Jaunumi

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Cybernetics is not just another branch of science. It is an intellectual revolution that rivals in importance the earlier Industrial Revolution.

Isacc Asimov, 1950

 

Open Problems in Artificial Life

Mark A. Bedau¤;†, John S. McCaskill‡, Norman H. Packard§, Steen Rasmussen¤¤, Chris Adami††, David G. Green‡‡, Takashi Ikegami§§, Kunihiko Kaneko¤¤¤, Thomas S. Ray†††

Abstract    This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated.

A List of Open Problems

A. How does life arise from the nonliving?
1. Generate a molecular proto-organism in vitro.
2. Achieve the transition to life in an artificial chemistry in silico.
3. Determine whether fundamentally novel living organizations can exist.
4. Simulate a unicellular organism over its entire lifecycle.
5. Explain how rules and symbols are generated from physical dynamics in
living systems.

B. What are the potentials and limits of living systems?
6. Determine what is inevitable in the open-ended evolution of life.
7. Determine minimal conditions for evolutionary transitions from specific to
generic response systems.
8. Create a formal framework for synthesizing dynamical hierarchies at all scales.
9. Determine the predictability of evolutionary consequences of manipulating
organisms and ecosystems.
10. Develop a theory of information processing, information flow, and
information generation for evolving systems.


C. How is life related to mind, machines, and culture?
11. Demonstrate the emergence of intelligence and mind in an artificial living
system.
12. Evaluate the influence of machines on the next major evolutionary transition
of life.
13. Provide a quantitative model of the interplay between cultural and biological
evolution.
14. Establish ethical principles for artificial life.

Mark A. Bedau is an American philosopher who works in the field of Artificial Life. He is the son of philosopher Hugo Adam Bedau.

Bedau teaches philosophy at Reed College. He is also the Co-Founder of the European Center for Living Technology (ECLT)[1] and Visiting Professor, Ph.D. Program in Life Sciences: Foundations and Ethics, European School of Molecular Medicine.[2] Bedau is also the editor of the Artificial Life Journal.[3]  He has been the COO of Protolife, a biotechnology start-up based in Venice, Italy.

Rakstā uzskaitītas mākslīgās dzīvības problēmas, bet tas, kas katrā nozarē ir zināms un paveikts, nav atdalīts no tā, kas vēl nav zināms. Piemēram, informācijas jaunrade bioloģiskajās būtnēs (10.punkts) ir zināma, izprasta un aprakstīta daudzās publikācijās.  Bet mēs vienmēr varam teikt, ka vēl viss nav izpētīts un vajaga pētīt vēl. 

 

EmTech: Get Ready for a New Human Species

Now that we can rewrite the code of life, Darwinian evolution can't stop us, says investor Juan Enriquez., Wednesday, October 19, 2011By Emily Singer

The ability to engineer life is going to spark a revolution that will dwarf the industrial and digital revolutions, says Juan Enriquez, a writer, investor, and managing director of Excel Venture Management. Thanks to new genomics technologies, scientists have not only been able to read organisms' genomes faster than ever before, they can also write increasingly complex changes into those genomes, creating organisms with new capabilities.  

Enriquez, who spoke at Technology Review's EmTech conference on Tuesday, says our newfound ability to write the code of life will profoundly change the world as we know it. Because we can engineer our environment and ourselves, humanity is moving beyond the constraints of Darwinian evolution. The result, he says, may be an entirely new species.

Enriquez is the author of the global bestseller As the Future Catches You: How Genomics & Other Forces Are Changing Your Life, Work, Health & Wealth. His most recent publication is an eBook, Homo Evolutis: A Short Tour of Our New Species.

Technology Review senior editor Emily Singer spoke with Enriquez after his talk.

TR: Why do you think there is going to be a new human species?

Juan Enriquez: The new human species is one that begins to engineer the evolution of viruses, plants, animals, and itself. As we do that, Darwin's rules get significantly bent, and sometimes even broken. By taking direct and deliberate control over our evolution, we are living in a world where we are modifying stuff according to our desires.

If you turned off the electricity in the United States, you would see millions of people die quickly, because they wouldn't have asthma medications, respirators, insulin, a whole host of things we invented to prevent people from dying. Eventually, we get to the point where evolution is guided by what we're engineering. That's a big deal. Today's plastic surgery is going to seem tame compared to what's coming.

How is this impending revolution going to shape the world?

Ninety-eight percent of data transmitted today is in a language almost no one spoke 30 years ago. We're in a similar period now. But this revolution will be more widespread because this is software that writes its own hardware.

