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Dorian Gray Face Cream

Greg Chaitin, Life as Evolving Software, here. Sets up  a bunch of useful machinery to talk about computation. Personally, I would drive that machinery towards a Universal Debugger/rootkit to reverse engineer the genome/biosphere cell division rather than computation. On the computation side your upside is something like Karmarkar 2. With Universal Debugger your upside is Dorian Gray face cream that: beautifies,  cures cancer, enables you run faster than Usain Bolt, and provides the benefits of 20 years of psychoanalysis  in two applications. The face cream keeps Benedict Cumberbatch from becoming Randy Quaid and Miley Cyrus from becoming Phyllis Diller. If you Reverse some chunk of the Biosphere before the Chinese, Russians, and Indians, i’d imagine you get the Isaacson book and the Aaron Sorkin movie  and a bunch of other stuff. So the upside is way better on the Universal Debugger. Hard to estimate what the chances of seeing the upside are.

Few people remember Turing’s work on pattern formation in biology (morphogenesis), but Turing’s famous 1936 paper On Computable Numbers exerted an immense influence on the birth of molecular biology indirectly, through the work of John von Neumann on self-reproducing automata, which influenced Sydney Brenner who in turn influenced Francis Crick, the Crick of Watson and Crick, the discoverers of the molecular structure of DNA. Furthermore, von Neumann’s application of Turing’s ideas to biology is beautifully supported by recent work on evo-devo (evolutionary developmental biology). The crucial idea: DNA is multi-billion year old software, but we could not recognize it as such before Turing’s 1936 paper, which according to von Neumann creates the idea of computer hardware and software.

Radiolab, Antibodies Part 1: CRISPR, here. Wait,…the process model in all DNA maintains a stack that can match inputs against elements in the stack, maybe? Listen to the podcast and tell me that is not what they are saying. So you have all the cells in the biosphere from the last million or so years. They all have DNA/RNA programs that you can now sequence and read. The cells are like little transcription based computers with 3D printers that make stuff according the the DNA/RNA programs. You can read the programs. You can execute the programs. You can look at the outputs. CRISPR gives you universal  Cut  and Paste. You just want gdb and spice ( a debugger and a circuit simulator) then you got a shot at figuring out the cell division process model – and the Dorian Gray Face Cream and Reversing the Biosphere. Kurzweil might pull some google/alphabet talent.

Remember the story about the Russian guys in Moscow  somehow get possession of a running PDP10 back in the day but then have to  reverse the TOPS-10 source because they only have the executable for the OS. Word was their TOPS-10 was way better than DECs. Maybe they could make Dorian Gray Face Cream for Putin. This problem is more like the Russian guys got a trillion trillion trillion pdp10s, micro vaxes, vax780s on the black market all running slightly different code and they are asked to reverse engineer the operating systems so the government can make a clone to sell behind the iron curtain.

Hidden inside some of the world’s smallest organisms is one of the most powerful tools scientists have ever stumbled across. It’s a defense system that has existed in bacteria for millions of years and it may some day let us change the course of human evolution.
Out drinking with a few biologists, Jad finds out about something called CRISPR. No, it’s not a robot or the latest dating app, it’s a method for genetic manipulation that is rewriting the way we change DNA. Scientists say they’ll someday be able to use CRISPR to fight cancer and maybe even bring animals back from the dead. Or, pretty much do whatever you want. Jad and Robert delve into how CRISPR does what it does, and consider whether we should be worried about a future full of flying pigs, or the simple fact that scientists have now used CRISPR to tweak the genes of human embryos.

Dominic Basulto, The Washington Post, The Big Trends in Synthetic Biology You Need to Know, here. DARPA is in so there is money. Give the Dorian Gray Face Cream to our Troops.

Both public sector agencies and private sector investors are pouring new money into the synthetic biology space, and that’s leading to a situation where we can expect a burst of new innovations impacting fields as diverse as agriculture, energy and health. According to the latest “U.S. Trends in Synthetic Biology Research Funding” report from the Wilson Center’s Synthetic Biology Project in Washington, D.C., the U.S. government funded more than $820 million in synthetic biology research programs in the period from 2008-2014.

In the public sector, the role of innovation giant DARPA in funding synthetic biology projects has exploded, eclipsing the role of other prominent U.S. government agencies that fund synthetic biology programs, such as the National Science Foundation (NSF), National Institutes of Health (NIH), and the USDA. In 2014 alone, DARPA funded $100 million in programs, more than three times the amount funded by the NSF, marking a fast ramp-up from a level of zero in 2010.

Given the innovation leadership role that DARPA has played in everything from self-driving cars and robots to the development of the Internet, it’s definitely worth keeping an eye on what DARPA is doing in the field of synthetic biology. Through initiatives such as its Living Foundries program, DARPA seeks to facilitate the creation of a manufacturing platform for living organisms. At the end of September, DARPA awarded an MIT synthetic biology lab, the Broad Institute Foundry, a $32 million contract for designing and manufacturing DNA.

