CA has become an early-stage investor in Melbourne-based Sonnant Pty Ltd, a transformational artificial intelligence (AI) and machine learning (ML) company that provides content discovery for the spoken word. 

According to the GfK Australian Share of Audio 2019, consumption of digital audio is growing in Australia and is expected to reach 80% of the population by 2024 and SCA’s recent launch of LiSTNR is designed to be a best in class consumer digital audio experience. 

SCA’s in-house technical capability will be enhanced by Sonnant’s AI intelligence, providing an in-depth of understanding of SCA content that allows for rich meta data and exciting new user experiences. 

Sonnant allows SCA to enhance the key product pillars of LiSTNR delivering a personalised experience to each user based on the topics they most enjoy listening to.

SCA Head of Digital and Innovation, Chris Johnson, says “SCA is a proud supporter of the Australian entrepreneurial ecosystem, so when we found a company of Sonnant’s calibre in Melbourne, we knew that an investment partnership would provide significant long term value to both parties.

“We were delighted when Sonnant’s tech outperformed several ‘off the shelf’ products we pitted it against in testing. Even better that they were right in our own backyard! The partnership demonstrates our commitment to not just delivering engaging digital products but building the technical capabilities that power market leading platforms today.” 

Sonnant CEO, Tony Simmons (pictured right), says: “Technology now allows us to do things with the spoken word that was merely science fiction a few short years ago. Sonnant has long recognised that the consumption of audio, especially the need for better audience discovery of relevant content with podcasts, can greatly benefit by our exacting AI processes.  

“Importantly, by applying Sonnant’s machine learning, SCA will reduce manual processes and SCA customers and advertisers will experience more precise results in a shorter period of time. We are very excited for the opportunity to work with Australia’s pre-eminent media organisation to create even better listener experiences and a high degree of engagement.” 

The post SCA invests in Australian AI and machine learning company appeared first on Artificial Intelligence.

Summary

• The company has developed a security robot named ROAMEO and is valued at more than $700 million as of time of writing.
• However, the latest quarterly revenues were less than $0.12 million and Artificial Intelligence Technology Solutions is losing money.
• What’s worse, it has a negative working capital of $15.7 million as well as various convertible notes with interest rates of 10% and above.
• The main driver behind the company’s soaring share price seems to be high retail investor interest, which emerged a few weeks ago.
• I doubt the business is worth much considering the weak revenues and balance sheet.

Introduction

I’ve noticed that there’s significant interest from SA subscribers in my articles on OTC companies that are popular with retail investors, such as Tesoro Enterprises (OTCPK:TSNP), Viper Networks (OTCPK:VPER) and Healthier Choices Management Corp (OTCPK:HCMC).

In light of this, I thought it’s worth taking a look at Artificial Intelligence Technology Solutions (OTCPK:AITX), which is currently one of the most traded companies on the OTC market. It’s an artificial intelligence company with an interesting business focused on security robots.

However, Artificial Intelligence Technology Solutions is unprofitable and the business looks worthless, considering the working capital is negative. I think this one is a sell.

Overview of the business

Artificial Intelligence Technology Solutions specializes in robotics and artificial intelligence-based hardware and software solutions. The company has several subsidiaries, including Robotic Assistance Devices, Robotic Assistance Devices Group, Robotic Assistance Devices Mobile, On the Move Experience and OMV Transports and its main products include security robots such as ROAMEO.

The company claims it has secured USD 16mn in conditional pre-orders on this product alone. The first ROAMEO unit was deployed in October 2020 and the client was an unnamed Fortune 500 firm.

In January, Robotic Assistance Devices announced that it entered the European Union market after receiving an order in Romania for two units.

Some of the other products in the portfolio of Artificial Intelligence Technology Solutions include a gate control system called AVA.

The products of Artificial Intelligence Technology Solutions certainly sound interesting but my concern is that they have limited market potential.

Looking at the company’s financials, revenues stood at just $0.12 million in the quarter ended November 2020. While the gross profit margin was impressive at almost 80%, the company booked a $0.9 million loss from operations due to pretty high general and administrative expenses for such a small business.

The balance sheet also looks bad as assets stand at just $0.7 million and working capital and book value are deeply in the red.

