Artificial intelligence is increasingly moving from research labs into everyday clinical workflows, and prenatal imaging is one of the latest areas to see rapid innovation. DeepTech company Diagnoly has announced the launch of its real-time fetal ultrasound AI assistant, Fetoly, on iOS, expanding global access to AI-assisted prenatal care.

Already deployed in more than 20 countries, the new iOS release allows obstetricians, maternal fetal medicine specialists, and sonographers to run the application directly on an iPad, connecting seamlessly to existing ultrasound systems without requiring additional hardware or upgrades.

This marks another step in the broader trend of AI moving into mobile, interoperable healthcare tools that integrate directly into clinical workflows rather than requiring entirely new systems.

AI As A Second Set Of Eyes

Fetoly AI analyzes fetal ultrasound scans in real time, helping clinicians verify anatomical landmarks and examination completeness

Fetoly is designed to function as a real-time ultrasound assistant, continuously analyzing the full ultrasound video stream during fetal examinations. The system helps verify that examinations are complete by identifying anatomical structures and can highlight suspicious findings through automated measurements, while keeping clinicians fully in control of the diagnostic process.

According to Diagnoly, the goal is not to replace clinicians but to provide a second layer of analysis that improves consistency, efficiency, and diagnostic confidence.

Fetal ultrasound is widely considered one of the most operator-dependent imaging procedures in medicine, with outcomes often influenced by the experience of the practitioner and the clinical environment. AI-assisted analysis has the potential to reduce variability and help standardize examination quality across healthcare systems worldwide.

Running Locally, Not In The Cloud

One of the notable aspects of Fetoly is that it operates locally on the device rather than relying on cloud processing. This approach helps address data security and privacy concerns while also ensuring the application can function reliably in clinical environments without constant internet connectivity.

This local-processing model is becoming increasingly important in healthcare AI, where data privacy, regulatory compliance, and workflow integration are critical factors for adoption.

Expanding Clinical Capabilities

The latest version of the application includes improvements in real-time performance and anatomical detection, as well as new automated measurement ratios that assist in detecting conditions such as:

• Ventriculomegaly
• Corpus callosum abnormalities
• Total anomalous pulmonary venous return (TAPVR)

These updates are delivered through regular software updates, allowing the system to continuously evolve and improve clinical support without requiring new hardware.

The Rise Of Mobile Medical AI

The launch of Fetoly on iOS reflects a broader shift in medical technology toward mobile, AI-powered tools that can run on tablets and portable devices. Instead of large centralized systems, many healthcare AI tools are now designed to work alongside existing equipment, making adoption faster and more cost-effective.

This trend is particularly important for prenatal care, where access to specialist expertise varies significantly across regions. AI tools that support clinicians in real time could help improve diagnostic quality and access to care globally.

As demand continues to grow for intelligent imaging tools and AI-assisted diagnostics, solutions like Fetoly highlight how artificial intelligence is increasingly becoming embedded directly into everyday clinical practice rather than remaining a separate technology layer.

The post Bringing AI Into Prenatal Ultrasound appeared first on Tech Trends.

Democratizing Animation

Marketers know that few tools are as effective in engaging your audience as a well-crafted animation. Traditionally, however, this type of material has been extremely labor-intensive – and therefore costly – to produce.

Yet LottieFiles is a company looking to change all that with its open-source tool that allows animators to spend less time learning and deploying complex code and more time crafting captivating content that will wow users and increase conversion rates.

LottieFiles allows designers to spend less time learning and deploying complex code and more time crafting captivating content
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Lottiefiles is a lightweight, interactive, and scalable animation format that allows for customization without having to code, build and render bulky files from scratch. In fact, Lottie files are, on average, 600% smaller than other popular animation formats such GIFs, allowing for a much faster, more responsive, and therefore engaging user experience (UX).

Lottie files are on average 600% smaller than GIFs, allowing for a much faster, responsive, and engaging user experience
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Popular apps such as Airbnb and Duolingo have wholeheartedly embraced this user-friendliness. Use cases for Lottie animations range from app loading and wait screes to gamification and user onboarding, as well a vast array of websites and apps looking to serve meaningful content to their users, according to LottieFiles CTO Nattu Adnan

“LottieFiles has helped hundreds of thousands of developers and designers from over 65,000 global fortune companies like Netflix, Disney, Google and Amazon to ship interactive animation faster and more effectively,” adds the company’s Co-Founder and CEO Kshitij Minglani.

Augmenting Reality

AR (Augmented Reality) has been steadily gathering momentum in recent years, and it is easy to see why. Merging the physical and digital worlds is an exciting proposition that opens up a whole world of possibilities for users, and the companies hoping to reach and keep them engaged.

From new ways of experiencing art to enabling customers to realistically try products before committing to a purchase, Augmented Reality is becoming ever more pervasive across an incredibly broad swathe of industries.

Augmented Reality is becoming ever more pervasive across an incredibly broad swathe of industries.
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“Research shows that AR will evolve from one-off ‘surprise and delight’ moments to provide everyday utility and practical value, right across the consumer journey.  This could include helping people visualize how products look in their home, locating products in-store through wayfinding applications, or getting more out of a product post-purchase through usage guidance,” explains Jeremy Pounder, Futures Director at Mindshare UK

One example of how it is possible for innovative companies to bring their customers the best of both worlds by creating Omnichannel experiences is Canadian start-up StickerYou which offers customized, die-cut stickers online, but also maintains a physical shop where customers can touch and feel the merchandise.

“The broader trend in retail, particularly among millennials, is a shift in focus from products toward experiences. For this reason, many customers still choose to visit a physical shop even if it may be more convenient to order the item online, explains StickerYou Founder and President, Andrew Witkin. “For retailers, this presents an opportunity to leverage technology to literally augment the value of their products for their customers,” he concludes.

