thought prompting with GPT-4!

https://t.co/h91YXCen3G

[Charlene Chambliss @blissfulchar]

A lot of friends have asked me about my process for using LLMs to learn more quickly. Well, I finally wrote a post on the Tidepool blog about it! These are a few of my top strategies for efficient learning with LLMs: https://t.co/AiZClRnvce

[Peter Gao @pgaooo]

LLM engineering can seem like dark magic, but making some simple changes to your prompts can greatly improve your RAG quality!

https://t.co/W8C1SkhTeM

[Peter Gao @pgaooo]

We wrote a guide talking about how to diagnose and fix common issues with RAG systems!

https://t.co/plLh5nCwlW

[Peter Gao @pgaooo]

@FanaHOVA @latentspacepod @DecibelVC @swyx possible to see slides from the talk? I saw you posted https://t.co/vt0ndoj9xM on a previous thread but it seems to be 500-ing now.

[Peter Gao @pgaooo]

I know a lot of engineers who used to work in autonomy who are now working on LLMs. And it makes sense, too - it turns out a lot of lessons about improving robotic systems applies to improving generative AI systems!

https://t.co/O0aMi7bsl6

[Peter Gao @pgaooo]

Tidepool's Quality Reports help you find where your model is failing in production and break down your top failure cases by root cause. Prioritize work with the most impact and improve your LLM app faster!

https://t.co/gRMR0f32CV

[Peter Gao @pgaooo]

A common question LLM devs have is, "is my LLM doing what I want it to?" We wrote an article talking about some easy tips to make sure that your model is doing what you want it to before and after you ship it to users!

https://t.co/01KdmYrfI2