Fast-Tracked Disruption & Innovation In The Tech Sector (Platforms, Open AI, COVID-19),

By members of the Quest Community at the last TGS session:

Alot of things have impacted technology including the recent global pandemic which impacted almost every facet of life – technology is no exception. In fact, the spread of COVID-19 has only served to increase the pace of what was already a rapidly evolving sector and fast-tracked the move of abstract technologies into mainstream usage.

From organisations finding new ways of working and identifying the technologies that could support same, to projects exploring the utilization of block-chain in industries such as forestry and mining, this technological shift continues to drive further disruption and innovation.

There are certainly interesting times ahead and it is likely that we will see greater diversity in terms of the channels through which technology projects are being rolled out and the types of companies undertaking same.

Emerging technologies and processes, including Artificial Intelligence (AI) and Machine Learning (ML), will be powering a lot of development within business and wider society, as the rise of decentralised working from home continues and the development of smart cities is accelerated. Things that we thought would be years down the line could, in reality, happen in a matter of months.

In fact, it’s already here!

We don’t have to look very far to find an example of a dynamic platform that has the potential to transform how we do a lot of things and is generating a great deal of hype. The GPT-3 model from OpenAI is the largest language model ever created, with almost 200 billion parameters. This system is one that could change how we write, programme software and interact with machines or devices.

One of its modes automatically generates text which is extremely convincing and human-like, bringing about the possibility of having a genuinely interesting conversation with a computer. Furthermore, when a user starts to type a sentence, the system can complete it. Similarly, a user can direct the model to complete an action, such as writing a love poem, and it produces one.

Not only does this create the potential for a completely revolutionised User Interface (UI) design, it delivers a new way of interacting with technology which is smooth, natural, and doesn’t require having an instruction manual to hand. The user simply says what they need, and the system responds accordingly.

On a larger scale, the GPT-3 model could change how we programme. As long as the concept is not too complex, there is every chance that this model could take direction from a human on what they want to programme and do it for them.

The next stage of disruption?

It is quite hard to say what is around the corner when you consider the rate at which these language models have grown in size. Earlier this year, the largest model of this nature from Microsoft had around 10 or 12 billion parameters. Within the space of half a year, that has increased tenfold. It is inevitable than bigger models will appear and will become more cost-effective. Moreover, big technology companies will produce their own versions.

Of course, a system such as this needs to be placed in capable and careful hands, otherwise it could be used for malicious purposes, or lead to a number of difficulties during production that are left unaddressed. It will take a period of experimentation for such models to be effective and reach a standard where the “generate again” button is no longer needed because the results delivered are highly accurate, relevant and reliable.

Imagine, then, if we were to put these models into robots. What if we combined the capabilities we have in terms of image and voice recognition with this type of mode? We could have robots that vacuum your floor while discussing philosophy. Further down the line, it is likely that disparate systems will be able to have conversations with each other and bridge the gap between themselves without human involvement.

The existing systems we use now will also evolve. For example, internet search engines could reach a point where they don’t provide various options for the user to choose, but rather give a definite answer to the question asked.

The truth of the matter is that the capabilities we thought were years away are actually emerging today as a result of technological advances and human behaviors, but also necessity. And these developments will have a huge and likely irreversible impact on the world.


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How Software Testing Has Evolved Over The Last 50 Years By Dorothy Graham,

Software Testing Consultant, Speaker & Author:

It might be hard to imagine a world where computers had just 0.5MB of memory. Information was stored on magnetic tapes, software testing involved handwritten coding forms and the internet didn’t exist. But that was the reality just 50 years ago. Since then, drastic changes have occurred within the tech sector – transforming the way software is both developed and tested – so it is quite unimaginable what could happen over the next half-century.

So, what exactly has changed within the software testing space over the last 50 years?

Testing has become a growing profession:

Testing was once considered a necessary evil, or perhaps more accurately an unnecessary evil, within the sector. When it started to emerge, it was a common belief that if testing were not performed, there would be no bugs! However, this mindset has changed – testing is now viewed as a valuable and crucial part of the software development process. It has become a respected profession and there is a variety of international qualifications available to those who choose this career path. Not only that but testers can now have specialisms within testing, from performance to security, web-based to mobile, Artificial Intelligence (AI) to automation – and even different subcategories of automation. Testing has really mushroomed as a discipline and an area of expertise in recent years.

Technological advances have been vast:

As well as a shift from mainframes to mobile apps, emerging technologies have completely revolutionised how testers and software developers do things. There are also a range of commercial and open source tools at their disposal, in addition to vast informational resources including dedicated testing webinars, blogs and books. These resources and technologies offer greater support for testers, including the possibility of automation. Back in the day, coding forms had to be handwritten and manually punched onto punch cards with a machine. If there was a typo in the form, it was not possible for the programme to be compiled. Now, with high-performing computers and coding programmes, this process is much more efficient and effective.

We have achieved better integration of testing:

Technological advancements over the years have resulted in continuous integration of testing within the development process and testing is no longer squeezed in at the end of the development method as it once was. Moreover, testers now play a central role within the software development team, the knowledge they possess is much more extensive and automation has become an integral part of the approach. However, human or manual testing will always play a key part in testing due to the fact that end users are people and there may be scenarios or defects that automation will not be able to identify and detect.

There are more complex systems nowadays:

Compared to before, there is a much larger landscape of opportunities in terms of what can be developed from a software perspective. Furthermore, systems are much more interconnected compared to 50 years ago with the emergence of the Internet of Things (IoT) and Machine Learning (ML). Testing is required across all these areas before products or services, such as self-driving cars, can be rolled out. As software and technology become more complex, the methods of testing also have to adapt. This will continue to be the case as the sector moves forward.

But not everything has changed…

The testing mindset remains the same:

For testers, their greatest asset is the tester mindset. And this is something that hasn’t changed over the years, nor should it. Where others focus on the positives and what they know, testers think about what could go wrong and the possibilities that others do not consider. Their professional pessimism is incredibly useful because it counteracts the optimism of the developer to ensure that alternative scenarios are explored, issues are considered, and problems are addressed.

More progress is still needed

While testing has followed the rapid evolution of technology and this pace of change remains constant, more still needs to be done in this space. For example, while there are qualifications available for people interested in testing, it is not yet taught at universities as a discipline. Moreover, a common issue testers face (there are exceptions!) is that managers still don’t quite understand this area therefore don’t realise the value of it. People who are new to testing also need to continue to develop their learnings, conduct research and expand their knowledge where possible.

Without a doubt, software testing has come a long way over the last 50 years. This progress has been driven by a number of factors including technological advances, better integration of stages with the software development process and a greater understanding of the role of testers. While certain aspects are the same and obstacles still remain, it is an exciting field which will continue to evolve at a rapid pace over the decades to come – which is why we look forward to seeing what the next half-century has in store.


If you are interested in AI, QA, software testing & other append-only tech and would like to engage with like-minded professionals from across the globe, get 60% discounted early bird tickets to this year′s Quest for Quality online conference by clicking here!

To access tons of resources, share topics/projects & join ongoing discussions on our Q4Q Knowledge hub, click here!

…don’t be left out, for more free sessions like this;