Nexttech

Nexttech
Creating Generational Legacies

Saturday, May 12, 2018

Jobs vs Machines in the Digital age




A while back, we conducted 50,000 surveys of Information and Communication Technology (ICT) adoption and use by small to medium businesses and not for profits. We mapped 19 industry sectors and 480 business categories in depth, and then created workshops to help organisations understand which technologies would be useful and why.

The results provided a gateway for helping organisations better understand what ICT could do for them. How it could help improve communication, increase productivity, insight, information sharing and collaboration – all the things we now take for granted.

We surveyed which products and services were being used. We queried how these were “rated” by users, and what sources of help, information and advice on technology, respondents relied on. 

Which was very interesting. Results were not necessarily those you might expect. 

For instance, government sources of help, information and advice rated far lower than all other sources in every survey we conducted. By a huge margin.

And the digital revolution rolls on. Ever increasing connection, collaboration and integration of technology continue to change the landscape. Providing many opportunities beyond just the use of ICT in individual businesses. 

And we now see that a relatively few large multinationals have grown to dominate and leverage this ever-connecting digital landscape in ways that many did not expect. 

Opportunity for many has now morphed into threat for many. And Cambridge Analytica is just one example of what can happen when data is collected, aggregated and re-identified for vested interest. There are many others.

And it is unclear whether this can be reversed.

In reaction to this changing landscape, we reviewed our database and mapped for each industry sector and each business category, a picture of how twenty-three new technologies are now threatening Australian organisations.
Challenging jobs, businesses and even whole industry sectors and regions.

We looked at everything from Artificial Intelligence (AI), 3D printing, Augmented Reality, Internet of Things, Blockchain, Cloud services, BIM, GPS, 5G, Cryptocurrency, Cybersecurity, Drones, Digital Identity, IP protection, Mobility, Nanotechnology, Robots, Solar and Battery Storage, Virtual Reality, Amazon, airbnb, Freelancer, Google, Uber etc, not forgetting climate change and “fake news”, to define just how new technologies are collectively changing the work environment for better and for worse.

It is an interesting map and only makes real sense at the individual business category level, because businesses within an industry sector do many different things, and technology affects each business category differently, sometimes productively and sometimes negatively.

At the business category level, the impacts become personal. It is real people walking out the door replaced by technologies of all kinds. Software is implemented, efficiencies gained and restructuring does the rest. Roles are redefined and full time jobs are moved to contract, part time, freelance and even outsourced overseas.

We have all witnessed these changes. However, when you do the sums and add up the number of employees impacted by these changes over a relatively short time frame, the result is worrying.

We are told that as a result of digital disruption roughly half of existing jobs will be impacted in some way over the next twenty years. Not everybody agrees with the figures, but these predictions align with our research pretty well. 

We can see, by matching each business category against all the potential impacts that roughly 6 million jobs in Australia are under threat, with 2.5 million over the next 5 years. Which is concerning when you realise than just over 12 million Australians currently have jobs and now half of those are under threat.

And according to Roy Morgan latest figures for May 2018, 1,196,000 Australians are now unemployed, and another 1,349,000 are now underemployed and looking for more work. Which is nearly 20% of the workforce.

And in most cases the job threat from digital disruption represents replacement not displacement. A robot or software product or both will replace the job completely, not just displace or push workers into some other job opportunity. Because the impacts are happening across every industry sector, and in every country pretty much at the same time.

The change suits some people, but not everybody has skill sets (brain skills, eye skills, hand skills, no skills) that can be easily translated and transferred to new job opportunities. Especially when there are even fewer new jobs available that AI, blockchain or robots can’t replace.

New jobs are being created, but these jobs are not for everybody and favour brain skills and eye skills = STEAM.
And you can’t move workers from one job activity into another job activity if workers are being pushed out of that area at the same time.

If we don’t prepare for this (and we are still only just talking about this, not actually doing anything), we are in for a big shock. 

In this new digital version of workplace musical chairs, half the chairs are being removed simultaneously. Not just here, but across the world. With additional disruptive pressure coming from climate change, war, terrorism, refugee movement and political game playing of all kinds.
Currently, two of the biggest costs to Australian society (and treasurers) are health care and prisons. 

