Norske politikere gjør sosiale medier til fluepapir for falske nyheter

Falske nyheter spres via sosiale medier som bl.a. Facebook for bl.a. å påvirke en politikk, politisk prosess eller demokratiske valg i en bestemt retning. Dette viser seg å fungere bedre enn hva de fleste trodde bare for en kort tid tilbake. 

Temmelig sikkert er at falske nyheter har hatt en påvirkning på 2016-valget i USA og kanskje også Brexit. Så hva er problemet her hjemme? Jo, det viser seg at flere og flere Nordmenn har droppet tradisjonelle medier til fordel for f.eks. Facebook fordi de da får alt på samme “plattform”, de kan oppdatere seg på vennegjengen og “samtidig” lese “nyheter”. Det er en voksende gruppe personer her hjemme som synes helt å ha glemt hvor regulert nyhetsformidlingen faktisk er i de fleset demokratier, inklusive i Norge hvor vi bl.a. har redaktør-ansvar og pressens faglige utvalg - dette for bl.a. å sikre kildekontroll.

Våre politkere og myndigheter har altså ulike “verktøy" for å begrense falske nyheter men ingen kontroll på falske nyheter publisert på internett som f.eks. Facebook eller andre sosiale medier - hvorfor vil de da at vi skal lese nyheter på Facebook? 

Norske polikere gjør nemlig akkurat det ved å publisere sine ytringer og politiske budskap på Facebook. Vi ser dette bl.a. når topp-politikere i Arbeiderpartiet gir sine ytringer på Facebook under Giske saken og #metoo kampanjen. Hvorfor gjør de dette? Vet de ikke bedre? Når skal Norske topp-politikere slutte å “legalisere” nyhetesformidling på Facebook og andre sosiale medier? Faktum er at de gjør Facebook til et fluepapir for falske nyheter når de ivrig for at deres tilhengere skal lese deres ytringer på Facebook og ikke i tradisjonelle Norske medier på papir eller internett.

Kan årsaken være at det haster så mye å få sine ytringer ut i media at de ikke kan vente til det Norske medie legger ut ytringene? Eller tror de at Norske medier ikke vil ta tak i deres ytringer? Neppe, jeg vil anbefale alle offentlige organisasjoner og personer til bare å bruke Facebook og andre sosiale medier til statisk informasjon som parktiske detaljer og hvordan de kan kontaktes og lignende. I tillegg kan de kanskje kjøpe seg et privat sikkert domene og en blogg-applikasjon som vil koste mindre enn en hundrelapp i måneden. Her kan de publisere sine ytringer og heller legge ut linker til sine respektive private internettsider på sine Facebook-sider - og altså ikke selve ytringen!

Fortsetter de å gjøre som i dag risikerer vi store demokratisk problemer i fremtiden når falske nyheter er med på å vri våre demokratiske prosesser i uheldige retninger uten kontroll av våre myndigheter og vårt ærværdige Storting.

Det hjelper ikke at Facebook nå har annonsert at de ønsker å satse mer på “venne-kommunikasjon” og mindre på nyheter - dette er bare et resultat av taktikk og det faktum at de ikke greier å ta et redaktør-ansvar for den store mengde “nyheter” som flommer inn på Facebook. For bare en uke siden fulgte Facebook opp med å oppmuntre brukerne til selv å kvalifisere kredibiliteten til nyhetene de leser(?). Dette hjelper heller ikke stort og har ikke noe å gjøre med redaktøransvar!

Så kjære politiker, når det oppmuntres til å tenke seg om tre ganger for du legger ut noe på Facebook så er det ikke bare for å beskytte dine personlige data, men også for å unngå å “legalisere” plattformen med dine viktige politiske ytringer og dermed gjøre plattformen til et fluepapir for falske nyheter!

Blockchain - intro

Blockchain is a decentralised ledger technology used by a business network to securely exchange digital or physical assets. Each member of the network is granted access to an up-to-date copy of this encrypted ledger so they can read, write and validate transactions. Once a transaction is validated using a consensus process, it's instantly committed to all ledgers in the network.

