Hmm, I hope they got a good price. This doesn't really seem like a pain point for researchers (at least not for me). We are all pretty adept at using existing tools to find the papers we need to find. The bigger issue is time to properly read them.
That said, I like the idea of CZI acting as a hub for tool development that will enable all researchers broadly. There are a bunch of tools that are incredibly useful to making logistics of a lab simpler.
1. Lab management and logistics: quartzy and others
2. Online paper writing: overleaf and a few others
3. DNA Bashing: benchling et al
4. Bioinformatics: They could do a bunch here
I worry that a lot of things in this space right now will disappear pretty quickly once the VC gravy train runs dry. More importantly, I think this is something that CZI might have expertise to do well and sustainably.
I don't know how meta works, but currently there is no quick way to do queries like: Find all studies which test compound X in concentrations between A and B sorted by organism, much less tools that use machine learning to extract the relevant information from thousands of papers and make simple summaries.
What would be much more useful that making logistics of labs simpler is cheaper and more flexible lab automation to make all tasks in a lab programmable and automated.
Pt1. Again, not sure this is useful, and has been tried many times with no useful end. The major issue is that simple summaries assume papers to be true. Just aggregating papers and making summaries is basically like search and reading abstracts. Understanding the true differences when within the morass is the hard part and usually is often very subtle.
Pt2. A lot of people talk about automation, but biology has changed so fast in the last decade that any serious automation efforts in this space have become quickly outdated. It's useful when you are doing the same thing a million times, but such things are often already automated.
I don't disagree with that, but I do think there's massive improvement waiting to be done on scientific search engines. Not sure if there will be any big breakthrough until computer can read and understand the content of scientific papers to a much higher extent than today though.
As for automation, I think that flexible automation solution shouldn't become outdated so fast. I think automating a lab to a large extent would be the same as automating a kitchen. You need to take thing in and out of storage, in a lab this would usually be different types of freezers, refrigerators, incubators etc., then you do stuff like mixing, slicing, dicing, heating, cooling, shaking, transferring liquids and solids between different types of equipment.
Smaller labs often don't have much automation. There's plenty of labs that don't even have lab robots, even though they do plenty of pipetting. Automated storage solutions are also rare as far as I know. Just deploying existing solutions and making them cheaper would help.
The only way to make thing really programmable though, is to automate everything. One challenge is that most machines and equipment only have interfaces for humans. If you were to place all your equipment in a kind of rack you could have a mix of conveyor belt for moving materials and robot arms on tracks in the roof to do manipulation tasks. Still it would be challenging to operate much of the equipment unless it is rebuilt to have standardized interfaces, but perhaps improvement in computer vision etc could eventually mitigate this. Another challenge is to make lab equipment communicate and compare data in completely different formats etc. There's lots of challenges but building a lab robotics system that can completely replace humans in doing the lab work should be possible even without hard AI and the hardware wouldn't necessarily have to be extremely expensive either.
Meta had a lot of promise but never realized it. I was an early adopter and watched the platform evolve. In the end, their discovery tools were never as good as google scholar: Meta constantly missed papers that would show up in other search engines, and the tools they promised - search by antibody, tool, equipment, organism - were all just vaporware. Good for them for selling to CZI, but the platform was just a major disappointment all around. They'll never catch Scholar.
That said, I like the idea of CZI acting as a hub for tool development that will enable all researchers broadly. There are a bunch of tools that are incredibly useful to making logistics of a lab simpler.
1. Lab management and logistics: quartzy and others
2. Online paper writing: overleaf and a few others
3. DNA Bashing: benchling et al
4. Bioinformatics: They could do a bunch here
I worry that a lot of things in this space right now will disappear pretty quickly once the VC gravy train runs dry. More importantly, I think this is something that CZI might have expertise to do well and sustainably.