The company has a significant amount of convertible notes, which I think don’t have favorable interest rates and conversion rates.

Retail investor interest

One interesting thing that I noticed about Artificial Intelligence Technology Solutions is that its share price has recorded several short-term spikes over the past five years.

The latest one started around the end of December 2020 and shares have risen 598% in 2021 as of time of writing.

Just like the other three OTC companies I’ve covered in the recent past, Artificial Intelligence Technology Solutions has attracted significant interest from retail investors. On Twitter alone, there is a new tweet with the $AITX hashtag every few minutes at the moment. The company also seems to be popular on websites like Stockwits as well as reddit. Its own subreddit was created on December 30 and it has 3.7k members as of time of writing.

I think the company is doing an excellent job on the marketing front and you can find several recent interviews with its president Steven Reinharz on YouTube. Also, Reinharz’ profile on twitter features the #RADArmy tag, which has picked up traction on social media platforms over the past month.

Investor takeaway

Artificial Intelligence Technology Solutions has interesting products and I think the company is doing an excellent job of promoting its business and shares, especially on social media platforms.

However, the company is valued at over $700 million as of time of writing and I think this valuation is very hard to justify. Looking at the latest available financials, revenues are low and the Artificial Intelligence Technology Solutions is losing money. What worse, it has a negative working capital of $15.7 million and the book value is negative. I think this company isn’t worth much and it’s a sell.

The only scenario I see in which the bear case could be wrong is one in which ROAMEO becomes a revolutionary product in the security space. I view this as highly unlikely.

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Few areas of the corporate world are fraught with the conflicting objectives found in employee health. Company health plans are designed to maintain employee health. Healthy employees are more productive. And generous health coverage bolsters recruitment and retention, a key goal in the zero-employment economy.

But benefits are also a nagging cost center. And many employers are uncertain about the legality of analyzing the health data their plans create.

How to balance these often conflicting priorities?

Enter the latest potential solution: data mining platforms and consultants.

Data warehouses are nothing new. That’s where employers first turned when they needed a black hole in space to store the enormous bits of data generated every minute of the work day. But now, as the Big Data industry rushes ahead, driven by its own data, employers suddenly have myriad options for managing and mining those bits stashed away on the cloud. The question is: How do I get the answers I need from my data in a timely fashion with actionable recommendations? Oh, and without running afoul of privacy concerns?

That’s where vendors like Springbuk, Segal Group, Artemis Health and others come in. Their promise to employers: We’ll help you quickly find out what you’re looking for in your data. And we will also bring to your attention trends and issues you didn’t know existed that can generate a better return on your health plan investment.

Employers are signing on for these services despite concerns about just how deeply they can mine health data. A recent Accenture survey found that only 30 percent of respondents were “very confident that they are using new sources of workforce data in a highly responsible way.” But 62 percent said they were already “using new technologies and sources of workforce data today,” and three-quarters were eager to analyze their employee data to grow and transform their businesses, and to unlock their employees’ full potential.

And apart from legal protections around privacy, which remain uncertain, workers don’t seem to be fearful of the Big Data/Big Brother syndrome. More than 90 percent of employees responding to the survey said they were fine with collection of personal data, as long as it “improves their performance or well-being or provides other personal benefits.”

Connecting with employers

Platform builders are finding two routes to employers: Directly to them through their sales teams, and through broker channels. Says Springbuk’s Reasen, “We do believe in the value proposition of the broker model. They represent a strong advocacy at the local level that still exists. They like to be able to offer a tool like ours to get into data warehouses and analyze what’s there for their clients.”

Springbuk just unveiled an upgrade of its health intelligence platform that its executives say will both greatly reduce the time required to mine specific intelligence from health data, and provide clients with customized, curated data-based reports on topics ranging from risk mitigation, care efficiency and drug savings, to steerage procedures and potentially unnecessary procedures.

The upgrade further enhances the platform’s ability to identify members within a plan population “who are at risk of developing health conditions and then get actionable information including appropriate treatment, disease management resources and risk mitigation strategies. At-risk employees are identified based on a proprietary algorithm using a database of existing claims,” the company says.

In other words, the platform both responds rapidly to employer queries about employee health, and anticipates, explores, and issues reports on trends that clients may not be aware of.