The net result is faster, private, confidential and audit-able business-to-business interactions among suppliers, distributors, financial institutions, regulators or anyone wishing to make a secure exchange. Blockchain creates a permanent, digitised chain of transactions that are grouped in blocks and can’t be altered.

Some benefits of blockchain:

    Reduces settlement time from days to near instantaneous.
    Removes overhead and cost intermediaries.
    Reduces risk of collusion and tampering.
    Increases trust through shared processes and record keeping.

1) One of blockchain's main benefits lies in its transparency, as the aforementioned ledger functions as a living, breathing chronicle of all peer-to-peer transactions that occur.

2) Each time a transaction takes place, such as one party sending bitcoin directly to another, the details of that deal - including its source, destination and date/timestamp - are added to what is referred to as a block.

3) This block contains the transaction in this example along with other similar types of transactions that have been recently submitted, usually within the past ten minutes or so when you're dealing with bitcoin in particular. Intervals may vary depending on the specific blockchain and its configuration.

4) The validity of the transactions within the cryptographically-protected block is then checked and confirmed by the collective computing power of miners within the network in question.

On an individual basis, these miners are computers which are configured to utilise their GPU and/or CPU cycles to solve complex mathematical problems, passing the block's data through a hashing algorithm until a solution is found. Once solved, the block and all of its respective transactions have been verified as legitimate. Rewards (bitcoin, in this example) are then divvied up among the computer or computers that contributed to the successful hash.

5) Now that the transactions within a block are deemed valid it is attached to the most recently verified block in the chain, creating a sequential ledger which is viewable by all who desire.

This process continues in perpetuity, expanding upon the blockchain's contents and providing a public record that can be trusted.

In addition to being constantly updated, the chain and all of its blocks are distributed across the network to a large number of machines.

This ensures that the latest version of this decentralised ledger exists virtually everywhere, making it almost impossible to forge.

The Nobel Prize in Literature 2017: Kazuo Ishiguro

The Nobel Prize in Literature 2017 was awarded to Kazuo Ishiguro "who, in novels of great emotional force, has uncovered the abyss beneath our illusory sense of connection with the world".

I have now read through "half of his novels published in English", i.e. four of his novels. I am not sure if anyone has ever been awarded the Nobel Prize in Literature based on a smaller production, but after reading through some of his novels I have not seen a text more beautifully presented than what I have experienced in his novels. I would like to draw the attention to three of his novels presented in three very different historical periods of England, one contemporary (Never Let Me Go. – London : Faber & Faber, 2005), one by a butler reminiscing from the "glory" of the upper class England between the first- and second world war (The Remains of the Day. – London : Faber & Faber, 1989) and then the third from the rural England in the middle ages with ever ongoing conflicts between the Saxons and the Britons (The Buried Giant. – London : Faber & Faber, 2015). 

The key is that Kazuo Ishiguro actually tells his story with the distinct language/dialects that was actually used during all these three historical periods and he does it with ease and an elegance that I for one has never ever experienced. Its as if he has been spending hours on mending and compiling each English word into a sentence not leaving anything to vagaries, his language is simply amazing - Kazuo Ishiguro is truly one of the most deserved Nobel Prize in Literature laureates ever, despite his somewhat minuscule production...

Quantum Computing - from a novice point-of-view

Quantum Computing promise to change the world in the ways we will do computing and solve problems that we are unable to solve with traditional computers based on silicon transistors. We all have observed the physical limitation of the incumbent transistor gate that is currently down to about 10nm of contact length and provided the researchers can successfully use nanotubes as the new material, we may see 5 nm transistors in the near future.

Conceptually this technology and how the Quantum Computer is built could not be more different. Therein lay also the challenges and application constraints of the two technologies. Our conventional  silicon based computers  have already stopped scaling vertically due to heat issues when trying to reduce the contact length of the transistor gates, thus we are now resolving this issue by building multi-core systems, i.e. a horizontal scaling scheme requiring new programming models applied each individual operating systems as well as individual applications that enables different threads to be processed in parallel in multiple cores.

