When Southern Cross Austereo (SCA) become an early-stage investor in Melbourne-based Sonnant, Which-50.com Surprisingly, Sonnant CEO Tony Simmons responded by offering a demonstration to explain how it all worked. Sonnant styles itself as a "transformational artificial intelligence (AI) and machine learning (ML) company that provides content discovery for the spoken word". Simmons explained that the key to Sonnant's success was their initial decision to train the AI to understand the Australian accent in phase one. Anyone who's tried to make a booking at a restaurant while in America will know what I mean." Australian English is most associated with monophthongs (single vowels), where there are approximately 20 distinct sounds compared to American English, with only 16 sounds. Also difficult for the AI are Australian diphthongs, the timing between two vowel sounds and the tendency for a falling second sound. An accurate transcript of an analogue recording is necessary to map the ...

This week, the New South Wales Police announced the introduction of upgrades to their Insights policing platform. This new technology is designed to provide further services to frontline officers through faster access to critical information in the course of their roles in identifying persons and criminal activity across the state. Powered by Microsoft Azure cognitive technologies, the machine learning and deep learning capabilities were fully deployed in February 2021, with the goal of reducing police labour hours on manual data processing tasks, such as reviewing video feeds. Examples of how the AI systems will be used include one case were NSW Police collected 14,000 pieces of CCTV footage as part of a murder and assault investigation which would previously have taken detectives months to analyse. Microsoft claims the AI/ML infused Insights platform ingested this huge volume of information in five hours and prepared it for analysis by NSW Police Force investigators, a process which would otherwise have taken many weeks to months.

VAPAR an Australian startup in the Internet of Things arena which utilises artificial intelligence (AI) and machine learning (ML) to automate condition assessments for stormwater and sewerage pipelines, has raised $AU700,000 in seed funding. The funding round closed with a diverse range of angel investors in addition to Startmate and Australia's premier VC, Blackbird Ventures, who are also investors in Canva, SafetyCulture, and Culture Amp. The company, which began two years ago started says it aims to bring emerging technology into the traditional asset management space and revolutionise the way infrastructure is tracked, repaired and maintained. Co-founders Amanda Siqueira, CEO, and Michelle Aguilar, CTO, said they started the business after witnessing first-hand the tedious and time-consuming tasks of manual video inspection. Their software is used by water utilities and local councils to reduce the time needed for inspection reviews.

Consumers comprehensively reject the practice of brands, publishers and platforms tracking their internet behaviour without their explicit consent, according to research commissioned by Which-50.

Australian IBM cybersecurity engineers have developed an artificial intelligence (AI) system to analyse network connections and employee communications at an enterprise scale. The model detects changes in users' behaviour and can automatically triggers investigations even if the changes occur across multiple platforms. IBM research found the root cause for 52 per cent of data breaches in Australia was malicious or criminal attacks which often use methods like phishing and social engineering. The new IBM solution, developed in the company's Gold Coast cybersecurity lab as part of a hackathon, uses AI to monitor changes in employee behaviour and flags indicators of compromise. It was debuted to the industry at last week's Australian Cyber Conference in Melbourne as a way of showing what can be done but the solution is not something that can be bought directly from IBM. Currently known as "QRadar Insider Threat Detector with Watson" it uses IBM's AI model, Watson, to analyse user generated content – like emails, Word documents, and Slack messages – to detect both the tone of content and employees' typical behaviour or "personalities".

Deal making landscape in the artificial intelligence (AI) tech space during 2014–2018 was dominated by global tech giants, according to GlobalData. Of the top five acquirers, four were based out of the US, with Ireland-based Accenture being the only exception in the list. The four US-based companies–Facebook, Microsoft, Apple and Splunk–collectively accounted for 30 acquisitions in the AI tech space during 2014–2018, whereas Accenture acquired six companies in this area during the period. Aurojyoti Bose, Financial Deals Analyst at GlobalData, said, "Technology companies have been the dominant deal makers in the AI space. However, with AI making inroads into diverse sectors, the buyer universe in expanding and the space is also attracting investments from non-technology companies."

Increasingly sophisticated technology combined with changes in the way business works are transforming the role and expectations on B2B sales people. But one thing that hasn't changed is the power of the relationship between the buyer and seller. Trust remains the bedrock upon which great deals are built.

The report titled, The Shift to Predictive Engagement, recommends using predictive, real-time and reactive methods in conjunction. That's because without historical data to compare against it is impossible to retrain algorithms. Conducted by the Which-50 Digital Intelligence Unit in partnership with Genesys the report cites the use of analytics by full-service media buying agency, Audience Group, which implemented predictive engagement techniques last year. In the Investigates report, director James McDonald told authors that only a year ago the agency was manually allocating its spend between advertising, SEO, premium video, data use, remarketing banners, and mobile. Each channel would have its own budget approval, and then the team would execute slavishly for those channels.

The report titled, The Shift to Predictive Engagement, recommends using predictive, real-time and reactive methods in conjunction. That's because without historical data to compare against it is impossible to retrain algorithms. Conducted by the Which-50 Digital Intelligence Unit in partnership with Genesys the report cites the use of analytics by full-service media buying agency, Audience Group, which implemented predictive engagement techniques last year. In the Investigates report, director James McDonald told authors that only a year ago the agency was manually allocating its spend between advertising, SEO, premium video, data use, remarketing banners, and mobile. Each channel would have its own budget approval, and then the team would execute slavishly for those channels.

Customers shouldn't have to explain intent. Businesses should monitor what they are up to, so that customers can expect the same personalised attention from online shopkeepers as they get when visiting their favourite farmers' market. Put simply, the online marketplace is fundamentally different to the physical marketplace. As customers, we're often alone online and need to find the products or services we'd like to purchase. If we can't find what we want, we simply navigate away without a trace. This is one reason why online marketing suffers from lacklustre conversion rates.