Meeting Virtually

Even before the COVID-19 pandemic became the catalyst for what we now know as a socially distanced “new normal,” technology had been pushing us towards having more of our interactions in virtual environments.

From virtual live comedy shows to professional poker tournaments, people had started to not only accept the premise of hosting their familiar interactions and experiences in immersive virtual worlds.

Technology has been pushing us towards having more of our interactions in virtual environments
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Given the continuation of the pandemic, however, we have seen most events in the global conference calendar going virtual in some way or another, including one of the biggest highlights in the tech circuit – South by Southwest (SXSW) which is held in Austin, Texas in March.

SXSW Online 2021 included a variety of online meetings, sessions, musical performances, and many attempts at virtually recreating the interactive experience of SXSW.

As Tech Trends correspondent Laura Kobylecky reports, the world of virtual Austin exists within VRChat, an online, virtual reality, social platform which added a layer of immersion and interactivity to this year’s online conference and left her feeling as if she’d really attended the event.

Tech Trends’  Consultancy services offer support for companies looking to enhance their brand’s digital strategy with immersive and emerging technologies such as Virtual, Augmented and Mixed Reality

Alice Bonasio is a technology journalist, communications consultant and Tech Trends’ Editor in Chief. Connect with her on LinkedIn and follow @alicebonasio and @techtrends_tech on Twitter.

The post Top UI/UX Trends for 2021 appeared first on Tech Trends.

A Deloitte survey revealed that most companies – a staggering 90 percent of those approached by the research and consultancy firm – consider cognitive technologies to be of crucial strategic importance, and over 80 percent of those were either already using it on some level or planning to implement it in the near future.

That is hardly surprising considering the dramatic efficiency savings that adoption can bring. According to Bill Eggers, executive director of Deloitte’s Center for Government Insights, in the U.S. alone, federal employees spend about 4.3 billion hours per year on a variety of mundane tasks such as recording information and handling. He estimates that currently available AI and robotic process automation could free up about 1.3 billion of those hours by automating such tasks, effectively enabling quantum leaps in productivity as AI allows institutions to anticipate rather than merely react to problems after they occur.

Yet in spite of its pervasiveness, and the fact that it has been around for many decades, AI still falls, paradoxically, in the “emerging technology” category. One that constantly presents new facets and developments that bring us ever closer to the worlds imagined by the likes of Isaac Asimov.

And what also emerges as such technologies mature are sub-categories that address their more specific applications, to the point where it makes as little sense to refer to AI as a single entity as it would to bundle all computers into one homogenous category.

So we turned to industry stakeholders for help in defining three of these major branches of AI-assisted, augmented, and autonomous intelligence – and to provide some practical examples to help us understand their current (and future) applications.

Assisted Intelligence

Assisted Intelligence is a basic level of AI that primarily consists of automating repetitive and mundane tasks and procedures. This – at least in theory – frees up humans to perform more complex and creative assignments, enabling efficiency savings by allowing paid employees to focus on high-value tasks that are not so easily automated.

In order to work well, assisted intelligence requires clearly defined input and output parameters, and is most useful in applications such as monitoring and producing alerts and directions, which can then be checked by an actual person. Typical applications for this type of AI include GPS navigation programs and manufacturing robots.

Augmented Intelligence

Augmented intelligence, as the name suggests, augments and supports – rather than replaces – human intelligence, yet it is more complex and versatile than the basic assisted AI we described above.

This is a symbiotic relationship where humans and machines ideally learn from one another and work collaboratively by layering machine learning over existing human systems to accelerate and improve accuracy of those human-led processes. In other words, it enables us, at least in theory, to make better and faster decisions than we would otherwise.

Among the models included under this umbrella are machine learning, natural language processing, image recognition and neural networks, with typical use cases encompassing healthcare, public safety, and fraud detection.

Autonomous Intelligence

Autonomous intelligence allows machines, bots and systems to act independently of human intervention. This is the most complex form of AI not only in terms of the technology itself and its implementation and effectiveness but of the moral implications of effectively handing over decision-making to machines. What accountability frameworks are needed if we are indeed to pursue that path? It is, quite simply, the fascinating and scary realm of science fiction, except that reality is rapidly catching up, and it remains to be seen whether the dystopian visions presented in The Matrix or Terminator franchises will come to life in some form.

“What happens when humans cannot establish all the constraints, boundaries, and limits, because of our lack of vision and imperfections as human beings?” asks Lucas Werthein, Co-founder and Head of Technology at Design Innovation firm Cactus. “Machines can go through all potential scenarios in seconds, but we as humans cannot necessarily create boundaries for things we don’t know,” he explains, citing a fascinating study which demonstrated how AI is capable of adapting in ways which can be utterly baffling to humans.

An AI Spectrum?

These definitions essentially help us envisage the different levels of interaction between humans and machines. They answer the question of how much autonomy and agency does (or should) AI have.

Yet although defining categories is helpful on some levels, the lines between them are not usually well defined, nor do they remain static. It is perhaps more appropriate therefore, to think of them as a spectrum or continuum rather than attempting to pigeonhole use cases into one category or another.

Josh Browning, machine-learning architect at AMP Robotics, agrees that it may be more accurate to view these categories in terms of progression. “AI often starts in the simplest phases (assisted) and progresses to a fully autonomous phase. This is more of a spectrum, rather than individual examples that fit into each category. For example, consider spam filtering. The initial application will be simple and rules-based: filter emails as spam if they have all capitalized titles, many misspelled words, etc. As data is collected, it moves into the range of augmented intelligence: the application can make reasonable decisions on its own, but requires human feedback to continue to learn. Once it has achieved a certain level of performance, it may be moved into the final category of being fully autonomous,” he concludes.

