Of course we do. It's also a must. It's a requirement for any progress related to space travel and in relation to populating other planets. It's amazing that this is and still is, a question. The real question here is - does life have meaning or not?
Very true. Most of it has to do with coding that involves prediction, statistical analysis, vector similarity and other experimental techniques that involve approaches outside the box of formal methods encapsulated in off-the-shelf libraries.
It is about looking at mortality as some kind of disease and not a common thing that happens to all living beings.
As a human, I am afraid of death as the most of us. I like to toy with the idea living forever, or at least hundreds of years...
But looking at our society now. As the average lifespan getting higher, more people stay in jobs longer as usual. The young wont have any jobs, because their parent will stay in the positions. In the end the old would have to sustain the young and soon after that, no one would want to have a child, because who needs another hungry mouth.
Of course as the 1st world country citizens will afford living a longer life, 2nd and 3rd ones wont.
This will create a massive gap between nations. Like we didn't have that already.
And we don't know how the human mind could handle this anyway. Maybe you would go actually mad after 200 years of living.
And as I said. The extra years always add up to the end. Maybe you live 200 years, but 2/3 of that is spent being old and useless.
As highly appreciated and acknowledged people warn us about the ramifications of A.I., so we should be extremely cautious about banning death.
To be honest I would be less afraid of A.I. as the consequences of immortality.
Choose your poison, however, living long enough to fight for a chance to change, defeat or restructure that poison, in whatever form it comes, is what I choose. Choice B) does not give you that option unless it's your understanding that:
C) There is another option
D) Choice A) will someday positively impact the reanimation of those who've selected Choice B).
It is good to have someone living as long as possible who actually wants to make the world a better place.
But, we all know who will be the ones actually benefiting from this.
The ones who don't give a rats ass about anything, only selfishly living longer just to make more money, have more power. Hoarders who are rather a disease for humanity then being useful.
In an ideal world it would be a fantastic thing. But we aren't living in one. We can try, but unless 90% of humanity stops acting like a maniac, it will divide humanity on another level.
We can't cope with the fact properly, if our neighbour has a bigger car then ours. Imagine how people would cope with the fact, that some of us can live for hundreds of years.
Immortality is a nice thing, but not until the minds are cleared, poverty, hunger, closed mindedness, are banished and humanity as a whole can act and decide without having constant internal struggles.
Just look at the idiots who are against vaccinations, religious nut-jobs, greedy, selfish, maniac, egocentric, etc...
All the beautiful traits of humanity. Do you want to give those power to live long, or maybe forever?
Would you prevent new generation to blossom and create something new, by selfishly clinging to life and not letting go to give way for the change? It is a common thing that the older you are, the less you can change, or keep up with trends. And this is not only about are ageing bodies. We might have the risk to stop evolving. To stop innovating, exploring, etc...
I advise to you to read "2br02b" from Kurt Vonnegut. A short story about our society perfecting immortality. It is very interesting.
And to answer your question. I would probably choose 'A', even if I fear that it will have a very negative impact on humanity.
Do you have any information on their current status and their biggest issues/blockers?
What I'm wondering about the different approaches is if they could receive bigger breakthroughs by sharing / crowdsourcing their issues and getting a wider attraction / reach. E.g. sometimes the answers to a problem lie in another industry
Like e.g. the fold.it game helped decyphering the crystal structure of an AIDS causing virus in 10 days, while scientists were battling it for 15 years
- Inner-workings of Mitochondria and cell death/apoptosis at the wrong time.
- DNA repair genes
- Telomerase production/use
Analyzing genomic pathways associated to these is key. Understanding why the expression of genes varies or decreases/increases at the wrong time is also key.
Being able to use Cogntive computing/biomicry/AI/Machine Learning etc to analyze the hidden connections and relationships between phytochemicals, genes, proteins, pathways and environment is the next frontier.
We're working on it and could certainly use additional crowdsourcing approaches.
Do you have any specific ideas of a massive road-block that would benefit from a Mechanical Turk approach? E.g. issues that would require an AI, but if split into a lot of tiny problems, that could be solved as a whole?
I've been giving this some thought and have some ideas on a few directions we can go in. For example, cognitive biomimicry/AI can be trained to predict certain things like answering "What is the capitol of Austria?"
With statistical inference and probability, a system can provide a number of answers to questions. A crowdsourcing component can be used to rate the answers the system provides thereby allowing the system to learn via feedback loops.