As it so happens, parallelism is what is the strength of the Quantum Computer.
Conventional digital computers store information as binaries, i.e. as bits that takes a value of either 0 or 1. Quantum Computers use the superposition of quantum states of particles, i.e. they use atoms, electrons, ions or photons to store information in elements called qubits.

As qubit can exist in superposition they can represent 0 or 1 or a superposition of 0 and 1 at the same time:

Unlike an electrical circuit, qubits are tiny particles (atoms has a size of 0.1-0.5 nm) that are magnetically suspended (or suspended by laser beams) in an extremely cold environment - fractions of a degree above absolute zero. What's so clever about this is that by keeping these particles in a state of superposition, they can simultaneously take on the role of both the 0 and the 1 in binary code.

Because qubits can contain these quantum multiple states simultaneously, Quantum Computers have the potential to be millions of times more powerful than today's conventional supercomputers.

The information in a qubit is encoded into its quantum properties such as the spin of an electron. The number of possible states equals 2^n for n qubits, i.e. two qubits can process four states simultaneously (in parallel) and 6 qubits can process 2^6 = 64 states simultaneously.  Each qubit can give just one answer when measured (under the mind-bending rules that govern the quantum world, measuring or even observing a subatomic particle alters it), but the superposition of states provides extraordinary processing power (if we can work out how to build them into a computer).

Currently the future quantum computer is targeting specialised parallel tasks including complex computations of possible folding configurations of complex molecules. Protein folding is an enormously complex computational problem (ref DNA/RNA) that is near impossible to solve with conventional computers.

Google has built a Quantum Computer with 9 qubits, IBM Research claims they will be able to build a ~50 qubits Quantum Computer in a few years, conversely IBM Research has also achieved to build a 5nm transistor based on silicon nanosheets that promises a 40% performance improvement over todays 10-14nm chips. To me, this pushes the Quantum Computer further into the oblivious future as we incline to lean towards conventional digital computers that are general purpose computers.

Dan Brown's Origin

Dan Brown did it again! Yet another exciting story with cliff-hanger chapters and amazing amount of research into technology, "hidden" dark religious movements and now artificial intelligence (AI).
As a technologist myself, I am impressed. He truly finds the right laws of physics as well as current state of computer technology to spin around an ever more fantastic story - and whenever I am sure he is going in the wrong direction, he has a good explanation.
This is indeed a must read for everyone, but maybe even more for those who loves physics, quantum computers and the race towards an ever more advanced AI.
Enjoy!!!

AI, Machine Intelligence, Thinking Machines and Smart Machines

A robot with rudimentary social skills
(Kismet robot@MIT  Museum)

Today we are experiencing a global media tsunami around the topic of AI and machines that can think, supersede the human brain, replace our jobs and even being a threat to the humankind (ref great minds like Stephen Hawking and Elon Musk).

Is it true, are we on the brink of developing and releasing machines that can think for themselves? Machines that are truly intelligent and that has a mind of itself?

If you ask the vast majority of people working in the tech industry, I guess you will have a vague and uncertain answer, but if you ask the top notch research people that are working on AI and developing cognitive systems, you will have a load and clear no, not in any foreseeing future, if ever! (ref “What to Think About Machines That Think” edited by John Brockman):

The media just dont get it, they are mixing all terms and definitions and focuses on imaginary robots that supposedly can out-think the human. What we do have experienced, for many decades already, are programmable machines that replaces boring, tedious and simple jobs by ticket machines, road tax systems, ATMs etc and lately more advanced and user-friendly internet banking systems replacing thousands of bank tellers and soon even traders (already happening), accountants and real estate agents.

So, in short, what happens is that the machines are getting more resources and capabilities to process more data, i.e. big data. The finance industry is a good example where we will see more and more usage of big data being processed by powerful machines with the help of machine learning. The finance analysts are spending most of their time investigating data for potential investments which are then fed into potential trading opportunities. The analysts are thus processing as much data as possible before an investment decision is taken.