The usefulness of establishing a common lexicon for technologies like AI is that it enables us to have more constructive conversations about them, and perhaps be better equipped to deal with the hurdles and pitfalls along the way.

As Mike Nager, Business Development Manager at Festo Didactic, says, the path forward is not likely to be hindered by technological progress, but rather by how well society accepts further non-human interactions and how the regulations and laws keep up, to both allow beneficial technologies to flourish while safeguarding human life and privacy.

And it is that human touch that we must not lose sight of, according to Benjamin Cox, Director of Product Marketing at H2O.ai.

“By keeping humans in the loop, companies can better determine the level of automation and augmentation they need and control the ultimate effect of AI on their workforce. As a result, enterprises can massively mitigate their risk and develop a deeper understanding of what types of situations may be the most challenging for their AI deployments and machine learning applications,” he concludes.

This article was originally published in Futurithmic

A @DeloitteInsight survey revealed 90% of respondents consider cognitive technologies to be of crucial strategic importance.
Learn more about the different forms of #AI: https://t.co/HHuhwH8NsL pic.twitter.com/Z22UKZgCvJ

— Futurithmic (@futurithmic) September 14, 2020

Tech Trends offers a broad range of Digital Consultancy services to guide companies, individuals, and brands in effectively leveraging existing and emerging technologies in their business strategy.

Alice Bonasio is a XR and Digital Transformation Consultant and Tech Trends’ Editor in Chief. She also regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. Connect with her on LinkedIn and follow @alicebonasio on Twitter.

The post The Many Flavours of Artificial Intelligence appeared first on Tech Trends.

By Margaret Heffernan

The hard truth is that much in life is, and always will be, unpredictable – and we’re better off accepting that than falling for propaganda
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“We can win a complete victory over this virus,” Zhang Hanhui, the Chinese ambassador to Russia, recently declared, adding that in Hubei, “the disease will be liquidated next month”. This is propaganda masquerading as prediction, as it often does. People fall for it because predictions like this are comforting, even when they’re wrong. But it’s fear, not his knowledge, that makes anyone believe him. The hard truth is that much in life is, and always will be, unpredictable – and we’re better off accepting that than falling for propaganda, however optimistic it might be.

They might all look the same , but there is no predictive profile of an epidemic
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Epidemics are scary because they don’t follow predictable patterns. They might look the same but there is no predictive profile of an epidemic. There is just one certainty: that they will break out. After that, uncertainty rules: we don’t know what disease, in what country or when. New strains of diseases appear constantly; since the 1970s, new pathogens have been emerging at an unprecedented rate of more than one per year, and in a world of global travel, they move fast. Different geographies need different kinds of response. What works in one place, with one disease, might not work somewhere else. So these crises take us by surprise, even when we know something is coming.

What works in one place, with one disease, might not work somewhere else. So these crises take us by surprise, even when we know something is coming
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Technology can help, of course – not in predicting epidemics but in identifying them fast when they start. Artificial intelligence created by the Canadian firm, Blue Dot, analyzed masses of data on animal and plant disease outbreaks, together with global news reports, and was able to identify the outbreak of what has become known as COVID-19 a full week before the Center for Disease Control announced the appearance of a new flu-like disease.

Applying AI to global flight data generated accurate predictions about where and how the disease would spread
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Applying AI to global flight data also generated generally accurate predictions about where and how the disease would spread. Because treating epidemics is always a race against time, this represents a meaningful improvement in speed once an infectious disease has emerged. Like all applications of AI, it is only as good as the data on which it is based, which in epidemics can be tricky because each one is unique. Scientists and health care workers are still needed to analyze findings and diagnose patients. And AI doesn’t change our inability to predict epidemics before the pathogen shows up.

Technology can help, not so much in predicting epidemics but in identifying them fast when they start
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Spotting the outbreak is just the beginning. The holy grail in every epidemic is a vaccine to stop a disease from spreading. The development of vaccine candidates is time and labour-intensive and also unpredictable; many fail. The Coalition for Epidemic Preparedness began work on new vaccines for beta coronaviruses in 2016, so they aren’t now starting from scratch. The speed of genome mapping has hugely accelerated vaccine development so that researchers already know the genes and the molecular structure of the protein that gets the virus into human cells. Sharing that information with research teams around the world accelerates discovery.

AI doesn’t change our inability to predict epidemics before the pathogen shows up
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But it’s still slower than anyone would like because each new vaccine has to be tested, injected into animals to see if they develop any immune response. Some won’t work, some may cause side effects worse than the disease. Paradoxically, epidemics sometimes die out before the vaccine is ready for testing; that means the drug has to wait until the next epidemic – if it happens to be exactly the same disease – before it can be tested and evaluated on humans. That’s one reason it took so many years to produce a successful Ebola vaccine.

Scientists and health care workers are still needed to analyze findings and diagnose patients
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Technology has now accustomed human beings to expect accurate prediction of just about everything: when the Uber arrives, how long the journey takes, whether you’ll like a book, or movie or meal. So the idea that some things in life can’t be predicted feels counter-intuitive. For decades, tech innovation has relied on the belief that, with massive amounts of data, together with the tools to interrogate it, everything ultimately proves predictable. Real-life proves otherwise.

