graphene
Onwards and upwards!
Where does the money go?
The penalty is divided up between the other European
data authorities, while the money that comes to the
ICO goes directly to the Treasury.
Much more concerned about the possibility of the current Labour party gaining power actually.
texfiles = acronyms.tex analytical_mecs_procedure.tex analytical_mecs.tex \
anderson_old.tex background.tex chaincap.tex \
conclusions.tex cvici.tex gold_chain_test.tex introduction.tex \
main.tex mcci_manual.tex methods.tex moljunc.tex \
tb_sum_test.tex times_procedure.tex tm_mcci_workflow.tex tmo.tex \
vici_intro.tex
# dynamically generated figures
all: main.pdf
main.pdf: $(texfiles) figures/junction_occupations.pdf figures/overlaps_barplot.pdf \
figures/transmission_comparison.pdf \
figures/wigner_distributions.pdf
pdflatex main.tex && bibtex main && pdflatex main.tex && pdflatex main.tex
figures/junction_occupations.pdf: figures/junction_occupations.hs
ghc --make figures/junction_occupations.hs
figures/junction_occupations -w 800 -h 400 -o figures/junction_occupations.svg
inkscape -D -A figures/junction_occupations.pdf figures/junction_occupations.svg
figures/overlaps_barplot.pdf: figures/overlaps_barplot.py
python figures/overlaps_barplot.py
figures/transmission_comparison.pdf: figures/transmission_comparison.py
python figures/transmission_comparison.py
figures/wigner_distributions.pdf: figures/wigner_distributions.py
python figures/transmission_comparison.py
clean:
rm *.log *.aux *.blg *.bbl *.dvi main.pdfOr is that an oversimplified view?
About heating with computers, There is a Dutch company doing this, https://cloud.nerdalize.com/. It's interesting to think about how their economics work, because the heaters will be switched off for large parts of the year, and for much of the day. They must be banking that computation won't get much cheaper over time (in terms of FLOPS/$) because otherwise it'd be hard to recoup their initial investment. In a sense, this almost looks like a bet against Moore's law!
I can't help but think it would be really cool to automatically produce a circuit that would output the gradient of the error of the actual NN, so you could optimize that directly.
Unfortunately it doesn't have a (pure) TeX reader yet, but that could be implemented relatively easily.
It's anyone's guess how significant these constraints will be from the viewpoint of developing artificial protein machines (maybe rapid (bio)degradation is a good thing!), but there's definitely large swathes of chemical design space outside of arbitrary chains of known amino acids, and we might be able to discover entire classes of molecular machines that don't have the drawbacks of bioinspired proteins.
Of course in an ideal world those cycles would be used to help cure cancer, but given that these warheads exist, it's probably a good idea to invest resources into getting an idea of what shape they're in.
Therefore, even if the raw performance in terms of FLOPS sound similar, the two systems will have widely differing performance on real workloads.
Re: rigidity; I'm curious (apologies for not having read your papers) how you define "just enough" flexibility, and how your design tools take freely moving components into account. Would you agree with my intuitive feeling that there's a tradeoff between designability and functionality, and that your spiroligomer work sits between rationally designed protein structures (very hard problem) and Drexlerian molecular-scale gears and ratchets (similar, determinsitic design rules as in macroscopic systems)? Or, do you feel that anything protein "machines" can do, spiroligomer machines can do too?
I recently started a startup that has molecular nanotechnology as the end goal, and my thinking has been that the flexibility of proteins is an essential element in achieving the capability to design and manufacture with atomic precision, and that the concomitant complexity of the large numbers of degrees of freedom can be tamed with a data-driven approach leveraging machine learning algorithms. I'd love to hear if you have any thoughts on this, and how it relates to the spiroligomer approach.
If you read the Feynman speech that he references at the beginning, he actually mentions that as you scale machines down, things like mechanical rigidity will degrade and you will need to change your design rules accordingly. I always assumed that when you reach the molecular level, thermal motion and the constant bombardment by water molecules would mean that the only viable option is to use proteins, just like nature does, so it's very interesting to see that this guy is aiming to use more rigid structures at the molecular level. I guess this is a way to reduce the complexity (degrees of freedom) compared to designing protein tertiary structure. I wonder if this is too constraining though, he admits he has yet to figure out how to build mechanical machines using this approach, and intuitively I'd expect that to be very difficult with this degree of rigidity. You might need the additional flexibility of peptide chains to do many of the interesting things that are possible.
He does point out the advantage of durability, but this raises the obvious issue that one of the questioners alluded to, namely toxicity/pollution risk. I'd think degredation by biological or other means would be a feature, not a bug, since as he points out, even conventional plastics are a huge pollution problem.
Fascinating stuff nonetheless.
After three months, they invest £10000 (in exchange for 8% equity) in all teams that are settled on an idea and seem promising.
There are no fees of any kind.
(disclosure: I'm on the current cohort)
(disclaimer: also in the current cohort)
It won't be that simple, since even this (allowing customers to contribute power back to the grid at scale) requires expensive infrastructure upgrades.
Also, the main result of this work seems to be not energetic efficiency, but the production of flexible precursor chemicals.
On the wetware side, there is of course a similar incentive to keep the genetic sequences that result from your work private, in addition to perhaps ethical concerns regarding the dissemination of arbitrary DNA.
As a fellow software guy considering going into drug development research though, I do wonder: Given your mentioned open source credentials, it's probably plausible that you are at least sceptical about software patents? If so, what is your opinion on patents on drug molecules and DNA sequences? I'm struggling a bit with this since the only way to a big exit seems to involve protecting any findings as IP (because of the costs of the regulatory process), but I'm not sure I'd want my work to be patent-walled.
Do you know what you would do if you are one day faced with the choice of whether or not to patent one of your molecules or sequences, knowing that not doing so would have significant adverse financial effects on your company?
(This all may sound somewhat critical, but I'm really just curious. My email is in my profile if you prefer to respond privately.)