Search
Generic filters
Search in excerpt

An ETF for every investor.

CASH

Horizons High Interest Savings ETF

Price
$50.03
$0.00
0.00%
NAV
$50.0050
$0.0050
0.01%

Benchmark

Fixed Income

Fact Sheet
Learn more about CASH

QQCC

Horizons NASDAQ-100 Covered Call ETF

Price
$4.71
$-0.09
-1.88%
NAV
$4.6947
$-0.0318
-0.67%

Active

Covered Call

Fact Sheet
Learn more about QQCC

HRAA

Horizons ReSolve Adaptive Asset Allocation ETF

Price
$11.13
$0.01
0.09%
NAV
$11.1572
$-0.0018
-0.02%

Active

Corporate Class – Alternative

Fact Sheet
Learn more about HRAA
Explore All Products
Search
Generic filters
Search in excerpt
Back to Media

Objects in the Future May be Closer than they Appear

jupiter.jpg  

BY: HANS ALBRECHT, CIM®, FCSI, VICE-PRESIDENT, PORTFOLIO MANAGER AND OPTIONS STRATEGIST, HORIZONS ETFS

December 14, 2018

By definition, science fiction runs ahead of reality in depicting potential future technological capabilities. We like to dream beyond our abilities, and this is frankly what makes the genre so much fun. When the film 2001: A Space Odyssey was released in 1968, did viewers think it plausible that humanity could, in only a few decades, be travelling to Jupiter? In those days, the space-race between the U.S. and the Soviet Union was growing more competitive each week. A moon landing was imminent and the first un-manned space mission to Jupiter was in fact only a few years away. So what about the concept of humans making trips to Jupiter by 2001? Why not – although we now know that it’s going to take a little while longer to achieve those lofty ambitions.

Artificial intelligence (“A.I.”) is an area of innovation that requires both heavy computing power and large amounts of data to move the needle of relevance. During the 1990s, experiments with machine-learning had only narrow success. Why? The data wasn’t rich or plentiful enough. Equally as important, computer processing power wasn’t yet ready to tackle the number crunching processes that are required to turn large amounts of data into predictive gold. Because of this, A.I. experienced a kind of ‘A.I. winter’ as funding and focus in the area waned for years to come.

One of the hopes in having A.I. work well lies in being able to replace human input for tasks. We would then naturally require a certain level of competence in order for this to become reality. As deep-learning results improve, and error rates drop, the usefulness of the intelligence improves. As an example, image recognition and classification technology was merely passable in 2010, with error rates roughly five times that of a human. By 2012, those error rates had plunged to about two times the error rate. Now, A.I. can classify images better than a human. To extrapolate this concept, would it be exciting to see radiology imaging software that could detect certain types of cancers with a great deal more accuracy than a radiologist? The possible benefits to society are mindboggling. 

Why this rather sudden level of success? The required ingredients of computing power and rich data are coming together at an incredible pace. Computation power, thanks to advances in graphics processing units, has been doubling every 3.5 months since 2012. And the availability of data has exploded. It is said that 90% of the world’s existing data has been gathered in the last two years. 

Online retail shopping and banking has caught fire. Social media usage is clearly massive – think of how much of our behaviour is now tracked as we navigate passively throughout our connected lives. Much of this is being registered as ‘big data’, which many tech companies exploit. As more of the world comes online and conducts much of its business there, this mass proliferation of available data will rise even more exponentially. Mobile phones as an internet gateway are changing everything. For many, smartphones have become an extension of their very selves – keeping track of what they do and like, where they go and how they interact.  Data is becoming more detailed and granular than ever before. If big data is being considered the ‘new oil’, then mobile phone data represents a bottomless geyser. We’re in the early stages of a profound sea change in data mining and the way that information is processed. The implications for these advances will proliferate across all avenues of society with incredible pace.

Stanley Kubrick would have loved to have seen it – the present may finally be catching up with the future. You can watch in awe or you can be a part of it – by investing in RBOT and FOUR

The views/opinions expressed herein may not necessarily be the views of Horizons ETFs Management (Canada) Inc. All comments, opinions and views expressed are of a general nature and should not be considered as advice to purchase or to sell mentioned securities. Before making any investment decision, please consult your investment advisor or advisors.

Get Horizons insights in your inbox

Please select whether you are an…*
* Indicates required field

Related Posts

At Horizons ETFs, we believe in education as empowerment. We endeavor to equip Canadian investors with the knowledge and tools they need to navigate the investing world. From the ETF basics to more complex topics like how our suite of inverse and leveraged funds work, our comprehensive learning library aims to be accessible for all investors, from beginners to experienced traders!