Focus efficiently only on what you can predict and you risk managing the flukes out of the system
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Terrorism isn’t always defined by profiles or patterns; terrorists know that randomness protects them. Surveillance produces more data than ever before, but it’s hard to find what you don’t know to look for until it’s too late. As head of MI5, Eliza Manningham-Buller was aghast when, under President Clinton, the Americans abandoned human intel, thinking that technology would give them all the information they needed. After 9/11, that strategy changed, an acknowledgment that human intelligence was still crucial in finding new patterns in new places, previously never considered meaningful.

Technology has accustomed human beings to expect accurate prediction of just about everything, so the idea that some things in life can’t be predicted feels counter-intuitive
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Similarly in pure science, it’s been routine for politicians to call for greater efficiency to produce strategically desirable breakthroughs. But attempts to use data mining, to identify the hot spots from which such triumphs emerge, identified little more than scientists themselves already knew; it’s their job and passion to stay alert to developments in their field. Trying to build the perfect profile of the superstar scientist failed too. Scientific discoveries exist across a spectrum, from the predictable (when it became technically feasible to decode the human genome) to flukes (like microwave radiation.) Focus efficiently only on what you can predict and you risk managing the flukes out of the system.

The company that continues to recommend to me the books I’ve already written is so confident of its data analysis that it wants to send me what it predicts
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But ultimate predictability is the holy grail of much technology. It’s the faith implicit in Amazon’s anticipatory shipping patent. The company that continues to recommend to me the books I’ve already written is so confident of its data analysis that it wants to send me what it predicts I will be aching to read. Closer examination reveals seeds of doubt; I won’t have to return the first few they get wrong. But the only really predictable aspect of the offering is that I’ll forget, or be too lazy, to return the ones I never wanted. This isn’t prediction; it is forcing customers to do what the business plan requires.

Uncertainty is endemic to life
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Uncertainty is endemic to life. Will the COVID-19 epidemic be over by March? The best models of disease will only provide probabilities, not absolutes. Soothsayers always have their own agendas, so we would do better to prepare

The post Expert View: Dealing with the Coronavirus in an Uncertain Future appeared first on Tech Trends.

I think it is safe to say that most of us now accept the dominant role AI is going to have on our lives in the future. In fact, artificial intelligence already underpins many of our day to day online and offline activities. We might not want to think about it but our modern lives are reliant on early forms and systems of machine learning and AI. From banking to entertainment our work, financial and personal lives are already strongly influenced by AI. Taking control of what AI does for us and how that power can be harnessed to grow your new businesses faster is what this book is all about.

“AI is changing the rules of growth: those who can adapt will thrive, those who fail to ride the AI wave will perish. This book provides a blueprint of how to apply AI to growth in your business.” Jessica Osorio Lead, Mobile Growth, Mozilla

Our modern lives are reliant on early forms and systems of machine learning and AI. From banking to entertainment our work, financial and personal lives are already strongly influenced by AI
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Author Lomit Patel knows a thing or two about boosting growth in successful early-stage startups having worked with Roku (IPO), TrustedID (acquired by Equifax), Texture (acquired. by Apple) and Earthlink. He is now Vice President of Growth at IMVU and responsible for user acquisition, retention, and monetization. He is also a respected public speaker, author, advisor, and has been recognized as a Mobile Hero by Liftoff.

“Lomit Patel has adopted and championed the power of autonomous marketing from the very earliest of days, and his practical, no-nonsense approach to outperforming against your growth goals will be indispensable reading for anyone looking to make their mark in the world of digital marketing.” Sal Aurora Chief Data Scientist, Nectar9

Lean AI is the next in a series of best-selling books for innovators and business people which is part of Eric Ries’ “The Lean Startup” series published by O’Reilly. While previous books in the series have addressed how companies can be more innovative and nimble while being less wasteful, how to to be more socially impactful and world-changing and how to structure a modern successful company, this book provides practical advice on how innovative startups should use artificial intelligence and machine learning with automation to scale up their growth.

Lean AI provides practical advice on how innovative startups should use artificial intelligence and machine learning with automation to scale up their growth
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“Companies are spending millions of dollars without understanding the true ROI of their marketing investments. With the advent of machine learning and artificial intelligence, marketers will be able to deepen their understanding of the customer journey and serve them in new, exciting ways. The Lean AI provides a solid foundation for the next generation of marketing automation in the age of intelligent machines.” Shamanth Rao CEO and Founder, RocketShip HQ

The Lean Startup series is a methodology for developing businesses and products that aim to shorten product development cycles and rapidly discover if a proposed business model is viable. The books along with associated online resources and worldwide events teach how this can be achieved by adopting a combination of business-hypothesis-driven experimentation, iterative product releases, and validated learning. The Lean Startup method teaches you how to drive a startup—how to steer, when to turn, and when to persevere—and grow a business with maximum acceleration. It is a principled approach to get a desired product into customers’ hands faster.

The Lean Startup method teaches you how to drive a startup—how to steer, when to turn, and when to persevere—and grow a business with maximum speed. It is a principled approach to get a product into customers’ hands faster
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Lean AI is broken up into six sections to help us tackle the complex and powerful features of AI and how it can be harnessed to take our businesses to the next level.

Part 1: AI + Growth Marketing = Smart Marketing focuses on Growth Marketing with an overview of the current startup landscape and the biggest challenges currently facing new companies around customer acquisition. It provides an overview of the main components of Lean AI and takes a look at industry trends for leveraging AI for smart marketing.

Part 2: Customer Acquisition 3.0 looks at the world of Customer Acquisition 3.0, which provides you with an overview to learn how to effectively leverage your customer data using “intelligent machines” powered by Artificial Intelligence. This includes reviewing how to identify tasks to automate, provides an overview of the “intelligent machine” framework, and explores whether to build it or buy it based on your resource constraints.

