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Wednesday, July 31, 2019

The Humorous Side of Artificial Intelligence

Humor is what makes humans special. When people try to teach machines humor, the results are at times laughable but not in the intended way. 

What makes humans laugh? Some occasions may be caused by contrary emotional states. Embarrassment, apology or confusion can cause nervous or courtesy laughter. Humans will laugh at jokes or will laugh at a play on words for instance, even though they may be very subtle. Everyone has a different sense of humor. What is funny to one person will go over the head of another. Laughter in some ways, is like human language and what may be hilariously funny in Japan will go over like a lead balloon in France.

Laughter bonds humans through humor. However, despite its prominence in our daily lives, there is little research on how and why we laugh.The study of humor and laughter and its psychological and physiological effects on the human body is called gelotology. The question as it relates to artificial intelligence is; can a sense of humor be taught  to machines?

Humor is a hidden language that we all speak but it is not a learned group reaction. It is more an instinctive behavior programmed by our genes and the societies we live in.  

Tristan Miller, a computer scientist and linguist at Darmstadt University of Technology in Germany says: “Creative language — and humour in particular — is one of the hardest areas for computational intelligence to grasp." 

Miller has analyzed more than 10,000 puns and called the experience torture. “It’s because it relies so much on real-world knowledge — background knowledge and commonsense knowledge. A computer doesn’t have these real-world experiences to call on. Up until recently, a robot or a computer could only know what it was told and could only draw from that knowledge.”

Great strides have been taken in trial and error learning in the science of artificial intelligence, this being one of the fundamental learning strategies employed by humans and animals. It is increasingly being used to teach intelligent machines boosting the flow of ideas between biologists and computer scientists. More studies in the trial and error approach could solve mysteries in animal and human cognition and help develop powerful new algorithms and therefore moving closer to AI being created with an ability to learn humor.

However, as humor is still somewhat  of a mystery in itself, can the trial and error approach be applied to developing humor in AI? Some scientists seem to think so. The following is a headline from Wired.com.  https://www.wired.com/story/comedian-machine-ai-learning-puns/?verso=true

The Comedian Is in the Machine. AI Is Now Learning Puns!
A researcher at Stanford University has created a pun generator that came up with the following groaner, all on it's own. 

"Why did the Greyhound stop? To get a hare cut". 

Her aim is to build AI that is natural and fun to talk to and that can crack jokes or compose a poem or even tell a compelling story. "But getting there," she says. "Runs up against the limits of how AI typically learns." 

Of course, a very common saying is a pun is the lowest form of humor but a machine has to start somewhere. Will AI eventually replace the Ricky Gervais's and Steven Colbert's of the world? Who is to say. 

"People have had some success in defining what would constitute humor," says Abhijit Thatte , Assistant Vice President of Technology and Practice Leader for Artificial Intelligence at Aricent, a global design and engineering firm. "But it has not been been codified yet."

As even full-time stand-up comics would admit, there is no magic formula to produce the perfect joke. Much of what makes us laugh depends on subtle factors such as context or body language. "Sometimes even we humans don't know why a joke is funny," says Thatte.

When it comes to an individual's funny bone, there has to be a really deep understanding of the world in which a person lives, how things work, how their society works and mostly how people in their society work. Humor is indicative of something that is really human and is also intelligent but in it's truly human form, currently outside the abilities of artificial intelligence.


Monday, July 29, 2019

Is Artificial Intelligence The Next Step in Human Evolution?

What is Artificial Intelligence or AI? Very simply, AI is intelligent machines that work and react like humans. Artificial intelligence can be classified as three different types of systems; 

Analytical AI only has characteristics consistent with cognitive intelligence such as thinking, reasoning or remembering using learning based on past experience to inform future decisions. 

Human-inspired AI has elements of cognitive and emotional intelligence and an understanding of human emotions and is used in conjunction with decision making.

Humanized artificial intelligence:
Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence) and is able to be self-conscious and is self-aware in interactions with others.