People without jobs and meaning in society can (and do) become depressed, ill and a burden on health services (which are already stretched to the limit). 

People without jobs and meaning in society can (and do) also become angry, hungry and desperate. And a significant number of frustrated individuals without jobs and no hope of finding a job, will react and respond in ways that lead to incarceration. Meaning more people in prisons.

Which we cannot afford, not just because of the dollar cost, but because of the impacts to families, children, communities and regions as well as the bottom line.

It all joins up.

At a time like this, cutting the tax rate for the richest in society is not a wise move. It will just confirm what most people already believe anyway. That our politicians have been highjacked by lobbyists, money and vested interests. 
That the Australian “fair go” has disappeared. 

 “Fair gone”. And we let it go.

We need to support the makers in our country not the takers – support agriculture, creative industries, ICT, manufacturing, medical and health, mining services, smart trades and tourism. Give the tax cuts to productive industries – the “makers”, not banks – the “takers”.

But the digital revolution is far bigger than one budget. And will have a much bigger impact on what happens next.
But we are not completely helpless, regardless of government indecision. And it is not all bad news. If we respond in time then many of the negative impacts of digital disruption can be managed or slowed giving us time to think and act. 

Ignore the digital threat or move too slowly, as we are doing at the moment, and the enemy will be at the gate before we are ready.

Governments prevaricate. It is their nature. The next election always takes precedent over action. Indeed the Murdoch press is in election mode already.

And few people can see the big picture. Those in the technology industry that do speak publicly with warnings about digital job destruction – Bill Gates, Elon Musk and Stephen Hawking among others – are not really understood. They can see it from the inside. We just see symptoms occasionally.

“Did you hear, Bill and Mary have been made redundant?”
And not all governments prevaricate. The Chinese government’s plan is to catch up with the USA on AI technology and applications by 2020 (just two years) and become a global AI innovation hub by 2030. 

And the Chinese don’t just talk about these things. They do them. 

Because they can. 

While our governments at all levels, just talk, muddle and fuddle and worry about their seats in parliament or council. They don’t worry about our seats in the new game of workplace musical chairs.

We live in a comfortable country, surrounded by blue sea and sky, with the sun nearly always shining on this huge, well resourced island a long way from everywhere.

But we are not the only ones who make decisions about what happens here in a digitally, interconnected world. Decisions affecting us are made in China, the EU, USA, UK, Japan, India and Korea every day.

So we need to wake up to just how fast the world around us is changing.

And take action.

We need to do three things. 


One. We all need to take time to really understand what is happening. Ask Google. Talk to a systems integrator. Then share, educate and inform others. 

Currently, digital disruption is viewed a bit like climate change. The impacts are off somewhere in the future. Which is correct. 

But that future is closer than you might think.

In the next three to five years we will see the first 1.5 million Australian jobs under threat, in financial services, retail, wholesale, rental and real estate, administration and support. As well as some categories in professional services and health.

And in the next ten to fifteen years, another 4.5 million jobs will be threatened as AI really takes hold. 

Which for our children and grandchildren in Australian schools is going to be a challenge.

As a student, “what should I study in the short term and longer term?” And “how will the work environment I expect to enter change?”

Two simple questions. But highly relevant to students in schools, higher education and training. And to their parents.
These questions are also important to the rest of us. Because the technologies that affect students, will also affect our jobs and workplaces. With redundancies, contracts, offshoring, part time and no time.

So. Job one. 

Understand what’s happening. Then help educate and inform.
We should all do that.

Job two. 
Leverage the positive impacts and opportunities presented by digital technology, wherever we can. We have lots of allies in the systems integrators, web services and voice services across our nation. They deal with these disruptive issues every day.

But not everybody has the skills to be a systems integrator or work in the ICT industry. And the whole sector only employs a few hundred thousand people anyway.

We need to focus a lot more energy on a wider spectrum of Australian productive industries to diversify and spread risk in a country far too reliant on dirt, meat and wheat, and invest more of our money, brains and creativity into a broad suite of value-added products and services. Then offer them to the world.