Part 3: What Metrics Matter to you? Moves you into the world of selecting the right metrics for success that align on driving long-term growth. It explores the importance of creative assets and the area of cross-channel attribution to help optimize your “intelligent machine”.

Part 4: Picking the Right Approach to User Acquisition looks at five proven keys to user acquisition strategies and how to pick the right one for your business. It also dives deep into the “growth stack” — a set of tools that all work together to help you get the specific results you’re looking for, given your situation.

Part 5: Managing Increased Complexity and Risk moves you into the world of managing increased complexity and risk with the data needed for artificial intelligence to work. It also explores how the future growth team which would coexist with humans and machines working together in ways that take advantage of the intelligent machine framework we share in the book.

Part 6: The Next Frontier moves into how humans and machines can work symbiotically to produce the best work — and that “next frontier,” as well as its potential for triumphs and its challenges to turbocharge your growth efforts.

“Lean AI reinforces the critical marriage between developing great creative and actionable data-insights. This has a profound impact to influence our creative ideas – something that until now, we thought would just be a dream.” Victor Zaud Sr. Director, Product Design, Disney+

Lean AI reinforces the critical marriage between developing great creative and actionable data insights. This has a profound impact to influence our creative ideas - something that until now, we thought would just be a dream
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Summing up the wealth of important info in this book is tough but for me, the core message of Lean AI is that modern companies now have the tools and technology at their disposal to vastly speed up the previously slow and expensive processes for determining if your product and market are aligned and to test and measure experimental iterations of your core marketing strategy. We can now turn over a lot of the time-consuming work of running a successful business to AI, acquire customers faster and more efficiently and see our business grow as a result.

We can now turn over a lot of the time-consuming work of running a successful business to AI, acquire customers faster and more efficiently and see our business grow as a result
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The language is pretty dense and getting up to speed with the technical jargon is essential but this book is bursting with valuable ideas and information for any business entrepreneur, leader, executive and investor who wants the competitive technical edge to scale up their customer acquisition growth better, smarter and faster than the incumbents. The startups with the best ideas don’t always win; it’s the startup teams that can execute well and leverage the right resources for optimal efficiency to get the job done well. Startups have a very low probability of success, so anything you can do to increase your chances of success or decrease your rate of failure is huge. We are moving into a golden age of AI and new companies simply must take advantage of it in order to be competitive. For those with little or no understanding of how to implement AI into their growth strategy, this book is a great resource, a must-read.

“Every now and then there is a new super-hyped technology. Most of the hype ends up in the graveyard, right next to companies that used them as their main line of business. AI isn’t just hype. AI is defining software, processes, work environments and decision-making in every aspect of our lives. I have no doubt that AI will continue to drive tremendous transformation in digital marketing. ‘Lean AI’ enables companies to view these dramatic changes as real opportunities.“ Oren Kaniel CEO, Appsflyer

Lean AI is scheduled for publication around mid-March but is available for preorder at Amazon today.

Tom Atkinson is Reviews & Dep. Editor at Tech Trends. Follow him on Twitter @techtrends_tech

The post Book Review: Lean AI appeared first on Tech Trends.

I spent many years working with start-ups and large corporations, and invariably they all spent a large proportion of their budgets getting their message across to consumers and other businesses.

Natural Language Processing (NLP) has advanced significantly in recent years, becoming much more sophisticated
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Yet while there is no doubt that external communications are important, I found that the most successful companies were, in fact, the ones which dedicated just as much time, effort, and resources (if not more) to get their internal communications right.

Because it’s all well and good projecting the right image to the outside world, but if your messaging is not consistent internally, in other words, if your mission is not clear to your own team, you have very little chance of it ringing true to those outside it.

One of my favorite quotes from Richard Branson really sums it up:

“Clients do not come first. Employees come first. If you take care of your employees, they will take care of the clients.”

Building a cohesive and inclusive corporate culture is challenging for any company, but those challenges are exacerbated even further in an age where many employees work remotely, often in different time zones.

With the right NPL tools, interactions can be turned into meaningful engagement at scale
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It might seem counter-intuitive, but where it comes to fostering better communication channels amongst humans, machines can be our most powerful allies. With technologies such as Artificial Intelligence – in particular, Natural Language Processing (NLP) – it is possible to enable better communication without having to over-stretch resources by dedicating people to maintaining those channels manually.

It’s all well and good projecting the right image to the outside world, but if your mission is not clear to your own team, you have very little chance of it ringing true to those outside it
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NLP has advanced significantly in recent years, becoming an increasingly sophisticated tool in discerning syntax (the arrangement of words in a logical manner) and semantics (referring to the contextual meaning of words), able to more accurately gauge human sentiment and leverage it appropriately. It can be used to bridge Top-Down Communication in Organizations and foster a better employee-employer relationship by ensuring that the employees receive all the relevant messages that they require, whether it is through regular email messaging or through highlighting their accomplishments.

“ It is a well-known fact that many companies fail to pass down relevant messages to their employees making them feel unwanted and disengaged,” said Gaurav Bhattacharya and Saumya Bhatnagar Co-founders of Involvesoft, a platform that enables companies to improve employee engagement through the use of NLP. He stresses that nowadays it is possible for chatbots to be highly effective in establishing a meaningful connection with an employee, understanding their strengths and weaknesses and helping them where needed.

Involvesoft provides its users with an Instagram-like feed that allows employees to read the latest news and announcements, spotlight stories, and take surveys and communicate with members of their community, which in turn improves top-down communication as the messages reach all the employees through the platform.

