Innovation

The Latest

10 May 2022: Microsoft Research has introduced an advanced prototype of PeopleLens for young learners with visual impairment at the University of Bristol. 

The solution uses augmented reality eyeglasses tethered to a mobile device to identify people and track their direction and distance from the user. Using artificial intelligence (AI), the solution registers people in the system through facial recognition and alerts the wearer in real-time by identifying the person and their distance and direction through spatialised audio. To protect privacy, facial images in the system are not stored as photographs but as vector numbers to represent identities. The technology is not yet commercially available, but does provide hints at what the near future will

Why it’s Important

Education is something of a laggard in the application of AI, especially in Western economies. 

However, innovations such as PeopleLens provide a glimpse (pun intended) of what is possible. Using AI in education is expected to grow quickly, but where and how it will be applied is as much a matter of economics as it is technology. 

The cost of AI at scale can be a prominent issue in this case. AI computation may be inexpensive in cases where requests are relatively small, but costs can quickly add up for applications that require millions or even billions of transactions. In addition, releasing new AI algorithms is still relatively expensive, due to the high cost of investment in research and design, as well as expenditures for the development of prototypes, complementary equipment and software. Hyperscale Cloud computing helps reduce these initial expenditures, but training is still required. 

Therefore, the business cases for an AI initiative must be carefully weighed against the potential future scale versus the value to individuals. In short, does it scale economically?

In a recent IBRS interview with an Australian Microsoft Azure specialist who developed an AI model to detect improper Microsoft Teams usage among students - such as cyberbullying, aberrant behaviour and inappropriate content sharing platforms - the transactional cost was not feasible, even with the aggregate value of securing children from harassment online. Since the Teams environment hosted hundreds-of-thousands of users, each producing scores if not hundreds of messages daily, the total cost of running the solution was not a viable commercial option.

In the case of PeopleLens, on the other hand, the number of transactions per individual may be relatively high, but the number of transactions as an aggregate is relatively low. As such, it is potentially an example of where the value returned is acceptable when compared against the cost. 

Who’s impacted

  • CEO
  • Innovation managers
  • Education policy strategists
  • AI solution development teams
  • Product research teams

What’s Next?

Industries that are planning to leverage AI effectively and at scale should ask for examples of how different AI-powered solutions are being justified.  

For most organisations, AI will be leveraged as features from within SaaS solutions, such as SalesForce's Einstein and Microsoft's use of GPT3 inside the PowerPlatform. 

However, for those looking to create new applications that leverage Cloud and ML capabilities, transactional volume should be carefully considered early in the planning stage to accrue the most value from the investments in research, design, development and production in the long run.

Related IBRS Advisory

  1. All Together Now! Hybrid Work, Technology, Diversity & Inclusion
  2. Innovation: Taking action in 2018

The Latest

10 May 2022: Microsoft has integrated the Z-code Mixture of Experts (MoE) models to Translator and other Azure AI services to improve the quality and accuracy of its translation capabilities. Through the Z-code MoE, the models can speed up language translations on Microsoft Word, PowerPoint and PDF files. 107 languages are currently supported. 

Why it’s Important

Pretrained ML models now produce faster translations with consistency and help human translators reduce their workload, especially for repetitive writing and translation tasks. IBRS has observed that hyperscale machine translation has already progressed in terms of computational efficiency. Capabilities such as Z-code save runtime costs by using parameters that are only relevant for specific translation tasks.

However, to match (or sometimes surpass) the quality of human translators, genre-specific translation engines trained specifically on different types of content must be employed. The generic models offered by the hyperscale Cloud vendors are often insufficient. 

Genre-specific machine translation engines involve training highly nuanced models. Solutions such as those from Omniscien Technologies, for instance, provide far more accurate models that can be curated. In addition, these specialised models also allow for the translations to run on an organisation's own infrastructure, which is a consideration for organisations that need to translate sensitive or private content without digressing from the context of the original text.

Who’s impacted

  • CEO
  • Corporate communications teams

What’s Next?

Machine translation services will eventually make their way into the daily life of most people, much like how global positioning systems (GPS) have been integrated into mobile devices. 

Currently, free machine translation tools such as Google Translate and Bing Translator are not nuanced and far less accurate when compared to the output of human translators. Translation apps such as SayHi, allow speech-to-text translation in real-time while Papago and Waygo feature image recognition that automatically translates text on pages, signs and screen. However, these still cannot produce highly accurate translations based on context and language registers.

As such, translation at a basic level (word-for-word, literal) is not good enough for all use cases. For example, translating medical information, patents, user manuals or outputs for e-discovery requests requires a much higher fidelity of translation that must include referential, cohesive and natural-sounding output. For these cases, consider specialised machine translation solutions alongside (and possibly complementing) the more general offerings from the hyperscale Cloud vendors.

Related IBRS Advisory

  1. Can IBRS provide information on the establishment and maintenance of multi-lingual Web sites?
  2. Software Agents Maturity Model
  3. Managing cultural diversity

According to a new analysis from IBRS, Australia could reap a $224bn dividend by fast-tracking investments in digital transformation – and grow the economy by 1.3 per cent, more than six times the benefit of the Olympic Dam Expansion.

Full Story.

The Latest

24 June 2021: Samsung Networks, which was launched early in 2021, has struck a deal with infrastructure supplier PLUS ES to support the deployment of Samsung’s 5G technologies. Given activities from other 5G vendors, it is clear that the 5G rollout in Australia will only accelerate.