The TPA Story, here. Steal the Best, here . There are probably still good guys around who can reverse engineer stuff. Ken Regan’s chess move sniffer seems relevant as well, here. How much of the output do you really need to understand profoundly to make progress? Maybe not so much. If you are given a PDP10 running supersonic flow past a wing simulation code and your job is to reverse the OS, you don’t really  need to know fluid dynamics like Garabedian, right? Maybe  reversing cell division is more like reversing the PCB/OS on the other side of the Iron Curtain in the 80s?

The name TPA refers to the term “Stored-program Analyser”, and the story behind this is similar to that behind Digital’s “PDP”. In the ’60s the Central Comitee of the Hungarian Communists Party ruled that all computer development in Hungary should be frozen and that computers should be purchased from the USSR. Noone was allowed to construct computers, so engineers at the Research Insitute for Measurement and Computing Techniques of the KFKI (Central Research Institute for Physics) decided to build “analysers”. This rule was later repealed, but the name “TPA” stayed.

The TPA-project lasted from 1968 to 1989 (although the name “TPA” lived until 1992), 1435 computers were sold during this time. Although the TPAs are often labelled als mere “clones”, it is important to point out, that most of them weren’t photocopies: 1215 were designed from scratch (most of them was designated to be compatible with something, these were re-implementations), 105 were “card-by-card” clones, and 115 were systems based on original processors (like the TPA11/510, which is a MicroVAX II; this was in the late eighties, when the TPAs were sort of “unofficial OEMs”).

Dang et.al., Practical Reverse Engineering: x86, x64, ARM, Windows Kernel, Reversing Tools, and Obfuscation, here. it’s like that old Dodgeball clip, here, if you can reverse an x86, you can reverse a Biosphere. One basic question – assume DNA is divided into code and data, can you determine which bases are code and which are data? Obviously if cells are keeping viral DNA sequences between log markers then the Viral DNA sequences are data not code, right?

Reverse engineering is the process of analyzing hardware or software and understanding it, without having access to the source code or design documents. Hackers are able to reverse engineer systems and exploit what they find with scary results. Now the good guys can use the same tools to thwart these threats. Practical Reverse Engineering goes under the hood of reverse engineering for security analysts, security engineers, and system programmers, so they can learn how to use these same processes to stop hackers in their tracks.

The book covers x86, x64, and ARM (the first book to cover all three); Windows kernel-mode code rootkits and drivers; virtual machine protection techniques; and much more. Best of all, it offers a systematic approach to the material, with plenty of hands-on exercises and real-world examples.

Offers a systematic approach to understanding reverse engineering, with hands-on exercises and real-world examples
Covers x86, x64, and advanced RISC machine (ARM) architectures as well as deobfuscation and virtual machine protection techniques
Provides special coverage of Windows kernel-mode code (rootkits/drivers), a topic not often covered elsewhere, and explains how to analyze drivers step by step
Demystifies topics that have a steep learning curve
Includes a bonus chapter on reverse engineering tools

Landenmark, et.al., An Estimate of the Total DNA in the Biosphere, here. Oh, less than 10 ^32 megabase pairs, so limit the linear table scans, right? Lots of base sequences, but I bet you can get statistical characterizations of the sequences. The code is certainly not going to be random. I doubt the data is even very random. There is no way these are anything remotely like 10^32 random mega base strings. They are going to be massively compressible once you figure out the distribution.  Probably need to figure out what the natural error correcting codes are and how sophisticated they are. Would be nice to prove there is no predetermined word size or find the set of standard sequence sizes. Ditto it would be useful if these programs can count  – they must be able to since they have logs. Is there a zero offset in the code?  Probably there has to be, right? Can they dereference pointers? detect overflow? bounds checking? temp memory ? I’m thinking you have a chance to do the Bloomberg Terminal for Reverse Engineering the Biosphere. It’s a web site that would contain the cell division process spec sheets as currently known. Pick some undergrad like Jeff Bezos or Brian O’Kelley and make them the kid/hero for the Sorkin movie.

Using information on the typical mass per cell for each domain and group and the genome size, we estimate the total amount of DNA in the biosphere to be 5.3 × 1031 (±3.6 × 1031) megabase pairs (Mb) (Table 1). This quantity corresponds to approximately 5 × 1010 tonnes of DNA, assuming that 978 Mb of DNA is equivalent to one picogram [3]. Assuming the commonly used density for DNA of 1.7 g/cm3, then this DNA is equivalent to the volume of approximately 1 billion standard (6.1 × 2.44 × 2.44 m) shipping containers. The DNA is incorporated within approximately 2 × 1012 tonnes of biomass and approximately 5 × 1030 living cells, the latter dominated by prokaryotes. By analogy, it would require 1021 computers with the mean storage capacity of the world’s four most powerful supercomputers (Tianhe-2, Titan, Sequoia, and K computer) to store this information [4]. The methodological approach is summarised in Box 1, and detail is provided in S1 Methods.

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