People think this technology will just change pharma or biotech, but it's much bigger than that. For example, it's already changing the chemical industry. Forty percent of Dupont's earnings today come from the life sciences. It's going to change everything; it will change countries, who's rich and who's poor. It's going to create new ethics.

New ethics?

It will change even basic questions like sex. There used to be one way to have a baby. Now there are at least 17. We have decoupled sex from time. You can have a baby in nine months, or you can freeze sperm or a fertilized egg and implant it in 10 years or 100 years. You can create an animal from one of its cells. You can begin to alter reproductive cells. By the time you put this together, you've fundamentally changed how you reproduce and the rules for reproduction.

What does it take to make a new species?

We're beginning to see that it's an accumulation of small changes. Scientists have recently been able to compare the genomes of Neandertals and modern humans, which reveals just a .004 percent difference. Most of those changes lie in genes involved in sperm, testes, smell, and skin.

Engineering microbes alone might speciate us. When you apply sequencing technology to the microbes inhabiting the human body, it turns out to be fascinating. All of us are symbionts; we have 1,000 times more microbial cells in our bodies than human cells. You couldn't possible digest or live without the microbial cells inside your stomach. Some people have microbes that are better at absorbing calories. Diabetics have a slightly sweeter skin, which changes the microbial fauna and makes it harder for them to cauterize wounds.

One concern about human enhancement is that only some people will have access, creating an even greater economic divide. Do you think this will be the case?

In the industrial revolution, it took a lifetime to build enough industry to double the wealth of a country. In the knowledge revolution, you can build billion-dollar companies with 20 people very quickly. The implication is that you can double the wealth of a country very quickly. In Korea in 1975, people had one-fifth of the income of Mexicans, and today they have five times more. Even the poorest places can generate wealth quickly. You see this in Bangalore, China. On the flip side, you can also become irrelevant very quickly.

Scientists are on the verge of sequencing 10,000 human genomes. You point out this might highlight significant variation among our species, and that this requires some ethical consideration. Why?

The issue of [genetic variation] is a really uncomfortable question, one that for good reason, we have been avoiding since the 1930s and '40s. A lot of the research behind the eugenics movement came out of elite universities in the U.S. It was disastrously misapplied. But you do have to ask, if there are fundamental differences in species like dogs and horses and birds, is it true that there are no significant differences between humans? We are going to have an answer to that question very quickly. If we do, we need to think through an ethical, moral framework to think about questions that go way beyond science.

Avots: http://www.technologyreview.com/biomedicine/38932/?nlid=nldly&nld=2011-10-19

 

Researchers Mimic Nature to Create a 'Bio-Inspired Brain' for Robots

ScienceDaily (July 27, 2011) — A group of engineers at NUI Galway and the University of Ulster is developing bio-inspired integrated circuit technology which mimics the neuron structure and operation of the brain. One key goal of the research is the application of the electronic neural device, called a hardware spiking neural network, to the control of autonomous robots which can operate independently in remote, unsupervised environments, such as remote search and rescue applications, and in space exploration.

One key goal of the research is the application of the electronic neural device, called a hardware spiking neural network, to the control of autonomous robots which can operate independently in remote, unsupervised environments, such as remote search and rescue applications, and in space exploration.

According to Dr Fearghal Morgan, Director of the Bio-Inspired Electronics and Reconfigurable Computing (BIRC) research group, at NUI Galway: "Electronic neurons, implemented using silicon integrated circuit technology, cannot exactly replicate the complexity of neurons found in the human brain, or the massive number of connections between neurons.

"However, inspired by the operation and structure of the brain, we have successfully developed a hardware spiking neural network and have used this device for robotics control. The electronic device interprets the state of the robot's environment through signals received from sensing devices such as cameras and ultrasonic sensors, which act as the eyes and ears of the robot.

"The neural network then modifies the behaviour of the robot accordingly, by sending signals to the robot's limbs to enable activity such as walking, grasping and obstacle avoidance." Dr Morgan explains: "Our research is focussed on mimicking evolution in nature. The latest hardware neural network currently in development will contain thousands of small electronic neuron-like devices which interoperate concurrently, in a similar way to neurons in the biological brain. The device can be trained to perform a particular function, and can be retrained many times for various applications.

"The training process resembles the training of the brain, by making, strengthening and weakening the links between neurons and defining the conditions which cause a neuron to fire, sending signals to all of the attached neurons. As in the brain, the collection of interconnected neurons makes decisions on incoming data to cause an action in the controlled system.