“Whereas an employee might be reluctant to ask a colleague or supervisor about something for which they feel they might get judged, a chatbot could help bridge that gap,” says Bhattacharya, adding that many times an employee will refrain from asking an important question because they are worried about how friends or colleagues might judge them, and this has a significantly negative impact on productivity levels, not least because failing to ask a question might mean a mistake is repeated without that person even realizing it.

As the CEO of the company, Bhattacharya very much practices what he preaches, since his own company also leverages NLP to make employees happy and successful by helping others. The Involvesoft platform helps companies and their employees to give back to the community by creating personalized giving and volunteering opportunities.

Involvesoft leverages NLP to make employees happy and successful by helping others
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Corporate Social Responsibility (CSR) is a hugely successful tool in building a cohesive company culture, often much more so than perks and personal rewards. In fact, Bhattacharya explains that such initiatives have been shown to improve company culture and team collaboration by up to 81% reducing turnover by as much as 30%.

NLP can thus create a self-learning virtuous circle, whereby every conversation, every interaction, and every good deed helps to evolve both humans and algorithms into a better platform. The information and insights gathered through this constant feedback loop are constantly deployed in optimization across the board within an organization: From user experience to consumer outreach, advertising and HR.

Whereas an employee might be reluctant to ask a colleague or supervisor about something for which they feel they might get judged, a chatbot could help bridge that gap
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With the right NPL tools, interactions can, therefore, be turned into meaningful engagement at scale, and provide a veritable goldmine of information for human resources and marketing teams alike, improving not only the work environment but also the product. It’s a win-win!

Tech Trends offers a broad range of Digital Consultancy services to guide companies, individuals and brands in effectively leveraging existing and emerging technologies in their business strategy.

Alice Bonasio is a XR and Digital Transformation Consultant and Tech Trends’ Editor in Chief. She also regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. Connect with her on LinkedIn and follow @alicebonasio on Twitter.

The post Communicating In the Age of Artificial Intelligence appeared first on Tech Trends.

2019 is nearing the last quarter and we are living and trading in a time when business software solutions are seeing amazing improvements in both their ability to do the traditional jobs which they were originally developed to do, as well as in integrating new features and functions which were not thought of as possible before. Let’s take a look at some of the latest innovations that are changing business software solutions for the better.

Business software solutions are seeing improvements in their ability to do the jobs they were originally developed to do, as well as in integrating new features and functions not thought of as possible before
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AI is Going to be Crucial for Project Estimation and Prediction in 2020

Modern project management tools have improved with AI integration and are more geared towards the year ahead, rather than just staying relevant in 2019. Expect project management tools such as Teamwork, Wrike, Smartsheet and Scoro to utilize machine learning capabilities of the integrated artificial intelligence components to their fullest in bringing forth the following advantages.

Modern project management tools have improved with AI integration and are more geared towards the year ahead, rather than just staying relevant in 2019
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KBE: Knowledge-Based Expert Systems

A Knowledge-Based Expert (KBE) system provides near accurate estimations regarding the number of resources and the exact time allocation that will be necessary to complete each and every task throughout the different stages of the project.

KBE systems are a major component of the planning, scheduling and budgeting phase of projects these days, and without the AI assistance, businesses that are using them would immediately start to see a dip in their ability to handle projects and complete them within the stipulated deadline.

KBE systems are a major component of the planning, scheduling and budgeting phase of projects these days
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As for companies that are not using any project management tools at all, or still relying on something that went out of date and support a long time ago, the improvement in project management will seem groundbreaking!

Better Preparation and Elimination of Scope Creep

AI will be eliminating at least some of the major “halt, reassess and reassign” steps that are generally needed to avoid scope creep.

For companies that are not using any project management tools at all, or still relying on something that went out of date and support a long time ago, the improvement in project management will seem groundbreaking!
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The predictive analysis may not always be enough to predict everything and advise accordingly, but by analyzing “if-then” statements relevant in most simpler, smaller projects, it is enough to help a project manager make provisions for scope creep, if and when the parameters are changed for one reason or another.

As for the ones that the system may not always be able to predict, they will still take a lot less time to handle as compared to the amount of time which would have been necessary, if the project manager and the team also had to deal with all the other issues the system managed to successfully predict in advance.

AI is a developing piece of software that continues to learn through pattern recognition, data collection, and analysis, so with the passage of time, more avenues of AI use will open up across all fields of business
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Artificial intelligence is no longer a new concept in business software, but yet it continues to surprise us by opening up new avenues not thought possible before. Surprising as the results might be at times, the phenomenon itself isn’t though.

AI is a developing piece of software that continues to learn through pattern recognition, data collection, and analysis, so it would only make sense that with the passage of time, more avenues of AI use will open up across all fields of business and everything else as well.

The post How Artificial Intelligence Can Supercharge Your Project appeared first on Tech Trends.

3 Ways Artificial Intelligence Can Help Your Business.

AI can help you to easily analyze every single piece of information produced digitally by any competitor; anything from online content, social media posts and written content to videos uploaded.
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Outstanding developments in technology mean that new and existing businesses have access to new ways of running and developing their companies. Artificial Intelligence (AI) is just one example of the breakthroughs in helpful and immersive technology; other examples include Virtual Reality and Augmented Reality.

With so many options out there, it can sometimes be difficult to know how specific technology can help your business in the best way; so here are 3 ways Artificial Intelligence can help.

Improve Your Customer Relationship Management

Good management of your customer data is imperative for the smooth running of your business. An adept CRM system is able to gather data across all the relevant channels, such as email, social media, and phone communication, in order to present you with the best way to improve the overall sales process.

You can now access CRM systems which use Artificial Intelligence to better help the process, with AI analyzing all customer feedback from all communication outlets and being able to adjust marketing strategies to better suit the information gathered.