We have to move beyond commodity “cargo cult” thinking. We are very fortunate to have a productive mining sector and a farming sector, but we need to broaden our vision for the future.

Job three. 
Mitigate the risks and the threats (slow them down) where we can’t change them.

Example. News Ltd and Fairfax support and protect the real estate industry from threat, because they own Realestate.com and Domain.com, both of which rely on the real estate industry for providing and uploading content into their sites. 
So it is in the interests of both publishers to “talk up” property investment and house prices, which they do, and also try to protect real estate agents from the impacts of alternatives, which they also did.

But this is rearguard action. It will only slow change down, not prevent it. And change will come, and is coming now from blockchain and AI. And real estate agents will ultimately be just a subject page in history books and Wikipedia.

But not quite yet.

Because change involves being “ready, willing and able”. 
And technology requires adoption and use. There is a human element involved. 

And choices.

So even though technology is now able to replace everything real estate agents do, News Ltd and Fairfax are not ready or willing to support the change. And real estate agents don’t want it either.

So vested interests can slow things down for a long time. Just think how much time the tobacco industry bought through political lobbying, strategic blocking action and denial – 60 years.

Threatened industries can be protected for a while. But only to offer time to migrate, translate, pivot and evolve into something else. Or be disintermediated.

Because the new threats are coming from everywhere and the investment in new technologies is enormous.
Each business category has its own story. And each category is at different stages of readiness, willingness and ability.
And each category has a different set of vested interests in play. And these factors can offer regions, sectors and business categories time to move to safe ground. We need to leverage this fact, with eyes wide open. Strategically.
Yes, jobs will disappear. Lots of them. 

But by using a little wisdom and understanding, we can help organisations and individuals to migrate, train, learn new skills, avoid the categories under most threat and generally turn threat into opportunity whenever possible. It won’t always be easy and it won’t always be possible.
But we have to face up to the facts. Not ignore them.
For our part, on a more positive note, we have already created a showcase of Australia’s best of breed manufacturers and producers for the world to see. A shop window of what we do best – produce, manufacture and create.

https://theredtoolbox.org/index.php/showcase-fp
If you know of any additional manufacturer, producer or service that should be included, let us know. And we will add them.

We have also begun to directly “build bridges” between Australian businesses and businesses in other countries, starting with India, partnering with the Australia India Business Council so that Australian businesses and Indian businesses can talk and engage. To increase export.
https://theredtoolbox.org/index.php/groups-3

We will add other countries into that “bridge building” framework in due course.

And last, but not least, we are now working on a new project based on the 50,000 surveys I spoke about – the ED Toolbox, designed to help students and parents better consider and understand the impacts of twenty three disruptive technologies on 400 business categories across 19 industry sectors, to grasp how those business categories will be affected and when. And what that might mean to work and jobs.

Because students and parents need help in understanding that the world of tomorrow is not the world of today or yesterday. And tomorrow is coming quicker than expected and disrupting the world of work and jobs, not just here but everywhere.

So as we now begin to engage with teachers, schools, consultants, training organisations and others on this project, we are inviting help and input.

First stage: Ed Toolbox for Students and Parents
This is a relatively simple tool that allows a student and parents to consider the impact of twenty-three disruptive technologies on 400 business categories across 19 industry sectors.
The tool should help in considering and planning study and work options for the future.

Second Stage: Ed Toolbox for Schools
This will be an extended version of the ED Toolbox, incorporating a social platform to allow discussion between students, parents and teachers, plus offering the potential to connect to and engage with a range of businesses already responding to the impacts of digital change in their workplaces.

Real world case studies.

We will also include a much wider group of interested parties in the development discussion, and in the solution. 
So we are meeting with schoolteachers and principals to get input and advice. Anybody with productive ideas on the project can sign up to the RED Toolbox for free and join the discussion.

Disruptive change is now a fact of life. But it is time to collaborate, push back and manage digital disruption to our advantage. Not just roll over and let it happen.

Ivan - join our BBG Innovation forum to collaborate, learn and grow - and explore solutions and plan for jobs for the future

Www.bbg.business



Monday, May 7, 2018

How Silicon Valley has become a $3 trillion asset - It all starts from a story!



How did Silicon Valley become a $3 trillion area? 