"Until now, the robotics arena has focused on electronic controllers which incorporate one or more microprocessors, which typically execute instructions in sequence and, while performing tasks quickly, are limited by the instruction processing speed. Power is also a consideration. While the human brain on average only requires 10 watts of power, a typical PC requires 300 watts.

"We believe that a small embedded hardware neural network device has the potential to perform effective robotics control, at low power, while also incorporating fault detection and self-repair behaviour. Our aim is to develop a robust, intelligent hardware neural network robotics controller which can autonomously maintain robot behaviour, even when its environment changes or a fault occurs within the robotics system."

Dr Jim Harkin, from the School of Computing and Intelligent Systems at the University of Ulster's Magee campus), said: "The constant miniaturisation of silicon technology to increase performance introduces inherent reliability issues which must be overcome. Ultimately, the hardware neural network or robot 'brain' will be able to detect and overcome electronic faults that occur within itself, and continue to function effectively without human intervention."

 

 

Konkursi

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„Mākslīgā intelekta fonda” rīkotajā konkursā visvairāk godalgu saņem Latvijas Universitātes studenti

Ir noslēdzies „Mākslīga intelekta fonda” rīkotais konkurss studentiem, kura ietvaros dalībniekiem bija jāuzraksta sacerējums, jāatrisina uzdevumi vai jānoformulē precīza oriģināla ideja vai algoritms par piedāvātajām tēmām. Visvairāk godalgas saņēma Latvijas Universitātes (LU) studenti.

Zinātnisko darbu konkursā pirmās godalgas saņēma Kaspars Balodis (LU) par darbu “Varbūtiskā reducējamība” un Kārlis Dimza (National Tsing Hua University,Taivāna) un Linda Gulbe (Ventspils Augstskola) par darbu “ Kādus uzdevumus cilvēks joprojām risina labāk nekā dators?”. Trešā godalga piešķirta Aleksandram Tarvidam (LU) par darbu “Sarežģītu adaptīvu sistēmu modelēšana ar aģentu tehnoloģiju”. Atzinības rakstus piešķīra Jeļenai Fjodorovai (LU) par darbu “Kā dators var atjaunot programmas tekstu pēc ieejas-izejas datu piemēriem”, Raitim Ozolam (LU) par darbu “Uzdevumi, kurus cilvēks joprojām risina labāk nekā dators” un Oļegam Verhodubam (RTU) par darbu „Kā veidot iespējami pilnvērtīgu abstraktu interaktīvu vidi, kurā mākslīgās evolūcijas ceļā attīstīt digitālus subjektus ar intelekta pazīmēm?”.

Paaugstinātas grūtības uzdevumu risināšanas konkursā pirmās godalgas saņēma Artūrs Bačkurs (LU), Juris Čerņenoks (LU), Dmitrijs Logvinovs (LU). Otrās godalgas piešķirtas Andreasam Šulcam (LU) un Aleksandram Tarvidam (LU), savukārt, atzinības rakstu saņēma Ginta Garkāje (LU).

„”Mākslīgā intelekta fonda” mērķis ir veicināt Latvijas zinātnes, izglītības un ražošanas attīstību un paaugstināt Latvijas valsts konkurētspēju datorzinātņu, robotikas, mākslīgā intelekta un ar to saistīto inovāciju jomā. Fonda mērķis ir sniegt nozīmīgu labumu sabiedrībai, attīstot zinātni un veicinot izglītību ar fonda darbību saistītajās jomās. Šī konkursa galvenie mērķi bija rosināt studentus un topošos studentus domāt un strādāt pie konkursa uzdevumā formulētajām tēmām, atklāt un iepazīt talantīgus studentus, kas būtu ieinteresēti turpināt darbu mākslīgā intelekta jomā, uzzināt jaunas, interesantas idejas un ieraudzīt pētāmās tēmas svaigā, neparastā skatījumā,” par Mākslīgā intelekta fondu un konkursu stāsta fonda vadītājs Einars Repše.