“The message around health intelligence, as opposed to health data, is resonating with employers,” says Springbuk’s Rod Reasen, CEO and co-founder. “I just got off a call with a very large organization that represents hundreds of thousands of lives. They want to know why they bought a data warehouse. ‘We thought we’d have access to a lot o f information. but actually it’s just access to a lot of data.’ Our health intelligence platform goes beyond a data warehouse to provide actually actionable intelligence.”

“It’s a question of data mining versus data reporting,” says Segal’s David Searles, vice president and the executive who developed Segal’s data analytics business. “Data mining creates new information from the data. The mining can say, for example, that you have 20 percent of your diabetics who aren’t getting their tests done. It is creating new actionable information from the data you are presented with.”

Data-driven decisions

These new platforms can swiftly adapt to shifting priorities among employees. As opioid abuse continues to take a toll on employee health and the cost of insurance, Segal was asked to examine one client’s population to identify total savings potential for opioid abuse prevention management.

“The client wanted us to quantify enhanced opioid criteria savings to medical and prescription drug programs,” he says. “We analyzed the data and discovered that, by limiting first fills of opioid prescriptions to a 7-day supply, ER-related opioid visits decreased 35.3 percent.”

Demand is strong to mine employee data to evaluate workplace wellness programs. Generally, employers want to reduce their wellness offerings to those programs that engage employees and produce better health outcomes.

“We get a lot of requests to examine the data for return on investments in various programs, both wellness or disease management. While you can’t really do an ROI accurately–no one agrees on a consistent methodology for it–you can determine the effectiveness of the program by looking at the change in biometric data of the participants,” Searles says.

“What we are pushing toward is this: Plan sponsors should use data to actively manage their health plans. They should evaluate their employee profiles. Let’s target a program that addresses conditions that are driving trends.”

One example would be designing a treatment plan for diabetics with coronary disease. “They should be highly motivated and will incur large claims if they don’t improve their condition,” he says.

But first, the company needs to know whether its workforce includes enough diabetics with coronary disease to justify creating such a program. And that’s where the emerging data mining platforms shine.

The new mining platforms have immeasurably reduce the time required for an employer to find the desired information. Springbuk’s Reasen says the chief medical officer for one client told him “it would have taken him a month to come up with the exact [report] we came up with in seconds.”

He adds: “When a user steps in front of a data warehouse, we are asking them to spend time and use their knowledge to extract information. We all have the same amount of time. How do we use it?”

Strategic benefits firm Sequoia Consulting Group is a Springbuk broker client. CEO Greg Golub says his clients especially value the executive reports the platform produces.

“Springbuk is very effective at producing executive reports, tailored for the CFO or HR leader. They do a good job of synthesizing the information into an actionable report. They are focusing on the right stuff.”

Sequoia’s chief marketing officer, Michele Floriani, says being able to offer Springbuk reports to clients has led to positive feedback. “We offer it as a service to our self-insured clients and together we make use of the output and insights to make annual and longer term strategy decisions on plan design. It’s really wonderful. That’s the value to us. It focuses on what matters to the client.”

The post Digging deeper: Health data mining platforms surge ahead appeared first on Artificial Intelligence.

A former executive from payment platform PayPal has launched a new deep learning health intelligence platform, Global Care Analytics, to provide claims-and-cost clinical data and predictive analytics for healthcare companies.

The company’s president, Scott Guilfoyle, formerly served as CTO of PayPal, as well as CIO of LendingTree, and other major companies. The move underscores the growing interest in the AI in healthcare space and the emergence of more companies leveraging AI to solve healthcare management issues.

“The CEO, COO or CFO can execute precisely targeted, complex queries on massive data sets with real-time or near-real-time responses by dragging and dropping preset queries into the engine,” Guilfoyle said of the company’s platform. “We have a patented hyper-ingestion engine that can take in a million datasets a minute, which is amazingly fast and accurate. Then our hyper-digestion process uses neural networks to analyze the oceans of data and become more and more accurate as it learns to refine its ability to make connections.”

One of the goals of the founders was to leverage healthcare data that is currently underutilized and “trapped” within organizations, according to CEO Kevin Sullivan.

