Sam Rodriques

Today, we're announcing Edison Advances, a home for our research announcements, engineering blogs, open-weights models and benchmarks. At Edison, we’re building Kosmos, an AI Scientist, to solve foundational research problems and make truly novel discoveries across scientific domains. Alongside that work, we’re developing better ways to measure and evaluate AI scientists, push their ability to work on long-horizon tasks, and identify gaps in their reasoning. Edison Advances brings our existing work together in one place and we will use it to publish new work as our research progresses. Follow along as the work develops, and get in touch if you’re interested in contributing.

Read more about Edison Advances here: advances.edisonscientific.com/research/annou…

Today, we're announcing Edison Advances, a home for our research announcements, engineering blog, open-weights models and benchmarks. At Edison, we’re building Kosmos, an AI Scientist, to solve foundational research problems and make truly novel discoveries across scientific domains. Alongside that work, we’re developing better ways to measure and evaluate AI scientists, push their ability to work on long-horizon tasks, and identify gaps in their reasoning. Edison Advances brings our existing work together in one place and we will use it to publish new work as our research progresses. Follow along as the work develops, and get in touch if you’re interested in contributing.

Read more about Edison Advances here: advances.edisonscientific.com/research/annou…

Here are a few of the beliefs that guide our culture at Edison: 1. AI will unlock a new era of scientific progress. 2. Developing medicines is a serious business that requires deep humility and skepticism. It is not enough to simply assert that AI will accelerate medicine; we have to prove it. 3. Trust is critical, and we can’t build trust with our customers if we compete with them. 4. Generic concerns about safety do not justify broad restrictions on science. When there are specific, credible threats, we should mitigate those threats transparently and proportionately. Otherwise, we should trust our customers to use their judgment. 5. Open-weights models are good for science, since they improve reproducibility and transparency. 6. There are real human lives on the line here. Every day counts.

TIL the problem of deploying UVC to disinfect the air and suppress respiratory infections is essentially the problem of manufacturing a material with a bandgap at 222nm/5.59eV at scale (e.g. AlGaN). This actually seems like probably a good problem for the material science AI labs.

it's amazing how much I appreciate bad punctuation now in chats with customer service agents because at least it means they're human

The steamboat singularity. In 1850 it was realized that there was an empirical scaling law governing the horsepower of steam engines, and thus the speed of steamboats. By the year 2026, steamboats would achieve top speeds of 26,000mph. New York to London in 9 minutes. t.co/vCW2xNXZ2Y

Our paper on Robin came out in Nature yesterday -- awesome to see it in print finally. Congrats to the team! @agreeb66 @MichaelaThinks @andrewwhite01 @benjamin0chang and many others.

Intelligence will soon be commoditized. The thing that will not be commoditized is data. Nowhere is data more important than in science. Karp's words are important for all companies, but especially for companies in science: you have to make sure you own your data. x.com/PalantirTech/s…

If you want to work on using AI to accelerate the discovery of new medicines and scale up the creation of new biotech companies, get in touch.

At Edison, we are on a mission to leverage AI to prevent or cure all diseases. Today, we are announcing a critical step: our first partnership using our AI scientist, Kosmos, to launch new biotech companies. Many of the most transformative new medicines begin life in biotech companies rather than big pharmas. We are partnering with Population Health Partners (PHP) to deploy Kosmos across their company creation pipeline. Kosmos will assist in the creation of PHP’s companies, allowing us to bring more medicines to patients. PHP has an outstanding track record of incubating successful biotech companies like @MetseraInc (acquired by @pfizer in a $10B deal), and The Medicines Company (acquired by @Novartis for $9.7B), to name just two. With PHP, we will focus on biotechs treating population-scale diseases like cardiovascular disease and obesity. If we can scale up the process of launching Metsera-style companies, we have an opportunity to transform medicine in the coming years.

Vídeo

More on our collaboration here: edisonscientific.com/news/creating-…

Wow this is insanely awesome. I bet like <0.01% of X understands even remotely what this is or why it's important but this is insanely awesome. x.com/alexrives/stat…

One of my favorite podcast appearances, with @l2k. There is a long history of AI overpromising and underdelivering in biotech and pharma -- why is this time different? Super fun episode. x.com/wandb/status/2…

On Friday someone asked me how they should think about what they should do with their career. I told her the most important thing to recognize is that progress proceeds as a series of S curves, and the most important thing is to recognize when an S curve is going to take off and get in at the bottom. The rest -- what exactly you do, for example -- is less important. This is true if you’re a scientist just as much as if you’re an entrepreneur. With AI today, we don't exactly know where we are on the S curve or when/if it will flatten, but we're certainly not exactly at the bottom anymore. That said, the economy is going to change dramatically in the next 10 years, and there are a bunch of other technologies that are clearly just over the horizon, so there are lots of other S curves that are taking off right now. There are major opportunities in every direction. There has probably never been a better time to be a scientist or entrepreneur.

I have spent my entire life working on this and thinking about this for the past 4 years. I don't know what will happen in 20 years, but I can promise you that on the 5-10 year timescale, scientists are not out of their jobs. AI is going to massively accelerate the pace of science, increase productivity, let individual scientists make way more discoveries way faster, and is going to make science overall more fun. But the model is going to be collaboration between humans and AI, not replacement. The key difference here between science and e.g. software engineering is that science is not verifiable in any rapid/convenient way (unlike software), unlike programming. We still need humans for their scientific taste.

Our paper on Robin is out at Nature! Robin was the first multiagent system for end-to-end biological research, which we preprinted last year, and was published back to back with Google's awesome Coscientist from @vivnat. Great validation, and major congratulations to the team.

Check it out here: nature.com/articles/s4158…