A computer will be able to process much more data much faster and reach a recommended trading that in itself easily can be automated. Similar use-case you will find in life science and diagnostics. Computers with machine learning algorithms will be able to process much more data (medical journals) much faster and reach a recommended diagnosis almost instantly.

But is this thinking machines? Is it even Artificial Intelligence?

Machine learning is basically about training a prediction model enabling it to refine its prediction by providing training data. This training is an exhausting process as you need to train the model to understand all possible correlations of the data points. In the case of the financial analyst, we need to train our stock trading model all the correlations between the financial data points that the analyst would claim are relevant for the potential trading. This is an exhausting process and thus this is the main reason why we still have human financial analysts and traders, but that will not continue for long as gradually machines will be trained by machine learning to accommodate this exhausting process. But still, all these “thinking” machines are just trained extensions of our human minds.

These machines and their software are not about to leap beyond us intellectually, much less turn us into their slaves. They are simply just doing the instructed tasks much faster. 
I realise that you could argue that we are already dependant (slaves) of our handheld smart devices like iPhone etc, making us into trans-human and thus maybe there is a short step from these “smart” devices to a dependency of the “thinking” machines that act as financial analysts, traders, real estate traders etc., but is this scary? No, but very beneficial and cost efficient.

Do we face singularity - the moment when the machines surpasses our intelligence? No, not any time soon, the fact remains, these machines are going to continue being dependent on the human programmers for any foreseeable future - however that also includes the potential of programmers (human) making errors and introduce bugs that could have some serious consequences.

Einstein is quoted as saying “Two things are infinite, the universe and human stupidity, and I am not yet completely sure about the universe”

What if the machines do the programming? Are we able to teach the machines programming? Not really, but we may use machine learning to assist the machines to do some extensions of its own algorithm and as there is research going on in deep learning with neural networks scaled twelve layers deep, there might be some interesting development in the near future. Deep learning has already revolutionised object- and speech recognition and achieved significant progress in melanoma recognition in dermoscopy images, but is this silicon-brain a thinking machine?

Despite these amazing progress, what about the remaining capabilities of our carbo-brain? Our carbo-brain have billions of neutrons in cortical hierarchies ten layers deep and it has the capabilities to, not only acquiring knowledge, but has a mind, thought, experiences and senses.

“The gap between our best computers and the brain of a child is the gap between a drop of water and the Pacific Ocean” (Carlo Rovelli, Theoretical Physicist)

And just one last point, these “Intelligent Machine Systems" are often referred to as Cognitive which is also a bit provocative given that the adjective is defined as “of or relating to the mental processes of perception, memory, judgement, and reasoning” - and I don’t think any of these software systems fits the bill - at the best, they are Kismet robots with rudimentary skills.

Trends and super trends

1. Hydrogen fuel cells with smaller batteries will replace today's [huge] battery powered cars as well as hybrid vehicles - hydrogen fuel cells are really disruptive to petrol, diesel and electric cars, trucks and buses. Todays electric vehicles (EV) is, hopefully, just an intermediate stage as these huge batteries are not sustainable both from a mineral mining (cobalt) and pollution (CO2) point-of-view: 
   

   
   

   • Published in the journal Ingeniøren, the Swedish meta-study, which analyses and summarises studies completed so far in the field, found that around 150 to 200kg of CO2 equivalents (environmental impact equivalent to that of the release of CO2) are produced for every kilowatt hour (kWh) storage capacity of electric car batteries.
     
     

   • For example, taking two electric cars, the Tesla Model S and Nissan Leaf, which have 100kWh and 30kWh batteries respectively in Denmark, the study says these capacities are equivalent to 17.5 tonnes and 5.3 tonnes of CO2 being generated respectively.

   •  To put this in perspective, a round-trip from Stockholm to New York, by International Civil Aviation Organisation figures, releases around 600kg (0.6 tonnes) of CO2 into the atmosphere. In Germany, annual emissions of CO2 are currently almost 10 tonnes per person.