This means that AI can provide relevant insights into customer activity and feedback, meaning you can optimize your entire sales process for the better, thanks to AI.

Good management of customer data is imperative for the smooth running of your business
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Use a Chatbot For Your Website

You’ve undoubtedly had experience with a chatbot before, they are commonly found on websites in the form of a small pop-up box in the corner of the screen asking if you need any help.

Artificial Intelligence can be used as a robotic customer service tool, programmed to help with any customer questions when visitors are exploring your website. It’s a very helpful tool, as it means customer communication is promptly initiated, and that there is always a customer service representative available from your business, 24 hours a day – even if that rep is robotic.

AI helps you better track the activity of your competitors and see exactly what they are doing, at any time
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This is a particularly effective option for those businesses which are just starting out or have a very small team, meaning a sales team might not have been established yet; an AI chatbot can help fill in the gap in human employees.

If you’re looking to further your understanding of AI in order to better implement it into your business or future career, you can fulfill a Masters in electrical and computer engineering online, which focuses on the future development of technology such as AI robotics.

A CRM system is able to gather data across all the relevant channels, such as email, social media, and phone
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Gather Relevant Research on Your Competitors

Competitor research is a primary focus and ongoing process for any business, especially those start-ups which are new to the market. However, competitor research can be very time-consuming and often difficult to navigate; and that’s where Artificial Intelligence comes in.

AI can help you to easily analyze every single piece of information produced digitally by any competitor; anything from online content, social media posts and written content to videos uploaded. AI also helps consolidate all this feedback into an easy-to-navigate report. AI helps you better track the activity of your competitors and see exactly what they are doing, at any time.

Artificial Intelligence can be used as a robotic customer service tool
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The post Supercharging Business Intelligence with AI appeared first on Tech Trends.

The central challenge for companies dealing with large amounts of data is a digitisation strategy. Here it comes to artificial intelligence and semantic technologies. The integration of these megatrends into enterprise processes and workflows will be the focus one of the subjects of the SEMANTiCS 2019, which takes place from 9 to 12 September in Karlsruhe, where top speakers from industry and academia will explore how AI systems can help businesses succeed in the digital age.

The central challenge for companies dealing with large amounts of data is having an effective digitisation strategy
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“Explainable AI is the is the key to progress and acceptance of AI,” says SEMANTICS 2019 General Chair Harald Sack. Explainability can be important in some applications, in particular, when AI is applied to humans. In other applications, it does not play any significant role. Some argue that our brain first acts and then tries to explain why it acted in a particular way, maybe mostly for communication purposes, to justify action and to convince others.

In lectures, panels and workshops numerous enterprise implementation projects and use cases will be presented which will help to bridge that gap between the complex concepts that underpin AI and the practical applications that concretely benefit businesses.

Topics include process optimization and automation, information logistics and data management as well as business development and customer relationship management. In community events, international high-tech experts will also discuss the future and significance of artificial intelligence in a broader context.

Explainable AI is the is the key to progress and acceptance of AI
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One of the core technologies for reducing complexity in business processes are Knowledge Graphs
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The keynotes will be held by prominent experts from the US and Europe, among them Willem Manders, Head of Knowledge Management at Shell, Michel Dumontier, Professor of Data Science at Maastricht University, Valentina Presutti, researcher at the Semantic Technology Laboratory of the National Research Council (CNR) in Rome and Michael J. Sullivan, Principal Cloud Solutions Architect at Oracle.

One of the core technologies for reducing complexity in business processes are Knowledge Graphs.

“Those who stay on their islands will fall back. This is currently the case with a large part of the data which is kept in silos,” says Andreas Blumauer, managing director and founder of the Semantic Web Company, which organizes the conference alongside FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Fachhochschule St. Pölten, and the Universities of Leipzig and Amsterdam.

“For every knowledge worker, it is a highly time-consuming task to identify, connect, understand, and interpret the right dots and information pieces. SEMANTiCS 2019 wants to show IT decision makers how companies can develop their own Knowledge Graphs along the whole Linked Data Life Cycle, to support decision and process augmentation based on that linked data,” adds Blumauer.

For Volker Tresp, Distinguished Research Scientist at Siemens, the

biggest challenges ahead when it comes to enterprises employing Machine Learning, Autonomous Systems and AI, is coming up with an effective business model that works for that individual company. In other words, there is no one-size-fits-all approach where it comes to leveraging Artificial Intelligence in your own business.

Those who stay on their islands will fall back. This is currently the case with many companies where a large part of their data is kept in silos
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In the coming years we need to build a strong academic basis for deep learning and machine learning in Europe
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“Machine Learning is a very strong and very robust technology. But this does not mean that each company knows how to transfer this success into a business. Currently, no company, whose business is on the internet, can do without AI. If it turns out that your company has an AI business, then you might have to drastically change the culture in your company. You can only be successful if you manage to hire the best talent and if you change the culture in your company so that it values, appreciates and listens to that talent.”

One example of an area where correct AI implementation can have a huge efficiency impact is Healthcare. Hospitals generate huge amounts of data each day, and patients can benefit from the structuring of that data into the Knowledge Graphs mentioned above.

“AI applications in image analysis have already been used for more than 5 years. Siemens Healthineers have been doing pioneering work and are working on many future use cases,” explains Tresp.

Volker Tresp, Distinguished Research Scientist at Siemens

“I am completely convinced that knowledge graphs will become more important. As in the medical area, most domains consist of unstructured data (sensory data, images, …) and structured data (diagnosis, procedures, lab results, blood counts). Roughly speaking structured data is the domain of the knowledge graph and unstructured data is the domain of deep learning. A challenge is to have both talk to one another. That is what we are working on!”

