I used to waste years preparing gourmet meals. It was creative, an expression of my humanity, and fostered zen.
Thanks to McDonalds, I don't have to do that!
I used to waste years preparing gourmet meals. It was creative, an expression of my humanity, and fostered zen.
Thanks to McDonalds, I don't have to do that!
This is sad
@lawprofblawg It used to be that you had to spend thousands of dollars on paying someone in the Global South to write your PhD thesis for you.
Now all you need is a subscription to Claude or OpenAI!
@lawprofblawg Hypothesis:
Anyone who genuinely believes that AI can “replace” humans is living such a limited existence that this is indeed possible.
@lawprofblawg It's not even McDonalds. It's like pieces of foam painted to look like food. It doesn't even perform the function it's purported to on a minimal level. It just looks like the same thing to a really noncritical observer.
That comment was written by someone who utterly fails to understand what research *is*.
@lawprofblawg I used to spend years lifting heavy weights, slowly building my strength and endurance, fighting through fatigue and lack of motivation.
A forklift could have lifted all that weight in an instant.
The weight lifting game has changed forever.
@krig @lawprofblawg I used to spend 10 minutes walking to the neighborhood grocery store. On the way I met neighbors, cleaned up litter, saw interesting flowers and artwork people on people's homes and businesses, got exercise, and didn't pollute the air, make loud noise, put anyone's life at risk.
A car could get me there in 2 minutes. The transportation game has changed forever. Are we really proud of that in hindsight?
@bovaz @lawprofblawg They are trying:
https://www.biorxiv.org/content/10.1101/2025.08.01.668204v1.full.pdf+html
It’s great to automate this, the reason we need LLMs for multidimensional optimisation when we have several numerical approaches for this is still unclear to me though.
Access to recombinant proteins is vital in basic science and biotechnology research. Cell-free gene expression systems provide one approach to address this need, but widespread utilization remains limited by the cost, complexity, and inconsistency of current platforms. To address these limitations, we carry out a multi-dimensional definitive screening design to reduce the number of reagent components and remove costly secondary energy substrates. From more than 1,200 reagent formulations, we discover a simple and reproducible system based on 12 components. The optimized reagent formulation can produce 2.4 ± 0.3 g/L of protein product at the 15-μL scale (∼$55/gprotein) and 3.7 ± 0.2 g/L (∼$36/gprotein) at the 4-mL scale with oxygen supplementation. This provides an 84 to 99% reduction in cost over previous cell-free reagent formulations. We further show that the optimized reagent formulation can produce nucleoside triphosphates from nucleotides and ribose and that it is robust to failure across batches of cell lysates, users/locations, and in the synthesis of different proteins. Specifically, we demonstrate the production of fifteen therapeutically relevant products, including full-length aglycosylated monoclonal antibodies. We anticipate that our optimized reagent formulation will further democratize the use of cell-free systems for protein manufacturing and synthetic biology applications. ### Competing Interest Statement MLO and MCJ have filed an invention disclosure based on the work presented. MCJ has a financial interest in SwiftScale Biologics, Gauntlet Bio, Pearl Bio, Inc., Synolo Therapeutics and Stemloop Inc. MCJ's interests are reviewed and managed by Stanford University in accordance with their competing interest policies. National Science Foundation, CBET - 2341123, DGE-1842165, 2021900 DARPA, W911NF-23-2-0039 Department of Energy, DE-SC0023278

@lawprofblawg
There is a tremendous danger here that people start relying on #AI so much they don't bother to learn on their own, and eventually unable to "fact check" what they are told to know if it's correct or not. 🤔
"#ArtificialIntelligence will never be a match for Natural Stupidity" - Mugsy
@lawprofblawg
I've done a PhD in computational physics prior to AI, now I work as a staff software engineer and conservatively use AI coding tools.
The person in the screenshot has a point. In my PhD, there were many time consuming and stupid tasks. Like figuring out dependency paths to compile a library. Porting plotting code from one library to another. This tedium is not where research happens.
If you delegate your core job, it will be bad, of course.
@lawprofblawg
The quoted post is also completely wrong - a gen AI program cannot design, run and report experiments. it can certainly write up some text that says that it did...
Of course, it would be nice to accelerate some parts of research and we already do that via automation of some parts of experiments and of data analysis. But inventing the contents of research is the opposite of what we want.
So we definitely need to keep training researchers, not only because doing it yourself is nice and formative, but also because it is the only way to actually do it.
I spent years trying to learn the French language, to understand its history and culture, so that I could travel to and appreciate French-speaking lands.
Now, the translate app on my phone can let me understand what they are saying in seconds.
Learning a foreign language has changed forever.