There are many areas of business, government and human entertainment that are well suited to the use of AI including but not limited to the following: 

  • Agriculture
  • Aviation
  • Education
  • Computer Science
  • Finance
  • Medical Care
  • Government
  • Heavy Industry
  • Mining
This list will continue to expand as  new generations of computers emerge and as the learning curve among the AI scientific community begins to flatten out. 

The science has not been around for that long. A handful of scientists back in the 1950's from a variety of fields (mathematics, psychology, engineering, economics and political science) began to discuss the possibility of creating an artificial brain. In 1956, the field of artificial intelligence research was then founded as an academic discipline.

There are a number of eminent scientists credited with founding of artificial intelligence science, foremost among them was Alan Turing, a young British mathematician who explored the mathematical possibility of artificial intelligence. Turing suggested that if humans could use available information as well as reason in order to solve problems and make decisions, why couldn't machines do the same thing? This was the logical framework of his 1950 paper, Computing Machinery and Intelligence in which he discussed how to build intelligent machines and how to test their intelligence.

However, before Turing could move further in this new science, computers had to change dramatically. They were at that time, essentially very smart calculating machines and while they could execute commands, they had no means of storing them. Some years later computer scientist and cognitive psychologist Allen Newell, political scientist, economist and sociologist Herbert A. Simon and systems programmer John Clifford Shaw all working at the Rand Corporation in Santa Monica, California, developed the Logic Theorist Offsite Link, the first program deliberately engineered to mimic the problem solving skills of a human being. 

They decided to write a program that could prove theorems in the propositional calculus like those in Principia Mathematica by Alfred North Whitehead and Bertrand Russell, a three-volume work on the foundations of mathematics written in 1910, 1912, and 1913. The first application of AI used in a practical manner was created by Joseph Weizenbaum in 1965 who developed ELIZA, an interactive program that carried on a dialogue in the English language on any topic. Weizenbaum, who wanted to demonstrate the superficiality of communication between man and machine, was surprised by the number of people who attributed human-like feelings to the computer program.

Artificial intelligence is becoming very good at many “human” jobs such as diagnosing disease, translating languages and providing customer service and as AI continues to evolve, there are reasonable fears among many people that artificial intelligence will ultimately replace humans in many jobs and occupations in industry and in the economy at large. 

Some AI scientists feel that is not an inevitable or even most likely outcome. While AI will radically alter how work gets done and who does it, the technology’s larger impact will be in complementing and augmenting human capabilities, not replacing them. Many developers of AI feel that with collaborative intelligence, humans and AI can actively enhance each other’s complementary strengths. What comes naturally to people such as humor is difficult for machines, and what is straightforward for machines such as analyzing terabytes of data very quickly is out of reach of the human brain. In our rapidly evolving world, regardless of whether it is business, education, industry, space exploration, quantum physics or medicine, all are going to require both kinds of capabilities.

The unanswered question at this point is; at some point in the future, will there be a emergence of AI and the human intelligence, therefore the next evolving step of the homo sapiens species and it's unique brain? To some, the answer is an unequivocal yes. 

At this stage of human evolution, there will be no turning back and the human race will be entering either a brave new world of human / machine collaboration or a world where humans evolve into machines. 

Thursday, July 18, 2019


Have you checked your mortgage rate lately ?  

If not, It's time to do just that.  These past weeks we have seen the 5 year fixed term rates drop to 2.69% for insured and 2.89% for  conventional rates. 

Are you paying too much ?  Even if you are facing an early payout penalty, it may make sense to refinance.  Sometimes a refinance can help pay other debts, to lower overall payments, or simply save you interest costs over the lifetime of your mortgage. If a penalty is involved, some math may be required to determine whether it is worth it to payout early.  Sometimes this analysis involves the risk of short term maturity  date that could result in a higher rate than today's 5 year guarantee.  

The best idea is to call me for analysis.  Once I help you calculate the cost benefits of an early refinance, my mortgage team is standing by to help you get through a smooth transition to your new financing.  

Considering a purchase ?  It's time to get ready with a pre-approval.  Pre-approval rate holds are good for 120 days while you sift through a buyer's market to find the perfect home.  