It all starts with a story - and this narrative starts with Mr and Mrs Leland Stanford 



Early 19th century was farmland 





1885 - Mr and Mrs Leiland Stanford set up Stanford University in memory of their son who died at Harvard. There is a great narrative how they arrived at the Harvard Presidents office in threadbare clothes- and was ignored by the secretary - eventually after a few hours - was “granted an audience” - and offered to erect a memorial in the form of a building . The president , looking at their clothes said - “it’s very expensive you know .... Harvard’s buildings cost $7m - at which Mrs Stanford whispered to her husband “is that all that is needed to set up a University? - and they moved to Palo Alto and set up Stanford!


1930s navy built an aerospace hub - scientists and smart people moved to area 


1939 HP founded there - got government contract making radar and artillery 




1940s - at Bell labs - William Shockley co-invented the transistor. Transistor became computer processor





1956 - Shockley set up silicon labs - employed grads from Stanford 


1958 - 8 employees left to create Fairchild semiconductors - became known as the “traitorous 8” -made computer components for Apollo programme 


1960s - Gordon Moore and Robert Noyce 2 of the 8 founded intel on a one page business plan 


Late 60s - 2 other of the 8 founded Kleiner Perkins 




1969 - government research project with Vint Cerf - that went on to become the internet 


1970 - Xerox set up in Palo Alto


1971 - Don Hoefler set up Silicon Valley Times - and the name Stuck!


Lots of stuff around Stanford research


1980s - Atari, Apple and Oracle founded


1990s - Ebay, yahoo ., Paypal and google


2000 - 2002 - dot com crash - I remember seeing empty building after enoty building!


2003 - 2018  - Facebook , Uber , Twitter and Tesla 



2018 - 2030 - ????


2030 - 2050 - ????












Sunday, May 6, 2018

The future of work - towards 2030


 Alvin Toffler predicted a future in his 1970 bestseller Future Shock that looks much like today’s reality.
Alvin Toffler's 1970 bestseller Future Shock anticipated the rise of the internet

He anticipated 
  • the rise of the internet, 
  • the sharing economy, 
  • companies built on “adhocracy” rather than centralized bureaucracy, 
  • the broader social confusions and concerns about technology.
  •  how the evolving relationship between people and technology would shape how societies and economies develop. 

So where will we be in 2030?

  •  Jobs - what will they look like? 
  • How will we re educate ourselves?
  • What will education look like?
  • How will we earn a living?
  • Will we need to earn a living?
  • How will we communicate?
  • Will everything we do be inaliebly linked to the internet?
  • Privacy? Will it exist?
So many other questions - what questions do you have?

Can we master greater connectivity

Many are convinced that the internet will be everywhere - or nearly everywhere - in the next generation. It will be "on" most things and built into many objects and environments. 

Experts claim that the internet will fade into the background, becoming like electricity - less visible but deeply embedded in human endeavors. 

Even those without high levels of literacy will interact with digital material and apps using their voice, igniting an unprecedented expansion of knowledge and learning.

The build of AI - will there be mistakes along the way? Who will build it? Will it incorporate values that we can be proud of? 

This explosion of connectivity has bought and will continue to bring infinite new possibilities, but also economic and social vulnerabilities. 
The level of coordination and coding required to stitch the Internet of Things together is orders of magnitude more complicated than any historical endeavour yet. 
It is likely that things will break and no one will know how to fix them. 
Bad actors will be able to achieve societal disruptions at scale and from afar.
 Consequently, we are faced with some hard, costly choices. 
  • How much redundancy should these complex systems have?
  •  How will they be defended and by whom? 
  • How is liability redefined, as objects are networked across a global grid and attacks can metastasize quickly? 

Will we create more meaningful work?

Will AI , IOT and machine learning Be good for humans? Will it create or destroy jobs? Will more valuable jobs replace those supplanted by technology. 
How are we as humans going to react to the technology revolution? 
What jobs will replace those that will be done by machines. 

How will education and skills-training adapt?

Colleges, community colleges and trade schools - models are being disrupted - Teaching is now blended  through online video or hybrid courses which provide both online and classroom experiences. 
Artificial intelligence systems will assess student performance and the sufficiency of the course. 
Employees are also self-training with online material.
What will always be needed is collaboration and human connection.