Par konkursa nozīmīgumu un mākslīga intelekta tēmas svarīgumu mūsdienās Mākslīgā intelekta fonda pētnieks Imants Vilks norāda: „Nosaukums 'mākslīgais intelekts' saka, ka pasaules zinātnieki mēģina izveidot cilvēkam līdzīgu intelektu atšķirīgā, ne-bioloģiskā vidē. Zinātnieku panākumi atsevišķu intelektuālu uzdevumu risināšanā (šahs, slimību diagnostika, tulkošana, informācijas meklēšana, kosmisko lidaparātu un militāru procesu vadība, cilvēku apmācības trenažieri) rāda, ka cilvēka intelekta spējas daudzās jomās ir pārspētas un tas notiks aizvien vairākās mūsu dzīves jomās. Varam sacīt, ka tā ir mūsu civilizācijas tuvāko desmitu gadu nākotne.  Šo netālās nākotnes uzdevumu risināšanai būs vajadzīgi speciālisti, kuru domāšanas pamatā ir nevis, kā raksta Havajas Universitātes kvantu fizikas profesors filosofijas doktors Viktors Stengers, pagājušo gadsimtu aizspriedumi un pirmatnējo cilšu ticējumi, bet mūsdienīgi priekšstati par cilvēka smadzeņu darbību, to informācijas apstrādes īpatnībām, problēmām un par to, kā šo darbību uzlabot. LU un „Mākslīgā intelekta fonda” rīkotā konkursa uzdevums bija aicināt jaunos speciālistus pievērsties šai interesantajai un cilvēces nākotnei svarīgajai nozarei.”

 

Konkursa labākie darbi.

A. Bačkurs, 8. tēma Paaugstinātas grūtības uzdevumi

A. Balodis, Varbūtiskā reducējamība

A. Šulcs, 8. tēma Paaugstinātas grūtības uzdevumi

A. Tarvids, 8. tēma Paaugstinātas grūtības uzdevumi

A. Tarvids, Sarežģītu adaptīvu sistēmu modelēšana ar aģentu tehnoloģiju

D. Logvinovs, 8.tēma Paaugstinātas grūtības uzdevumi

J. Čerņenoks, 8. tēma Paaugstinātas grūtības uzdevumi

K. Dimza, L. Gulbe, Kādus uzdevumus cilvēks joprojām risina labāk nekā dators?

Konkursa uzdevumi lasāmi 2.lapas beigās.

 

 

 

 

 

 

 

 

 

 

Raksti

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Par evolūciju viena indivīda ietvaros

Einars Repše, Māksīgā Intelekta fonds.

Spēlē „Dzīvība” (http://en.wikipedia.org/wiki/Conway's_Game_of_Life) lietotājs uzdod elementu sākuma konfigurāciju. Tālāk elementi pēc noteiktiem likumiem mijiedarbojas ar kaimiņu elementiem un vai nu „izdzīvo” un vairojas, vai „mirst”. Vikipēdijas attēls

Klasiski ar evolūciju saprot populācijas attīstību daudzās paaudzēs pēc principa – piemērotākais izdzīvo. Pazīstami arī koevolūcijas mehānismi, kur dažādas sugas paātrina viena otras evolūciju noteiktā virzienā, jo attīstās paralēli, vai nu konkurējot viena ar otru, vai sadarbojoties un izmantojot viena otras resursus. Tomēr, lai nu kā, bet evolūcija paredz daudzu paaudžu nomaiņu, līdz dabiskās atlases ceļā attīstās dzīvei piemērotāks indivīds.   Indivīda dzīves laikā iegūtās īpašības un prasmes parasti tiek asociētas ar apmācību un pieredzes gūšanu, nevis ar evolūciju tās klasiskajā izpratnē. Tomēr lietas nevar būt tik strikti nodalītas, gan analizējot tās no iemiesojošā subjekta puses, gan no sagaidāmā rezultāta puses.

Lasīt tālāk: http://www.lu.lv/terra2/raksti/t/6427/

 

 

Kā mākslīgās evolūcijas ceļā veidot dzīvas un domājošas struktūras uz datora.

Einars Repše, Māksīgā Intelekta fonds.

Vispirms jautāšu - vai jebkura nelineāru elementu sistēma spēj domāt, ja tos pietiekamā skaitā un pareizi savieno?