Contact Francine: francine.tracey@promerita.com

Monday, July 8, 2019


My wife and I recently drove from Vancouver to Saskatoon to visit friends. Neither of us had travelled through the prairies since the 1970's before we met; my wife by train from Toronto to Vancouver and me by car after crossing the border from North Dakota into Western Saskatchewan to drive back to Vancouver after an extended driving tour in the USA.

We were both amazed at the wide open spaces and the almost unlimited amount of uncluttered landscape which reminded us a great deal of northern Germany where we travelled extensively in 2017. The big difference between the prairies and northern Germany is the lack of renewable energy producing sources on the Canadian prairies. In Germany, we came across huge solar farms and wind farms, kilometer after kilometer. Farm houses, barns and most buildings had solar panels on the roofs. Towns had clusters of wind vanes on high ground near each town.
Saskatchewan grows many crop including canola and wheat that contribute a great deal to the Canadian economy, but much of the countryside we drove through lay fallow or was unused. While I understand the highest wind speeds in Saskatchewan are in the southwest, it seemed the unused land in the rest of this very flat land could be used to create massive solar farms. Given that Saskatchewan is the sunniest province in Canada, in all seasons, and boasting almost 3,000 hours of sunshine a year, building environmentally friendly, clean energy solar farms across the province would seem to be a no brainier.

Upon our return, I did a bit of research on Germany and came across the following information. Germany recently increased its renewable energy goal from 55 to 65 percent by 2030 to compensate for the decommissioning of aging nuclear and coal plants. Germany has been called "the world's first major renewable energy economy." Renewable energy in Germany is mainly based on wind, solar and biomass. Germany had the world's largest photovoltaic installed capacity until 2014, and as of 2016, it is third with 40 GW. It is also the world's third country by installed wind power capacity, at 50 GW, and second for offshore wind, with over 4 GW.

In Germany, the share of renewable electricity rose from just 3.4% of gross electricity consumption in 1990 to exceed 10% by 2005, 20% by 2011 and 30% by 2015, reaching 36.2% of consumption by year end 2017. As with most countries, the transition to renewable energy in the transport and heating and cooling sectors has been considerably slower.

Now however, more than 23,000 wind turbines and 1.4 million solar PV systems are distributed all over the country. According to official figures, around 370,000 people were employed in the renewable energy sector in 2010, particularly in small and medium-sized companies. This is an increase of around 8% compared to 2009 (around 339,500 jobs), and well over twice the number of jobs in 2004 (160,500). About two-thirds of these jobs are attributed to the Renewable Energy Sources Act.

Germany's federal government is working to increase renewable energy commercialization, with a particular focus on offshore wind farms. A major challenge is the development of sufficient network capacities for transmitting the power generated in the North Sea to the large industrial consumers in southern parts of the country. Germany's energy transition, the Energiewende, designates a significant change in energy policy from 2011. The term encompasses a reorientation of policy from demand to supply and a shift from centralized to distributed generation (for example, producing heat and power in very small cogeneration units), which should replace overproduction and avoidable energy consumption with energy-saving measures and increased efficiency.

Compare these statistics to Canada's record. In the electricity sector, hydroelectricity is the largest renewable energy source in Canada, accounting for approximately 60 percent of Canada's electricity generation. Other non-hydro renewable energy sources, such as biomass, wind, tidal and solar, contribute 3 percent, compared to Germany's 36% at the end of 2017.

The big issue with hydroelectricity is its impact on the environment due to the enormous amounts of concrete required. A major component of concrete is cement; the cement industry is one of the primary producers of carbon dioxide, a potent greenhouse gas. Concrete causes damage to the most fertile layer of the earth, the topsoil.

Solar energy systems have some certain negative impacts on the environment just like any other energy system, but solar energy is a lot cleaner when compared with conventional energy sources. Solar energy systems have many advantages such as being cheaper and not producing any pollutants during operation and, being almost an infinite energy source when compared with fossil fuels.
On a closing note, a common myth is that solar panels do not work during winter, but on the contrary, cold temperature will typically improve solar panel output. The white snow can also reflect light and help improve PV performance. Winter will only hurt solar production if the panels are covered with snow, a problem easily solved.

Saskatchewan, if not Canada could be a leader in this field climate and geography.