According to Tresp, Deep Learning (DL) was the reason for the recent breakthroughs in AI and it will continue to be the basis for the progress for the next years to come.

“DL builds on available labeled data, new algorithms, computational power, and an incredible community. Deep Learning will interact more strongly with other approaches and we will see more hybrid approaches. For example, we and other research groups combine knowledge graphs with machine learning and deep learning. I am also convinced that the link to cognition will become stronger: one can learn a lot from the organizational structure of the brain. We as humans can manipulate symbols and this will also become more relevant for AI. But we have to go new ways and not warm up old ones. As I like to say: AI is not only Machine Learning, but without Machine Learning there is no AI. In the coming years we need to build a strong academic basis for deep learning and machine learning in Europe and be open to new ideas that can contribute,” he concludes.

No company, whose business is on the internet, can do without AI
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Alice Bonasio is a VR and Digital Transformation Consultant and Tech Trends’ Editor in Chief. She regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. You can follow @alicebonasio on Twitter, connect with her on LinkedIn or subscribe to her Inside VR/AR Newletter for the latest curated immersive news.  

The post What is Your AI Digitisation Strategy? appeared first on Tech Trends.

“It’s pretty common knowledge that body language plays a big role in how we communicate in real-life, and the fact is that behavioral studies have been validating the correlation between the body and mind for decades.” explains Amir Bozorgzadeh, Cofounder and CEO at Virtuleap. “In the setting of spatial computing, the whole game elevates as all of our intuitions about non-verbal expression are suddenly given a voice.”

Virtuleap is a Lisbon-based startup, a Boost VC Tribe 11 company and a member of the CMS equIP startup program.They initially began developing their API to cater towards accessibility needs, broadening the user base of immersive content adapting for inclusiveness and maximum user comfort, like an increase of color contrast or adjustment of font size through individual user preferences.

With machine learning, the mathematical models will become more accurate over time
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The @Virtuleap API will be able to anticipate the profile of an anonymous user based on their behavioral cues by calculating probabilities on their likely psychographic and demographic profile
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That human-centric inclusive angle gradually evolved into incorporating scientific approaches such as neuropsychology and fractal analysis, which has now become what the team considers to be the first native metrics for human-centric research, design, and marketing for the spatial computing era.

The team leveraged modern neuroscience research to create mathematical models that infer emotional states based on your subliminal and unconscious body postures, gestures, and motion in immersive environments. For the next phase of development, they are now looking to stress-test the algorithms by feeding the machine learning with data from a consumer-facing app. The result is the “Attention Lab” – an Oculus Go “edutainment” app which has just been launched in beta – featuring a series of games and challenges that track user interaction.

Virtuleap's human-centric inclusive angle evolved into incorporating scientific approaches such as neuropsychology and fractal analysis
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@Virtuleap leverages modern neuroscience research to create mathematical models that infer emotional states based on subliminal and unconscious body postures, gestures, and motion in immersive environments
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The @Virtuleap concept is a mix of popular VR apps like Valve’s The Lab and Job Simulator and non-VR games like Lumosity and Cognifit
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“While players get to enjoy challenging their cognitive abilities, such as memory and concentration, the real benefit of the Attention Lab is access to an unprecedented depth of self-knowledge and psychographics that is enabled thanks to the new data points captured by spatial computing devices.”

With machine learning, the mathematical models will become more accurate over time by allowing the API to track and map physical, physiological and psychological “segmentation” profiles in order to build a database that can generate predictive analytics. For example, the API will be able to anticipate the profile of an anonymous user based on their behavioral cues by calculating probabilities on their likely psychographic and demographic profile.

The real benefit of the Attention Lab is access to an unprecedented depth of self-knowledge and psychographics that is enabled thanks to the new data points captured by spatial computing devices
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“If it walks like a duck, swims like a duck, and quacks like a duck, then our machine learning calculates the probability of how likely that otherwise anonymous user is a duck.” explains Roland Dubois, Cofounder and CXO at Virtuleap. “Everything we capture in the form of meaningful insights would otherwise require a traditional survey or user interview in order to capture.”

While players get to enjoy challenging their cognitive abilities, such as memory and concentration, the real benefit of the app is access to an unprecedented depth of self-knowledge.

“Players will get to learn about how their brains work and all sorts of insights about their neuroscience, not just about themselves specifically, but also in how it relates to the neuroscience of their friends and the community at large.” said Dubois. “Each experience will present different famous experiments that will, in turn, allow them to learn about how they react and respond in different situations. Insights that might just blow their minds.”

The Attention Lab is currently featured on the Kaleidoscope VR platform and is set to launch on the Oculus Store by Q2 2019. In parallel, the API will be made publicly available on an online platform later in the year. Virtuleap is currently accepting pilot campaigns with brands and companies in both the consumer and enterprise sectors in order to create what they are calling “template models” that will allow their biometric algorithms to be relevant for content across a range of different categories.

This article was originally featured on VRScout

The XR Attention Lab Takes Body Language To A Whole New Level via @alicebonasio https://t.co/Pa9AHYngA0 pic.twitter.com/rfKoTzzQZN

— VRScout (@VRScout) February 27, 2019

For companies looking to get into Immersive technologies our VR Consultancy service offers comprehensive support in strategic deployment of Virtual, Augmented and Mixed Reality

Alice Bonasio is a VR and Digital Transformation Consultant and Tech Trends’ Editor in Chief. She also regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. You can follow @alicebonasio on Twitter, connect with her on LinkedIn or subscribe to her Inside VR/AR Newletter for all the latest curated immersive news.  

The post Interpreting Body Language With XR appeared first on Tech Trends.