Intuitīvi šķiet, ka jā - gandrīz jebkura pietiekami sarežģīta nelineāru elementu sistēma spēj domāt, ja tos pietiekamā skaitā un pareizi savieno. Vienīgais, kas vēl varētu būt nepieciešams ir tīri lineāri signālu pastiprinātāji un invertori pareizās vietās. Jautājums par elementu detaļām varētu būt mazsvarīgs. Tas drīzāk līdzinās diskusijai par to kā labāk būvēt radiouztvērēju – no lampām, tranzistoriem vai diskrētiem loģiskiem elementiem. Savienojot lielā skaitā vienkāršus loģiskos elementus “un” un “ne” un dažas integrējošas palīgkomponentes, var panākt jebko, kas pa spēkam patvaļīgai analogai vai digitālai elektronikai. Vēl vairāk, viss dzīvais un nedzīvais mums apkārt ir uzbūvēts no ļoti primitīviem elementiem – elementārdaļiņām, atomiem, molekulām, šūnām un tā tālāk, no kurām diez vai kādam atsevišķam atomam, molekulai vai pat šūnai ir jebkāds priekšstats par kopējo veidojamo struktūru un tās “lielajiem” mērķiem un uzdevumiem. Un tomēr, tas viss kopā salikts strādā, pat ļoti labi strādā. Kāds zinātnieks ir teicis, ka dzīvība – tā ir ļoti vienkārša matērija, kas savienota ļoti interesantos veidos.

Līdz ar to, šķiet, ka priekšplānā izvirzās nevis kompleksas, potenciāli inteliģentas sistēmas atsevišķu elementu uzbūves jautājums, bet gan to pareizas savienošanas jautājums.

 Kā tieši savienot kādus nelineārus elementus, lai to veidotajā sistēmā spontāni veidotos jaunas, interesantas īpašības, to starpā intelekts?

 

Lasīt tālāk:

 http://www.lu.lv/terra2/raksti/t/7147/

 

 

Machines will achieve human-level intelligence in the 2028 to 2150 range

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Machines will achieve human-level intelligence in the 2028 to 2150 range: poll

April 26, 2011 by Editor
[+]

How similar will machine intelligence be to human intelligence? (credit: A. Sandberg & N. Bostrom/Future of Humanity Institute)

Machines will achieve human-level intelligence by 2028 (median estimate: 10% chance), by 2050 (median estimate: 50% chance), or by 2150 (median estimate: 90% chance), according to an informal poll at the Future of Humanity Institute (FHI) Winter Intelligence conference on machine intelligence in January.

“Human‐level machine intelligence, whether due to a de novo AGI (artificial general intelligence) or biologically inspired/emulated systems, has a macroscopic probability to occurring mid‐century,” the report authors, Dr. Anders Sandberg and Dr. Nick Bostrom, both researchers at FHI, found.

“This development is more likely to occur from a large organization than as a smaller project. The consequences might be potentially catastrophic, but there is great disagreement and uncertainty about this — radically positive outcomes are also possible.”

Other findings:

  • Industry, academia and the military are the types of organizations most likely to first develop a human‐level machine intelligence.
  • The response to “How positive or negative are the ultimate consequences of the creation of a human‐level (and beyond human‐level) machine intelligence likely to be?” were bimodal, with more weight given to extremely good and extremely bad outcomes.
  • Of the 32 responses to “How similar will the first human‐level machine intelligence be to the human brain?,” 8 thought “very biologically inspired machine intelligence” the most likely, 12 thought “brain‐inspired AGI” and 12 thought “entirely de novo AGI” was the most likely.
  • Most participants were only mildly confident of an eventual win by IBM’s Watson over human contestants in the “Jeopardy!” contest.
[+]

Probability density of human-level AI by date -- the blue represents skew Gaussian fits, the red represents triangular fits; previous dates are artifacts (credit: Anders Sandberg)

“This survey was merely an informal polling of an already self‐selected group, so the results should be taken with a large grain of salt,” the authors advise. “The small number of responses, the presence of visiting groups with presumably correlated views, the simple survey design and the limitations of the questionnaire all contribute to make this of limited reliability and validity.”

“While the validity is questionable, the results are consistent with earlier surveys,” Sandberg told KurzweilAI. “The kind of people who respond to this tend to think mid-century human-level AI is fairly plausible, with a tail towards the far future.Opinions on the overall effect were not divided but bimodal — it will likely be really good or really bad, not something in between.”

Brent Allsop, a Senior Software Engineer at 3M, has started a “Human Level AI Milestone?” Canonizer (consensus building open survey system) to encourage public participation in this interesting question in the survey: “Can you think of any milestone such that if it were ever reached you would expect human‐level machine intelligence to be developed within five years thereafter?”