“When executive management has desktop power to identify gaps in care or delivery of care services, outcome metrics, and the most complete real-time picture of the health of their patient populations, they can speed up more knowledgeable decision making,” he said.

According to Guilfoyle, the company, which plans to follow the analytics technology with Global Care Pay to provide a frictionless billing-claims-reimbursement system, could help eliminate waste in administrative duties, which add up to $147 billion to $510 billion.

The company, Global Care Administrators, is two years old and is raising capital.

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The impact of automation in the workforce extends far beyond any individual employee, organization or even industry. As artificial intelligence advances and companies adopt this technology, we’re beginning to see an economic shift.

In 2017, JPMorgan estimated that automation has the potential to increase global gross domestic product by more than $1.1 trillion over the next 10 years. Meanwhile, according to Bloomberg (paywall), PwC predicted that AI could add up to $15.7 trillion to the worldwide economy by 2030. While there’s a huge discrepancy between these projections, I believe the underlying message is clear: Automation is a major factor in the future of global economic growth.

And yet, some experts are anticipating an “AI winter,” a period when investments and developments in AI begin to slow down or stall. Although I’ve observed some success in funding AI in various ways — such as coding boot camps and computer science degrees in an effort to close the skills gap — we haven’t seen the complete payoff we’ve expected. AI still has biasproblems; deep learning still gets stumped by simple, if unexpected, variables; neural networks are far from the point where they can be consistently leveraged strategically for business.

As a serial AI entrepreneur, I’ve made it my goal to dedicate enormous resources to research and development for machine learning and AI, and I’ve been able to build tech companies that do the same. Although some do not agree we are approaching an AI winter, from my perspective, as the economy comes to increasingly rely on more sophisticated machines, we can confront a potential plateau of AI development by training machines as an industry and providing more education to those creating the technology.

Education Reform For AI

In my experience, most of today’s AI developers are constrained by the mandate to automate. As a result, machines can become products of what I call “teaching to the test.” They can do singular tasks incredibly well, given incredibly narrow conditions.

When AI has to go off-script, so to speak, it struggles. For example, tech company DeepMind was working to develop AI that would function as a world-class Breakout player. But according to Wired, what they found in this initial brush with gaming AI was that the “seemingly supersmart AI could play only the exact style of Breakout it had spent hundreds of games mastering.” Even the smallest change to the game mechanics or layout caused the whole thing to break.

My point is that the majority of AI today doesn’t have critical thinking skills or common sense. Instead, it’s been designed to succeed through sheer rote memorization. It’s processing information to give an answer or action, but it’s not actually understanding what’s happening.

To address this, I believe tech companies need a playbook for research and development to prepare themselves for the next wave of innovation. And although there’s no canonical curriculum for training AI, there are a few key steps executives can take to ensure they are investing in AI education the right way:

Hire strategically.

Perhaps most importantly, it’s crucial that organizations hire the right people. Staffing for AI isn’t easy. Ensuring your recruits have the right technical chops can be expensive, but it’s worth it. Look for employees who have a history of dedicated curiosity. Have they published research? Are they interested in continued education? I believe AI developers who are equal parts programmers and researchers are the most valuable asset a tech company can have. Organizations that can recruit and keep this talent will find that they are suddenly the owners of valuable IP because their new AI hires are able to devote themselves to experiments and training the tech, rather than learning the skills for the job.

Enable your entire team to become more AI-literate.

Of course, as organizations seek to hire for positions that will become the bedrock of their tech strategy, I suggest that executives consider investing other company resources in support. Make your organization more competitive in its hiring by acquiring or collecting diverse and interesting data sets. There’s so much data out there, and extracting some of that data can help you determine what’s possible. For example, you might pull data from hundreds of automated bots and then synch them to create immediate, actionable insights. This means that you might have to spend more time at the collection phase, and your data sets might have to be larger as you conduct additional research to fill in any holes.

Additionally, incorporate AI training into your company’s professional development cross-departments. I believe the workforce of the future depends upon AI leadership and literacy. It’s predicated on the idea that everyone can contribute to AI’s teachings. This doesn’t mean teaching everyone in your organization to code. In fact, quite the opposite. Keep your lessons high-level and even philosophical. You’ll know you’ve succeeded if everyone in your organization can explain how AI gets trained, how it could be applied to a situation and — this is just as important — why it might fail.

