anonmeow

It's more straightforward to tax snapchats and facebooks some more and put the money into cancer research.

Looks like I hit a nerve here, haven't I?

Note that my advice is rational and completely unironic. It is rational to follow the clique if you want to succeed in tech.

I act like that too.

Just having a 'compiler' will not change much about that understanding

The compiler is called "genetic engineering" and it's a 30 years old field. In particular genetic engineering allows you to knockout specific genes and observe the phenotype. This technique is commonly used on bacteria, plants and animals. There is an ongoing mouse knockout project, an attempt to study every mouse gene by turning it off. It is 50% complete so far. By the way, the experiments are performed mostly by hand.

We're very far away from understanding how a particular DNA string relates to phenotypes.

This problem can be solved much faster with a large scale effort. Thousands of automated experiments can run in parallel while recording the phenotype of the animals (including results of behavioral tests) and storing it for later analysis. On this genotype->phenotype dataset one can train an ML model. Actually there is a company that is trying this approach (just ML part, without automated experiments) http://www.deepgenomics.com/

I doubt that one company will be enough, though. With serious funding there could be much more progress in this area. We could have a full knockout map of mouse genome in less than a decade if we really wanted.

It may not be the solution you expected, but you could try upwork. Pay can be decent and it allows you to live while traveling across exotic countries. I know a programmer that lives this digital nomad lifestyle.

To use the YC/dev culture to your advantage you have to play your cards in a smart way. Make yourself a name (make a cool html5 website promoting yourself as a professional). Make trendy silly things in javascript, post 'em to github, to show HN. Get upvoted. Comment, gather karma. Don't show your depressive attitude to people, it turns them off (because it reminds them about their privilege of being born into a wealthy country).

Basically read this guy http://www.kalzumeus.com/2011/10/28/dont-call-yourself-a-pro... and follow the clique.

You can make it if you try hard enough.

Sadly, skills won't make any difference if you don't meet requirements for visa. You could take your time and get relevant degree though (anything CS related should work).

Also you can play DV lottery. It's a small chance (1.5%) but still larger than zero.

Start with researching visa laws. H1B is a very common way to come into US for work. EU has alternatives. Note that these visa require BS degree. As to what to write in your resume there are much better guides online than anything I'd say.

The Moore's law has ended (doubling time has become longer than 2 years, and looks like 10nm-7nm will be the last manufacturing process for a long time). From now on we will see more special-purpose hardware.

The same could be said about startups.

When the civilization is confined to one small planet while hitting the physical limits to growth, the fixed pie is a good analogy.

There is fixed and diminishing amount of arable land to grow the wheat and apples. You can make only so many pies.

Server CPUs have >2x memory channels when compared to consumer CPUs. IBM Power CPUs show that it's possible to get even more memory bandwidth than in mainstream Xeons. Looks like low RAM bandwidth in consumer CPUs is a mostly artificial differentiator to discourage use of these parts in servers.

On the other hand there are HMC and HBM technologies that offer order of magnitude more bandwidth and several times less latency. They are already used in AMD gpus as well as in prototypes of Nvidia's pascal gpu and Intel's Knight's corner 60-core cpu http://www.theplatform.net/2015/03/25/more-knights-landing-x...

I hope HBM comes to consumer CPUs too, but with current lack of competition in the market it can take a long time.

If the PR is good this could create a positive public attitude towards life extension. You'd get more funding in the end.

If governments and FDAs of the developed world were more cooperative it wouldn't happen this way. Startups don't have a billion dollars for FDA trials.

There is a quite large database of genes that affect aging in model organisms: http://genomics.senescence.info/genes/stats.php In this database there are 126 mouse genes.

It looks like (science funding) politics is the only reason we are not testing how these genes work in large mammals and primates. The public is scared of genetic engineering.

In fact, there’s actually no such thing as big science; we should really be calling it big engineering.

This is so true. Engineering is undervalued in comparison to science. It's easier to sell multi-billion project to the general public if you label it as science. Scientists are much more publicly visible than engineers; they are Nobel winners, geniuses, brilliant men single-handedly unraveling mysteries of the universe (or so it seems to the layman). Engineers generally work in larger teams, don't seek individual fame, don't receive their Nobel prize.