Heather McGowan and Chris Shipley points out that the  best education programmes will be those teaching how to be a lifelong learner, and that alternative credential systems will arise to assess the new skills people acquire. 

So, what specific human talents will be unable to be duplicated by machines and automation for some time? 
They say 
  • social and emotional intelligence, 
  • creativity, 
  • collaborative activity,
  • abstract and systems thinking, 
  • complex communication skills, and
  • the ability to thrive in diverse environments.
What are schools and universities need to doing to re-orient to emphasise these non-technical skills?

It’s all about Trust!!

  • Trust is about reliability, capability and intimacy 
  • Trust is not about wiifm 
  • Trust is key to the development of a sustainable future 
  • Trust is a social, economic and political binding agent. is the glue for economic development and social cohesion
  • Trust is the lifeblood of friendship and care-giving

When trust is absent, all kinds of societal woes unfold, including violence, chaos and paralysing risk-aversion

With the proliferation of internet and mass collaboration - has trust been degraded? 

Preferences for convenience, comfort, and information have made people vulnerable to the ways organisations  can identify, target and manipulate them
  • Fake news
  • Using other people’s info
  • Spam
  • Preying on needs from data analytics 
  • Data theft
  • Unlawful data use 

How much can social and organizational innovation alleviate new problems?

There are new ways of doing things
Old corporate structures are old

New ways of collaborating - using tools that can track measure and reward activity 
Some primary aspects of collective action and power are already changing as social networks become a societal force. 
These networks are used for both knowledge-sharing and mobilizing others to action. 
There are new ways for people to collaborate to solve problems. 
BBG is a case in point (www.bbg.business)
New laws and court battles are inevitable and are likely to address questions such as: 
  • Who owns what information?
  • Who can use and profit from information? 
  • When something goes wrong with an information-processing system (say, a self-driving car propels itself off a bridge), who is responsible? 
  • Where is the right place to draw the line between data capture - or surveillance - and privacy? 
  • What kinds of personal information can be legitimately considered when assessing someone’s employment, creditworthiness or insurance status? 
  • Who oversees the algorithms that decide what happens in society? 
There is a long road ahead to 2030. There is a lot of opportunity to make the uncertain more certain. 
We look forward to being a player in this exciting time 

Thursday, May 3, 2018

Machine Learning: What’s in It for Business?

Who knew that stats would be the bomb?

How do you take Big Data and convert it into actionable information that would help business thrive?

Who knew that Machine learning and data analysis algorithms will benefit those service providers who have accumulated large data volumes about their clients, enabling analysts and marketers obtain impartial insight into customer behavior: how the client activity changes if the company has modified its service or introduced a new one; whether the existing service offering has a weak spot, which needs fixing; who to target at what time! 

 Here is an example of how the results of a problem-solving session that took place at a datathon was used to make a business decision 

Datathon is a hackathon focused on problem-solving using Machine Learning.

A bank provided client data in an anonymized form. The datathon participants were to analyze the datasets by generating multiple hypotheses and identifying the viable ones. The problem was expected to be solved using cluster analysis, a method of unsupervised learning.

Unsupervised Learning – a machine learning algorithm that teaches the computer system to identify inferences in datasets. They would consist of input data without labeled responses. Cluster analysis helps find hidden patterns or grouping in data based on specific parameters. For instance, this could be segmentation of subscribers of a mobile services provider.

Multiparameter Data as Basis for Hypotheses

The team was to make hypotheses using data with disparate input parameters. They included description of the product or service acquired, the amount paid using the credit cards issued by the bank, and user demographics – age and sex. The majority of the data fell into categories based on high-level payment destinations – shops, gas stations, services, etc. Some of the categories had a more detailed level of description, for instance, AliExpress, Uber, Burger King, iTunes. The major hypothesis made by the team was as follows: if they analyzed the user money spending patterns, they would generate a rather informative user portrait.