The Future Of Company Success

Already, I’ve seen some companies commit the necessary resources for research and development projects in an effort to train AI to think about the challenges it’s presented with. Other companies considering doing the same should earmark resources purely for research and development in AI without the end goal being a breakthrough in automation. Make it clear that the underlying mission of your research teams is to push the bounds of your technical understanding — not push out a product. 

This shake-up in educating AI will unlock solutions we never dreamed possible. After all, the real value in AI comes from the bigger, new ways of thinking that it illuminates for us — the new patterns and wild ideas that only a machine, powered by tons of data and a healthy dose of common sense, could come up with.

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Joe Lonsdale said on CNBC on Monday that his fellow Palantir co-founder Peter Thiel was “courageous” for speaking out against Alphabet’s Google.

“Google is not a patriotic company,” said Lonsdale, also a founding partner of technology investment firm 8VC.

Lonsdale was responding to the criticism levied since Thiel on Sunday said the FBI and the CIA should investigate whether Google has been infiltrated by Chinese intelligence.

Thiel, also a Facebook board member and a supporter of Donald Trump’s 2016 presidential campaign, was speaking at the National Conservatism Conference in Washington, D.C., and Axios reported on his speech.

“Everyone in [Silicon] Valley knows that the Chinese government is very involved,” Lonsdale told “Squawk Alley” in an interview, though he didn’t point to any clear evidence. “It’s something we don’t talk about a lot. It was very courageous of [Thiel] to talk about it.”

Google, responding to Thiel’s comments, said, “As we have said before, we do not work with the Chinese military.”

The environment at Google is very “academic,” Lonsdale said, where people want to share their work across the world. “There’s nationalists in China coming and taking whatever they can learn and taking it back and using it for their own nationalist purposes.”

Lonsdale also commented on Google’s contract with the Defense Department, which expired earlier this year and was not renewed. “When Google made the choice ‘we’re not going to help the U.S., but we’re going to continue to work in China,’ it was very clear,” Lonsdale said of the company’s patriotism.

Silicon Valley-based Palantir, the data analytics miner, has worked with many agencies of the U.S. government, including the Defense Department, CIA and FBI. Lonsdale on Monday called Palantir “probably the most patriotic in the Valley.”

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Determining a job candidate’s potential for success is a difficult task. In the past, hiring managers looked to people’s intelligence quotient (IQ) to gauge whether they would bring value to their organizations. Now, however, emotional intelligence (EQ) is seen as an increasingly relevant predictor for success.

The post Emotional Intelligence is the Key to a Successful Company Culture appeared first on Artificial Intelligence.

There’s no doubt that artificial intelligence (AI) is a transformative technology – perhaps even the most transformative technology available today. But if you think the transformative nature of AI is limited to global tech giants and blue-chip companies, think again. AI is ultimately going to transform every business, in every industry.

That’s why every company needs an AI strategy.

Like any business transformation, if you want to get the most out of AI, it all starts with strategy. Your AI strategy will help you to focus on your core business objectives and prioritise ways that AI can help deliver those business goals.

In general, there are two ways businesses are using AI to drive success:

• Creating intelligent products and services
• Designing intelligent business processes

Let’s look at these two uses in a little more detail.

Intelligent products and services 

AI is, at heart, about making machines smarter, so that they can think and act like humans (or even better). We need only look at the popularity of devices like smartphones, smart fitness trackers and smart thermostats to see how consumers wholeheartedly embrace products and services that can make their life easier, smarter, more streamlined, more connected.

So it’s no wonder that businesses are increasingly looking for ways to make their products and services more intelligent through AI. Google’s search algorithms are an obvious example of an AI-driven tool. Amazon’s Alexa is another. Social media platforms also rely heavily on AI.

Chinese company ByteDance is, at the time of writing, the world’s most valuable startup. If you haven’t heard of them yet, you soon will. ByteDance product TikTok was one of the most downloaded apps of 2018. (If you’re wondering, it lets users create and share short videos.)