   • Therefore, the study has calculated that a fossil fuel vehicle can currently drive for more than eight years before it reaches the same environmental impact of a Tesla. For the Nissan Leaf, with its smaller capacity battery, this figure comes in at three years

   
   
   Every battery being used in today's electric vehicles are heavily depending on Cobalt which is a rare metal and Cobalt mining happens in Africa, predominantly Congo, thousands of miners in Congo dig by hand. Children, too.
    
2. Nanotechnology will resolve multiple material issues like replacing expensive platinum in hydrogen fuel cells. 
   
   
3. SO business based in US and Europe are being disrupted on price and performance by [Indian low cost companies](http://fortuneindia.com/2014/october/india-in-the-era-of-disruption-1.3290). I[ndian companies with Indian executives](https://qz.com/429017/can-indias-it-services-companies-weather-the-perfect-storm/) are much more cost-efficient than European or US based companies with high cost executive layers despite their “updated” business models with deployment of Indian infrastructure operation. These European or US companies needs higher profit margins to cover their expensive executives and also the running cost of their Indian infrastructure operation is higher (predominantly due to more people) than their Indian competitors simply because they do not know the culture and how to manage Indians efficiently.
   ---
   > The larger and more successful a company, the greater the risk of complacency. When a company is sitting on billions of dollars of cash, fat margins and good market share, it’s hard to create a sense of urgency and paranoia in the organisation and its shareholders. /Quote from QUARTZ India./
    

   

   Image Credit: Nilanjan Das Image Credit: ; Bandeep Singh

   
   
   
4. CRISPR-Cas9 is for fixing diseases and faulty genes in our DNA, people will live a longer healthy life, but will it also create superhumans? 
   

   

   Image credit: Royal Society of Biology

   
   
5. Silicon for General Purpose computing , Quantum qubits for special workloads. Pushing the limits of semiconductor technology (5 nanometer technology is just around the corner) is more important than ever as companies race to develop the latest applications for cognitive computing, cloud computing, and IoT. 
   

   

   Photograph of a quantum chip constructed by D-Wave Systems Inc

   

   IBM Research Alliance’s 5nm transistor (Photo credit: IBM)

   
   
6. Bio transistors - DNA transistor for sequencing:
   

   

   Photo credit IBM

   
   
7. Carbon (humans) vs Silicon and algorithms and [python] machine learning - silicon
   algorithms and machine learning will surpass humans in many areas. 
   
   
8. Labor vs cognitive robots - cognitive robots will replace many cognitive jobs, not only pure
   labor jobs. 
   
   
9. Future jobs are in microbiology, mathematics (algorithms) and machine learning. 
   
   
10. [Bio]IoT will replace smart phones. 
    
    
11. Wearable glasses will replace screens. 
    
    
12. Chat bots like Alexa, Siri, Mitsuku, Zo, Rose etc all gets cloud based and cognitive and will be
    in all households and on your “arm”. 
    
    
    
    
13. Algorithms will be the most valuable asset to companies in near future 
    
    
14. All social media data will not be encrypted and available to the authorities - internet is truly 
    “open”. 
15. Blockchain - superior digital ledger system
16. Azure Stack. fully integrated compute, storage and networking clustered Azure certified infrastructure (a single Azure Stack is a single region containing a single scale unit consisting of 4-12 servers) that provide “private cloud” services as well as hybrid cloud GW to public Azure. 
    
17. Humans has already transformed into [Transhuman] by use of their smart devices, i.e. these Transhuman has become completely dependent on their smart devices in all their daily tasks and consequently they become completely “lost” when their smart devices are left behind, lost or without power. Auxiliary power devices are becoming the next “big thing” and is selling in large numbers to ensure a never ending power supply. In parallel, the media and society at large is becoming more and more focused on AI and its possible impact on automation and jobs, but no-one is questioning the Transhuman and their smart devices.