Data Processing, Pattern and Correlation Analysis

Processing Unlabeled Data


The team analyzed all payment destinations and identified correlations. The inference – the greater the number of identical occurrences in payment destinations, the tighter is the correlation (a heavier connector weight on the pic)

The team processed the unlabeled data as follows: reduced its dimensionality, performed clustering and correlation analysis. For this, they used such tech and tools as Python, t-SNE, DBSCAN, and Matplotlib. The participants also sanity-checked the data against the real-world parameters. Thus, they identified an outlier in payment destination values that amounted to 16,000 for an Uber ride. When studied closely, the amount turned out to have a foreign currency attribute. Once the team converted the amounts in major currencies to a common currency and screened the rare ones, the data became more informative



Identifying Patterns and Correlations

The team managed to identify several meaningful patterns and interdependencies. The graph analysis and cluster analysis used by the participants demonstrated a correlation among the clients commuting via Uber and those who shop on iTunes. Another cluster located nearby showed that credit card holders with foreign currency accounts are young people who are regulars at local bars and restaurants.

Unbiased Hypotheses Verification

The Datathon participants test-proved that unsupervised learning is a great fit for validating unbiased hypotheses. This method does not aim to identify cause-and-effect relations or achieve stable results, which otherwise may add subjectivity to the data processing results. For instance, the assumption that an average fast-food lover would frequent different fast-food brands did not prove valid during this problem-solving session.

The topic covered is the result of Olga Babik’s contribution.

Olga Babik is a tech blogger and marketing specialist with Softeq, a software company in Houston, TX. Olga closely collaborates with the Softeq engineering team who work on a variety of IoT projects with the focus on big data mining and machine learning processing at the backend. She highlights her colleagues’ first-hand experience and skills in prototyping, devising, integrating, deploying, and supporting connected solutions driven by firmware, software, and hardware.


Tuesday, April 24, 2018

The Basics Of Bitcoin

Great article by Ezekiel de Jong 

After my recent attendance as a guest speaker at Dubai's Block-chain Innovation & Investment Summit, Hong Kong's Token 2049 & a handful of other amazing events. I found myself being asked by investors & new comers the same questions quite often.

Here are some of the insights and knowledge I have had the pleasure to learn since 2012. Some of this knowledge was learnt the hard way, some was mentored to me by pioneers of this age and some is my own discoveries made over 6 years and counting in the digital currency & block-chain technology sector.
The ultimate ELI5 guide on Bitcoin: how does it works and how we can make a profit from it.

What is Bitcoin?

Imagine a currency that can be minted by anyone, using a mechanism that provides a reliable way to control your production and assures you’re not minting counterfeit coins.

Imagine a currency that can be used worldwide, without any restrictions, and it’s worth the same regardless of the region you are.

Imagine a currency that is completely secure, that cannot be scraped, counterfeit or stolen.

Better: imagine a currency that you can use as a secret savings account, that nobody can confiscate, steal or even know it exists.

Bitcoin is a decentralized, secure and valuable cryptocurrency which is used by more and more people. 

It’s a cryptocurrency; that is, a currency that is virtual (there are no physical coins) and secured by robust encryption algorithms that even the Pentagon cannot crack. 

It’s decentralized because there’s no central authority minting bitcoins; any person with a powerful enough computer can do it. 

It’s secure because nobody can steal bitcoins from your accounts (except if you are careless). 

It’s valuable because bitcoin is a reference for other alternative cryptocurrencies like Ethereum, Litecoin and so; alternative cryptocurrencies (also known as altcoins) are like ripoffs, which are attractive (or not) due to innovative features or its reduced transaction fees).

All the bitcoins in existence are stored in a virtual structure called the blockchain

Blockchain is public ledger that keeps all the accounting, for all the people holding bitcoins. You can check that ledger, but you cannot alter it in any way.

What is a blockchain?



In a nutshell: it’s a public ledger that holds all the entries needed to keep the bitcoin accounting up to date. To put it easy: imagine a real-life ledger. It has pages and pages of listings: Tommy spent $ 2 in a coffee, Vicky sent Tommy $ 500 for a consulting job, Nathalie received $ 100 from George, etc. Every page in that real life ledger is a block in a blockchain: a block contains data; that is, entries in a ledger. 