And yet our lives depend upon the quality of engineers' work on a daily basis. Our largest global problems (climate, energy, pollution) are engineering problems. Shouldn't we praise engineers more?

It's a really, really, really big sea of possibilities nowadays for developers.

If you are in the silicon valley or at least in some 1st world country - sure, you have a lot of possibilities and ridiculously high pay. The sad truth is that exactly same skillset can be valued 10x less or 10x more depending on your location.

You can 3d print a relatively decent actuated humanoid arm: http://www.thingiverse.com/search/page:1?q=inmoov&sa= looks quite disruptive compared to your average web-mobile-whatever intangible.

The Diamond Age is a great book. Neal Stephenson is known for researching concepts he writes about, so the technology present in the setting is based on Drexler's thesis.

I wouldn't call it "a dream" in a sense that it's utterly unrealistic; physics says that these systems can work.

If someone is interested in real technical description of molecular manufacturing, you may read Eric Drexler's "Nanosystems: Molecular Machinery, Manufacturing and Computation". Most parts of this book can be read on the author's website http://e-drexler.com/d/06/00/Nanosystems/toc.html , and if you know how to google you can find the whole book.

The book contains a careful physical analysis of molecular machines. The technical material is unchallenged to the present day.

The ribosome, DNA replication complex and ATP-synthase (and other complex enzymes) qualify as precise molecular manufacturing, if you relax the definition a little. Ribosomes are already being engineered, see expanded genetic code.

How far could we go by modifying existing biological molecular machines? Probably quite far.

It is entirely possible http://www.youtube.com/watch?v=gy5g33S0Gzo , but there is no market for a domestic robot. Not even for an AiBo.

You see: poor people are accustomed to doing these chores by themselves, while the rich can always use their paper money to hire naturally occurring biological robots.

Given enough data and a good model (recurrent neural network can model arbitrary algorithms, for example) you can learn algorithmic regularities in data, including learning itself. There is a paper just about that: http://link.springer.com/chapter/10.1007%2F3-540-44668-0_13#...

If this can be scaled to human-like learning remains to be seen, but training a conversation RNN model that remembers some details of past conversations and acts on them should be possible.

Small volume of mouse cortex is already successfully scanned at 3x3x20nm voxel resolution, with smallest synaptic details being visible http://www.cell.com/abstract/S0092-8674(15)00824-7 The tool is called ATLUM. The process could be scaled up.

If you want a hard science-fiction novel about digital humans you could read Greg Egan's Permutation City, it's a masterpiece.

If someone can pay for these computing resources, why shouldn't he do it? Also there is no physical law that forbids cheap brain-scale computing. 1 exaflops could easily fit in less than 1 cm^3, given sufficiently advanced logic technology.

They should just call it copying/copies. The prospect of having your copy managing your assets could be desirable, for example.

Because brain is a highly nonlinear system, and these are hard to model. You cannot model every metabolic process in every neuron and astrocyte, you have to take computational shortcuts and use approximations. These approximations may have severe global effects.

To demonstrate the nonlinearity of these models there was an experiment http://www.pnas.org/content/105/9/3593.full where researchers excluded a single spike from the large scale brain simulation. The global state of simulation has diverged after 100 timesteps, compared to the version where this spike was present.

With modern ML techniques it looks feasible to recreate at least online behavior of an individual - facebook likes, comments etc. The datasets are here, in facebook/google datcenters, and DL models are already used to model conversation. It would be interesting to know just how many megabytes of logs of your online activities is really necessary to extrapolate your behavior into the future.

Facebook AI research is probably playing with such models right now.

This age won't come anytime soon in a world where hundreds of billions $ of capital are thrown into social-media-mobile-app economy.

Enjoy your capitalism where people working in advertising and meaningless app businesses get huge sums of money while phd postdocs researching molecular biology (which is necessary to at least have a chance of finding a cure for cancer) are getting by on their 60000$.

You, dear reader, probably hope that you will make enough money off your trendy webapp business and will get the best medicine when the time comes, but you probably won't. This man's fate awaits you.