Ref.: Sandberg, A. and Bostrom, N. (2011): Machine Intelligence Survey, Technical Report
#2011‐1, Future of Humanity Institute, Oxford University: pp. 1‐12. URL: www.fhi.ox.ac.uk/reports/2011‐1.pdf

Vairāk: http://www.kurzweilai.net/machines-will-achieve-human-level-intelligence-in-the-2028-to-2150-range-poll?utm_source=KurzweilAI+Weekly+Newsletter&utm_campaign=03d130a2a4-UA-946742-1&utm_medium=email

Par mums

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Lai veicinātu Latvijas zinātnes, izglītības un ražošanas attīstību un paaugstinātu Latvijas valsts konkurētspēju datorzinātņu, robotikas, mākslīgā intelekta un ar to saistīto inovāciju jomā, ir izveidots privāti finansēts Mākslīgā Intelekta fonds. Viens no tā mērķiem ir atbalstīt pētījumus, kas var novest pie modernu datorrīku izveides, kas palīdzētu Latvijā izveidot un nostiprināt uz zinātniskiem pamatiem balstītu rūpniecību atbilstošajā jomā.

Vairāk: skat. Par mums.

 

 

 

Phase change materials could be used to develop ‘brain-like’ computers

Unlike human brains that make no real distinction between memory and computation, computers currently deal with processing and memory separately. This means data has to be constantly moved around, resulting in a speed and power "bottleneck." Now, using phase change materials that can store and process information simultaneously, researchers at the University of Exeter in the UK have developed a new technique that could lead to the development of "brain-like" computers.

For their study, the researchers used a semi-conductor phase change material that they say exhibits remarkable properties. Not only did the study conclusively demonstrate that phase change materials can store and process information simultaneously. It also showed experimentally for the first time that they can perform general-purpose computing operations, such as addition, subtraction, multiplication and division.

Even more remarkable, the study showed that phase change materials could be used to make artificial neurons and synapses. This offers the prospect of an artificial system made entirely of phase change materials that could potentially learn and process information in a similar way to the human brain.

"Our findings have major implications for the development of entirely new forms of computing, including 'brain-like' computers. We have uncovered a technique for potentially developing new forms of 'brain-like' computer systems that could learn, adapt and change over time. This is something that researchers have been striving for over many years," says Professor David Wright of the University of Exeter and lead author of the study.

The paper, published in Advanced Materials, focused on the performance of a single phase change cell, but the next stage of the research will involve building a system of interconnected cells that can learn to perform simple tasks, such as the identification of certain objects and patterns.

Avots: http://www.gizmag.com/brain-like-computers-using-pcms/19036/

 

Mūsu laikmeta lielākā problēma

Viena no mūsu jaunatnes lielākajām problēmām ir derīgas informācijas iegūšana. Informācija - šis vārds mūsu sabiedrībā kļuvis populārs un tiek lietots vietā un nevietā. Sakaru nozarē par informāciju sauc derīgo signālu, bet nederīgo, traucējošo - par troksni. Informācijas atdalīšanu no trokšņa sauc par filtrēšanu.

Ja pirms 100 gadiem jaunā zinātkārā cilvēka vienīgā literatūra bija Lauksaimnieka kalendārs, žurnāls 'Atpūta', Kurts-Māleres romāni vai Bībele, par šodienu mēdz teikt, ka mēs dzīvojam informācijas pārbagātības laikmetā. Augstāk dotās definīcijas skatījumā tas tā nav: mēs dzīvojam trokšņa laikmetā. Signālu ir daudz, derīgas informācijas - aptuveni desmit reizes mazāk, un to grūti atrast.

"90% from published in science is trash". Stephen Hawking, The Universe in a Nutshell. (šī grāmata tulkota arī latviešu valodā - Universs rieksta čaumalā).

Daudzu jauno un zinātkāro cilvēku problēma šodien ir - kā atrast derīgas informācijas avotus. Šī interneta lapa dod lasītājam norādes, kur atrast materiālus, kurus lieto cilvēki, kas uzbūvēja datorus, mobilos tālruņus un kosmosa kuģus, izveidoja internetu un šodien strādā pie citām problēmām. Visa pamatā ir  viena prasība - mēs lietojam tikai to, ko var neierobežoti daudzas reizes pārbaudīt un pierādīt. Angliski to saka - everything based on scientific evidence.

Šajā interneta lapā mēs ievietosim ne tikai rakstus un domas par mākslīgo intelektu, bet norādes uz zināšanu avotiem, kas ir nepieciešami inteliģentas pasaules izpratnes un dzīves izveidošanai. Mēs atbalstām un atzīstam par pareizu zināšanu izplatīšanu par velti. Jo zināšanas ir visvērtīgākā cilvēka esības komponente, vienīgā, kas nodrošinās cilvēces izdzīvošanu lielā laika mērogā.

 

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