Apply this to Life Sciences, molecular biology, genomics/proteomics and we may have a system intelligent enough to produce new hypothesis in the area of life extension research or a system intelligent enough to combine two pieces of knowledge to come up with something new, a discovery or series of discoveries.
I have some other ideas too, look me up at biomimic@gmail.com if you want to collaborate on these.
Yes, I can discuss the underlying technology. Much of it is based on building large vectors similar to word2vec but much more exhaustive in terms of rich, scored and ranked vectors. Comparing vectors for similarity is almost as important as how one constructs the vectors in vector space. Mimicking the way a human might manually construct a vector remains key.
Relying on vector similarity as opposed to direct keyword matches is an approach that's taken. Utilizing statistical and probabilistic approaches as opposed to "words and rules" remains important.
The corpus is currently just limited Reuters public company profiles & descriptions but I plan to include SEC filings as well.
Traders, investors, hedge funds can engage is quick information arbitrage with it. For example, a stock runs up 20% in minute, you insert a keyword or the symbol related to the stock that ran up, you then get other stocks (a targeted basket) that have sympathetic, symbiotic and parasitic relationships before any research analyst can uncover the connections - rising tide lifts all boats or a lowering tide lowers them. Ref: "Contagious Speculation and a Cure for Cancer: A Non-Event that Made Stock Prices Soar" -http://www0.gsb.columbia.edu/whoswho/getpub.cfm?pub=1555
The system can include tiered consumer/trader/investor subscriptions, licensing and net profit sharing with selected hedge funds. SeekingAlpha, StockTwits, Yahoo Finance etc as revenue partners. We're raising a bit of funding in the meantime while we also use it as a trading tool ourselves.
It's a prototype that's being moved into production this week or next.
Thanks for the additional info. Its always fun to hear a little of the back story when people are willing/able to share.
I have built both prototypes and production systems using a couple of different approaches to text analysis. Its always fun to hear a little of the back story when people are willing to share.
I wish you all the best in converting it into a solid business.
Extremely nice implementation and very good explanation of its use case. What would be interesting in the future once you're at the marketing stage would be to run through an example using historical data to provide me with an indication of my returns.
Thanks and I agree that historical performance metrics would be a great indication of returns.
What I'd like to do would be to create a system that processes 5 years worth of historical data, gathers all symbols that have had spikes up or down by 10-75%, have good volume and liquidity and are affected by either news or an earnings report. I could then auto-construct the baskets that surround each issue and calculate returns on the long side or short side.
I like this system because it executes on 4 critical levels:
1. Works in a good market or in a bad market due to short and long positioning that can be taken whereas most trading systems (and Technical Analysis) only really work in good markets.
2. You don't have to be late in terms of buying into (or shorting) the direct issue. You buy into or short the indirect issues, which enable protection and diversification.
3. Nobody really is doing this today.
4. It's based on information arbitrage and hidden connections, not numbers.
When trading real money in a real market, predictions based on historical data go out the window.
Historical data will never be able to truly simulate manipulation or sympathetic, symbiotic or parasitic relationships. Ever back-test a trading system that simulates a Market Maker letting low block go under the bid or dialing down the sensitivity of the bid vs. the ask? Speaking from experience.
That's why I'm developing an algorithmic trading system based on sympathetic, symbiotic and parasitic hidden connections.
"When trading real money in a real market, predictions based on historical data go out the window." No they don't. Depends on the style of course but most arb or stat arb strategies are fully derived from historical data.
"Ever back-test a trading system that simulates a Market Maker letting low block go under the bid or dialing down the sensitivity of the bid vs. the ask" Could you express this more clearly? Your language is sloppy. Yes I've back tested lots of market making strategies - all far more complex in behavior than traditional market making.
If you think there is any insight into current market structure in that linked article, you're on the wrong track. It manages to be 15 years out of date and confuse open outcry (pit trading) with the specialist/broker system employed for equities.
And there's nothing magic about simulating "manipulation" - you're not one of those deranged paranoid zerohedge balloonheads are you?
And it's clear you have no experience in this area if you say something as trite as your last sentence.
Technologies: Data Science, Artificial Intelligence, Cognitive Computing, Machine Learning, Predictive Analytics, Partnership & Business Development, Sales & Marketing, Software Engineering, Algorithm Optimization and development. Working on data classification and pattern matching algorithms. Initial work involves an advanced context-controllable content summarization systems including - http://genopharmix.com/TuataraSum/index-156.html - http://genopharmix.com and http://www.genopharmix.com/TuataraSum/medium/medium_summary_.... - additional applications in Finance, Trading/Investing, Recommendation Systems and related.