Another ByteDance product is Toutiao, which, thanks to its combination of the search engine, news and social media, is often referred to as ‘Buzzfeed with Brains’. Unlike Facebook and other social media platforms, Toutiao doesn’t generate news feed content for its users based on who they’re following; it uses AI to display a continuous stream of content that’s based on what the platform believes that user wants. In other words, it gets to know you as a user and recommends content based on what it believes you like and don’t like.

Setting aside these obviously techy examples, AI is also being used to produce smarter versions of far more traditional products. Vehicles, for example, are now much smarter than they were 10 years ago and can perform a range of tasks autonomously, from perfect parallel parking to alerting a driver who’s starting to nod off at the wheel. More and more vehicles can drive autonomously, as well.

Even Barbie has had a smart makeover. The Hello Barbie toy uses natural language processing and machine learning (both subsets of AI) to listen and respond to a child. Inside Barbie’s necklace is a microphone that records what the child says and transmits it to a server for analysis. Then, choosing from 8,000 dialogue options, the system chooses the most appropriate response for Barbie to say. All this happens in under a second.

What’s more, Barbie remembers useful information from conversations, such as the child’s favourite food or favourite pop star, to use in later conversations. In effect, Barbie learns what your child likes and dislikes, so she can hold more intelligent conversations. Creepy? A little, yes, to my mind. But it goes to show how even the most unexpected products are becoming smarter.

Intelligent business processes 

AI is being used to help businesses across all sectors optimise and automate business processes. This can be as simple as automatically recommending product B to every customer who bought product A, based on the preferences of other customers. Or it can be as complicated as fully automating an entire production line. For most companies, the biggest AI opportunities lie somewhere in the middle.

For example, credit reference agency Experian is using AI to crunch through its masses of data and make quicker, smarter decisions on credit scores and so on. American Express is doing a similar thing by using AI to detect fraudulent transactions in pretty much real time.

Predictive maintenance is another example of AI-optimised processes. This involves using sensors to constantly monitor vehicles and machinery to predict when parts might fail. (The idea being that, if you know when something is likely to fail, you can replace it beforehand and minimise downtime.) Volvo is using this technology to predict part failure and provide more accurate information on when vehicles need servicing.

Thanks to natural language processing and generation, machines can also be used to communicate with customers. In fact, customer service chatbots and messaging chatbots are now pretty much mainstream. But did you know that AI can also be used to generate longer, more specialist content? In the UK, the Press Association has partnered with news automation company Urbs Media to get robots writing thousands of news articles each month.

Finding the right AI use for your company

The right use for you will depend on what your business is trying to achieve. That’s why your AI strategy (here is an AI strategy template) must be driven by your overarching business strategy. So before embarking on an AI strategy, it’s vital you review your business strategy first.

Then, when you’re crystal clear on the business’s organisational goals, you can start to look at ways AI can help you achieve those objectives. To help you define your AI use cases for your business, using an AI use case template.

The post Why Every Company Needs An Artificial Intelligence (AI) Strategy For 2019 appeared first on Artificial Intelligence.

Technology is on a linear incline. Apple released its newest line of iPhones in the fall of 2018, with Samsung following with its Galaxy 8As. Amazon created Alexa, similar to Siri but more focused on the home. There are various technological creations and advancements made every year by private corporations throughout the world. Eventually, improvement in the technological realm will slow down and stand still. When technological advancement will hit a plateau is unknown, but the creation of artificial intelligence could help determine it.

Artificial intelligence, also known as AI, exists in the present. Merriam-Webster defines AI. However. the level in which the robot exists still remains questionable. The film “Ex Machina,” which is Latin for “a god from a machine,” just how unfathomable the capabilities of technology can be. The movie previewed what a self-aware, AI-operated machine looked and acted like. Self-aware AI-operated machines in the movie was able to draw pictures, carrya conversation with a human, be aware of a human’s emotions and dress itself.

There are a lot of questions that come with the possibilities of artificial intelligence. If AI machines can behave like humans, they can begin to replace their jobs as well. Unless regulations were put into place to prevent AIs from taking jobs, there would be few big businesses willing to hire human workers for specific work. There are examples of work that has already been replaced by robots and as long as technology grows, artificial intelligence will continue to as well. Fortunately, many scientists and engineers believe AI will never be able to replicate human judgement.

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