Apparently, is not that simple (there are metadata and other information) but for our purpose, that’s not important.

Pages in our blockchain are glued together by some metadata: a hash points to the prior block, just like the numbers printed in a real-life ledger assures anyone that no page is missing. 

Also, every block in the blockchain is validated by all the computers involved, in a scenario known as reaching consensus. Every computer minting bitcoins is helping to create new blocks (pages in our ledger), and, thus, validating and securing all the entries on that block (or page). Securing the blockchain (and receiving bitcoins in exchange for the effort) is what is called mining.

Mining bitcoins

In the early times of bitcoin, mining was done with a simple home computer, but nowadays you need a powerful cloud of computers, a mining rig, to profit from it. Millions are competing with each other to obtain part of the mining rewards for each block, so, to make things fair, all the computers in the network reach a consensus: raise the mining difficulty to very high values.

While it can seem unfair for people with just an average computer, this is what makes bitcoin the strongest cryptocurrency: nobody can just try and hack random accounts and steal their bitcoins. That’s almost impossible, and, to do that, you need to invest far more money that you’ll be able to steal.

You can still mine bitcoins using just your computer, but that will not be profitable at all: you can join a mining pool and add your computing power to thousands of other people to earn a small portion of the rewards. You’ll get a tiny fraction of an already small fraction, but you’ll be contributing to secure the bitcoin blockchain.

Bitcoin value

What makes something desirable and valuable? Imagine a block of solid gold, or a case full of diamonds. Both objects are valuable due their scarcity, and desirable due to its durability and stability over long periods of time.

Bitcoin is something relatively new. Some people doesn’t even know about its existence, yet many people want to own some. That’s because, regardless of its age, bitcoin is already seen as a commodity —just like silver, gold or diamonds.

Of course, there are some ripples in our golden lake. Volatility, for starters. Bitcoin’s price isn’t stable yet, and it’s subject to speculation, fear, uncertainty about its future and veiled threats about bans and heavy regulations.

And that’s the part that seasoned speculators love most: fear can be profitable. FUD can be profitable.

Profiting from Bitcoin

Speculators are people that keeps only one universal truth in mind: buy low, sell high. They buy at bid prices and sell at ask prices. As bitcoin usually doesn’t fluctuate so much during a trading day, and it has a great volume, making a profit buying and selling bitcoin isn’t that hard to achieve. You only need to follow some guidelines:

Be refractory to gurus and experts spreading FUD

FUD can be your best ally, but also your kryptonite. All the FUD spread by journalists and mass media must be taken cum grano salis, and always be used for your own benefit. If there’s a rumor about bitcoin being banned in some country, don’t panic: it’s almost always a ruse to lower the price so big actors can but larger volumes at a discount. Join (and enjoy) the party!

Never panic: bitcoin isn’t going to disappear or sink overnight. It can happen —and will happen eventually—, but it will not be today, tomorrow or the next month. You’ll see that coming.

Be prepared for long periods of sunken prices: a bearish market (i. e. a market that’s afraid enough that only a small fraction of people are brave enough to buy) isn’t rare, and you must be prepared for that. Always treat your investments in bitcoin (and any other crypto for that matter) like a hobby, and not like an actual income. You cannot predict when the markets will turn bearish or bullish; therefore, you cannot predict when you will be able to sell and obtain a profit. It can be weeks or even months until that happens. Again: don’t panic.

Repeat every morning: buy low, sell high: the only way to make a profit in volatile markets is repeating it like a mantra. There’s no way to teach you how to spot when a given commodity is low and when is high; we can talk about candlestick charts, OHLC charts, trends and SAR analysis, but it will be worthless if you haven’t a trained gut. Candlestick charts are invaluable, but they are just half of what you need to go out and succeed in a wild market like these.

In a nutshell

Bitcoin is a relatively new commodity, one that you cannot touch or hold in your hands, but you cannot just steal either. It’s stored on a blockchain, that is a virtual ledger stored out there, in the cloud. People can make a profit out of it in two ways: mining it (doing a hard, blue-collar job, with a fixed payment) or speculating with it (a white collar job if you ask, but with a fairly high risk involved, and high profits awaiting for those brave enough to give it a try).