I’m excited to announce that @harvey has acquired @guardrails_ai !
Back when we started Guardrails, our mission was to build infra that made the AI transformation of work more reliable and secure. Our open source framework helped establish the guardrails infrastructure category, and Snowglobe, our simulation software, helped our customers save millions of dollars in operating costs.
Today, legal AI is at the frontier of the knowledge work transformation, and I’m excited to carry our mission forward by bringing everything we’ve built to Harvey.
I want to thank our amazing customers, the Guardrails open source community, our team, investors and my partner-in-crime @zaydsimjee for their support throughout our journey. I’m super proud of what we built together, and can’t wait to work on the frontier of legal AI with @winstonweinberg, @gabepereyra and the incredible team they built!
https://t.co/oiFzYLX8GB
Transformers are better at copying, while RNNs are better at modeling "meaning-bearing words—the nouns, verbs, & adjectives that say what a sentence is about"
We're building something special here @profound.
A big thank you to @kleinerperkins for visiting us at our New York HQ and giving us an opportunity to tell our story.
Stay tuned for our next chapter as we expand to become the marketing platform for AI.
We released Sonic-3.5 and Ink-2, the #1 streaming models for text to speech and speech to text you can use in your voice agents today.
New architectures enable new frontiers for speed and quality.
We're now the only provider to have #1 models for both speaking and listening.
When I finished college, my ambition was not to build the world’s fastest chip company.
I wanted to become a professor of development economics.
I went to work in Pakistan.
The Northwest Frontier Province is about as far from Silicon Valley as you can get.
After I came back, I started a PhD program and finished my classes and qualification exams.
Then I got bored.
I thought I'd add an MBA and end up teaching at a business school.
My housemate Jim was joining a tiny startup.
They asked me to join, twice.
I said no. I had no interest in data networking.
I thought it was plumbing.
Eventually I caved and wrote their business plan.
Then I joined them. And it turned out to be an extraordinary team and a phenomenal industry.
We built chips and systems for switching and routing. We played a small role in changing the world.
We sold the company less than a year later for $280M, when that was a lot of money.
8 of those guys are still with me, more than 25 years later, at @cerebras today.
I call it the myth of LinkedIn - this idea that we all had our careers mapped from the time we left high school.
Mine wasn't a straight path.
It was a series of accidents where I fell into things I enjoyed.
Where I was curious, met people whom I liked, and learned from.
If you're 18 and someone asks you to pick a narrow lane - don't.
Go to university.
Learn how to think.
Be as broad as you can.
Follow your curiosity. Explore.
The journey will take you to amazing places.
Stumbled onto https://t.co/PzN5DFHS8q by Norvig. "So my advice to you is to pick one of the 10,000 categories, or invent a category, and make progress in it. Pick problems that are ambitious enough that your expected value add over the next 20 years is at least $3.4M/yr."
Found my slides from college where I delivered a grad lecture on deep learning, history, and why I thought it was really really important.
Now that this stuff is popular more popular maybe more people will care about it.
https://t.co/0IiGtRR9ia
Equivariance is dead - long live equivariance?
Scaling pure Transformers is the future of molecular generative models?
I think its a lot more nuanced -- I tried to give some perspectives in my spotlight talk at #ICLR2025 AI4Mat Workshop last week
thanks @gwern for a beyond quality education on some of the most interesting rabbit holes over all these years (also the dedication to the design).
hoping to pay off more of this debt over time 🙏