Why it’s Important

5G will impact both consumer and business applications, as well as hybrid working. It is not just a matter of speed. With greater bandwidth and different cost points, new services become possible. For example: chatbots passing not to a human agent using text, but a human agent on video. These service delivery innovations need to be tested in terms of how the public will accept them, the operational and staffing changes needed to support them, and finally the IT issues and architecture they will raise (including what to do with all the new data coming in)!

CTOs and innovation teams in organisations with public-facing services need to be experimenting and testing new service delivery options and ideas now, since such services are likely to give a competitive advantage.

Who’s impacted

  • CIO
  • Development team leads
  • Business analysts

What’s Next?

If not already established, form a temporary committee to brainstorm the potential for 5G on:

  • Service delivery
  • Field operations and staff
  • Business processes, both internal and external, and how these can be digitised ‘into the field’
  • Hybrid working

Related IBRS Advisory

  1. 5G potential to deliver economic upsides
  2. Samsung unveils new smartphones
  3. Telecommunications reborn
  4. Redefining what ruggedised means

The Latest

23 February 2021: The appetite for crowdfunding of tech startups looks to remain strong, with the fledgling accounting software vendor Thrive securing AU$3 million through the Birchal service.  

Why it’s Important

There are two lessons to take from this announcement. 

First, commercial crowdfunding is a growth area that will favour niche tech start-ups. As more success stories emerge, this has the potential to re-invigorate the Australian startup community, which has been lagging. 

Second, it highlights the likely capabilities to be introduced in SaaS-based financial solutions: namely AI-powered automation and machine-learning decision support.

Who’s impacted

  • CIO
  • CFOs
  • Individual investors

What’s Next?

There is the potential for larger organisations to set aside funds to invest in startups. CIOs and CFOs may wish to watch the crowdfunding space that may provide relevant solutions to their needs, or secure services that may complement or even compete with their organisation. While IBRS acknowledges this strategy will not be suitable for the majority of organisations it works with, there is the possibility this will become more common over the next decade, especially for startups in security, Cloud management and cost control, AI-powered automation and machine learning-based decision support systems.

While Thrive is unlikely to be of interest to CIOs, being targeting squarely at SMEs and sole traders, the vendor’s goals leverage AI to automate much of the account process and provide recommendations, highlighting where development dollars will be going for many SaaS-based accounting solutions.

Related IBRS Advisory

  1. CIOs seek ready-made over DIY AI solutions
  2. How can AI reimagine your business processes?
  3. Salesforce Einstein automate
  4. The evolution of SaaS offerings for legacy systems

There is more innovation going on behind the scenes in Australian organisations than they are being given credit for. IBRS advisor, Dr Joseph Sweeney, who specialises in the areas of workforce transformation and the future of work stated, Australian organisations have led the world in the uptake of virtualisation which now has Australia leading in terms of Cloud adoption. 'World-leading Australian innovation was emerging in how Cloud-based services could be used to make internal operations more efficient, which was less glamorous than some of the consumer-facing apps being developed by emerging fintech companies, but equally worthwhile." said Dr Sweeney. 

“One area of innovation IBRS has identified over the last year is a rapid update of low-code platforms to allow less-technical staff to be involved in digitising business processes,” he said. Citizen developers aren't just limiting themselves to e-forms but are using a full range of low code tools and vendors are reporting sales growth of over 30%.

Full story.

The Latest

2 February 2021: Google has announced general availability of Dialogflow CX, it’s virtual agent (chatbot) technology for call centres.  The service is a platform to create and deploy virtual agents for public-facing customer services. Google has embraced low-code concepts to allow for rapid development of such virtual agents with a visual builder. The platform also allows for switching between conversational ‘contexts’, which allows for greater flexibility in how the agents can converse with people that have multiple, simultaneous customer service issues.

Why it’s Important

While virtual agents are relatively easy to develop over time, two key challenges have remained: 

  1. the ability to allow non-technical, customer service specialists to be directly involved in the creation and continual evolution of the virtual agents
  2. the capability of virtual agents to correctly react to humans’ non-linier conversational patterns.

Google’s Dialogflow CX has adopted aspects of low-code development to address the first challenge. The platform offers a visual builder and the way conversations are developed (contexts) can be described as ‘program by example’. While there are third-party virtual agent platforms that further simplify the development of agent workflows (many of which build on top of Dialogflow), the Google approach is proving sufficient for non-technical specialists to get heavily involved in the development and fine-tuning of virtual agents

Who’s impacted

  • CIO
  • Development team leads
  • Business analysts

What’s Next?

If not already in place, organisations should establish a group of technical and non-technical staff to explore where and how virtual agents can be used. Do not attempt a big bang approach: keep expectations small, be experimental and iterative. Leverage low-code ‘chatbot builder’ tools to simplify the creation of virtual agent workflows, while leveraging available hyperscale cloud platforms for the back end of the agents. 

Related IBRS Advisory

  1. Chatbots Part 1: Start creating capabilities with a super-low-cost experiment
  2. Virtual Service Desk Agent Critical Success Factors
  3. SNAPSHOT: The Chatbot Mantra: Experimental, experiential and iterative
  4. New generation IT service management tools Part 1
  5. Artificial intelligence Part 3: Preparing IT organisations for artificial intelligence deployment
  6. VENDORiQ: Tribal Sage chatbot