Each day we read about amazing technology breakthroughs, particularly when it comes to artificial intelligence (AI). But if AI is so great, why are these breathtaking technological achievements not matched with soaring productivity and economic growth? Or, to paraphrase an old jibe: If the economy is so smart, why aren't we all rich? After all, we live among astonishing examples of potentially transformative new technologies that could greatly increase productivity and economic welfare. As noted in the 2014 book, "The Second Machine Age," leaps in AI, machine learning and, more recently in areas such as image recognition, abound.

Suicide is the second most common cause of death in people between the ages of 10 and 19 in Canada. Despite the country's preventative efforts, the number of suicides continues to grow year after year. Existing efforts include increased funding for suicide research, new mental wellness educational programs, and human-assisted monitoring of national suicide statistics. Though these efforts provide an important foundation for preventing suicide in Canada, it's clear additional tactics are needed to save more lives. This is where the predictive and scalable capabilities of AI could offer assistance.

The two biggest societal challenges for the twenty-first century are also the biggest opportunities – automation and climate change. The epitaph of fossil fuels with its dark cloud burning a hole in the ozone layer is giving way to a rise of solar and wind farms worldwide. Servicing these plantations are fleets of robots and drones, providing greater possibilities of expanding CleanTech to the most remote regions of the planet. As 2017 comes to end, the solar industry for the first time in ten years has plateaued due to the proposed budget cuts by the Trump administration. Solar has had quite a run with an average annual growth rate of more than 65% for the past decade promoted largely by federal subsidies.

Although the term Machine Learning (ML) was coined in 1959, it's advancement and development has never been more critical than it is today, particularly within government agencies. As the amount of data being produced, manipulated, and stored exponentially increases, so does the very real threat of cyber-security breaches and fraud. Meanwhile, federal budgets and staff resources continue to decrease. ML can provide high-value services for federal agencies including data management and analytics, security threat detection, and process improvement--but the list does not stop there. Machine Learning is a type of Artificial Intelligence (AI) that takes human-input data, analyzes it, and learns from it.

Every new year, China's president Xi Jinping greets his nation with a video recorded from his office. Behind the desk he sits at is an impressive book shelf that reveals what the world leader has been reading; it gets closely analysed every year, as we first saw via Quartz. This year, there were at least two books on his shelf about artificial intelligence (AI). They were Pedro Domingo's "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World" and Brett King's "Augmented: Life in the Smart Lane". Released in 2015, "The Master Algorithm" describes how machine learning is remaking business, politics, science and war.

Year to year, CES has a certain sameness about it: Intel's booth at the front, Sony's in the back and thousands of ginormous TVs in between. The topics and trends feel like the same things we've been talking about forever: Internet of things, smart home, autonomous vehicles, wireless everything. Is this really any different from last year? But turn the clock back just three years -- if not more -- and you quickly realize that the tech landscape of the past feels like a different planet. To that end, as we prepare to embark to Las Vegas, we've come up with 12 questions that we're hoping the world's largest technology trade show will answer -- or at least give us a clue as to where the world of technology will be headed in the next 12 months.

With 2017 coming to an end, we can get a glimpse of what's yet to come in the next 12 months through the number of investments and product testing. It's no surprise that financial institutions were the first players to experiment with blockchain technology since 2014 and became active investors in the space that totalled $4.5 billion of funding in 2017. In the past few years, financial institutions were testing blockchain technology and working on proof of concepts. By 2017, this largely moved into production stages. In 2017, a group of 11 international banks developed a trade finance application using R3 technology.

The nation could be shaped by geopolitics, momentum from robust economic growth, and a host of new leaders eager to implement new policy.

We're only a few months into 2017 and cyber attacks seem to be hitting the headlines even more regularly than last year. In the same week, it was announced that cyber breaches have cost UK companies £42m since 2013. The week before that, it was revealed that Chinese hackers had been carrying out sustained cyber attacks for three years across the globe. As a result of this boom in cyber crime, startups and companies across the world are harnessing new ways to handle the sophisticated attacks and spending is thought to be around $106.1bn in 2017, according to research by IDC. Artificial intelligence (AI) and machine learning are just two types of technology that are fighting cyber breaches on the front line.

Suicide is the second most common cause of death in people between the ages of 10 and 19 in Canada. Despite the country's preventative efforts, the prevalence of suicide continues to grow year over year. Existing efforts include ramped up suicide research funding, the addition of new mental wellness educational programs, and human-assisted monitoring of national suicide statistics. Though these efforts provide an important foundation for preventing suicide in Canada, it's clear additional tactics are necessary to save more lives. This is where the predictive and scalable capabilities of AI could offer assistance.