The Dublin-based IT and professional services provider gave a virtual tour of one of its seven innovation labs in Sophia Antipolis, France. During the tour, speakers from the IT company gave the example of baby food, in particular spaghetti bolognese for a 12-month old.

It first needed to gather masses of information from social media and feedback from the consumers before applying AI as part of the knowledge discovery process.

The AI, which has been built into Accenture’s interface, listed popular ingredients, competitors who make that particular dish, plus positives and negatives for customers. This is all pretty typical in knowledge discovery, according to lab director Anne Groeppelin who led the virtual tour.

“What the team are now doing is looking at the ingredients in that formula, looking at all the criteria in terms of nutrition, the consumer rating, the cost, where the ingredients have been sourced in that recipe, the sustainability of the product and its taste profile,” she said.

The R&D team have developed a tool which allows its clients to change the recipe using suggested ingredients from generative AI. These are listed into three categories: expected, surprising and novel.

“The full idea was to add that ingredient [cocoa] which changes the formulation, the nutritional information and the cost, and then I can make the decision, do I want to try this formulation or not?” asked Groeppelin.

According to Groeppelin the tool not only boosts creativity but also efficiency, using simulation through generative AI to test what would be the best formulation for the recipe.

“If I add cocoa to that recipe, what is the amount I should add to maintain the nutrients score, to maintain the costs at an acceptable level, or to maintain the sustainability?

“It’s an example where we are using AI to augment creativity to interpolate new ideas and use large language model types of AI to reformulate and get to the level of detail that is needed to actually produce that product.”

Accenture is also testing LLM’s in the pharmaceutical industry to reduce the time to produce and market medicines and vaccines.

The lab director said it takes, on average, ten years to develop a new drug and get it approved due to the complexities involved in knowledge discovery.

“In life science in particular, you have very complex information from the existing drugs, the genes that are sources of a particular disease, regulations, tests of the medicines with the patients, and this amount of information cannot be managed by even several brains together.”

Accenture’s innovation lab in Dublin is leveraging LLM’s to perform knowledge discovery across a large set of information, linking all the existing information to predict the link between diseases, drugs, treatments and medicines.

For example, take Alzheimer, what are the types of medicine that has been applied before and what are the types of scientific publications that relate to it? Groeppelin asked the virtual audience.

“It’s really plugging all the information together to detect information we may not yet know and unearth new insights.”

AI is also being tested in drug product discovery to look at a specific molecule and simulate an alternative one that could have a better effect on the treatment of a disease.

“We select a molecule and decide the protein we want to attack in the body and then it interpolates what other molecule could fit, and those are already ones that have been approved by the FDA [Food and Drug Administration].”

The post How Accenture is leveraging LLM’s to help enterprises with product discovery appeared first on TechInformed.

“Using artificial intelligence (AI) and machine learning (ML) tools to analyse customer data and preempt shopping behaviour will help retailers keep on top of evolving customer preferences and ensure that their campaigns are relevant and tailored.

“Secondly, in 2023, expect an increase in digital ad campaigns enhanced by two-way, intelligent dialogue and visual touch points. Lastly, more retailers should continue meaningful and accurate advertising while keeping in step with tightening privacy measures.

“Next year, retailers that leverage AI, ML and AR are set to benefit from predictable, reliable insights which are gold dust in these testing times. The intelligence generated from AI and ML based enhancements can feed into initiatives such as loyalty programmes, that massively benefit from personalisation, and ultimately help increase resilience and more effective marketing campaigns in the face of uncertainty.”

Kevin Mathers, MD, retail at Google

“In 2023, we will see an increase in Artificial Intelligence (AI) as businesses aim to surprise and delight customers with personalised value that distinguishes them from a crowded market. Customer service teams will look to an Amazon or Deliveroo-style approach to managing queries and disputes. Automated rules will help with routine queries to free up resources. Connected real-time data-led insights will help businesses to be proactive in improving the overall customer experience whilst empowering customers through personalisation.”

Tim Annis, UK managing director, Bluechain

“In 2023 we can expect to see a greater focus on quality of engagement: understanding the voice of the customer and dynamic assessments around sentiment, such as tone of voice on calls, emails, chat and text. Thanks to AI and a wealth of rich chat, SMS and WhatsApp messages showing the cadence of customer and agent conversations, (as opposed to stop/start email interactions), organisations will get smarter and more sophisticated feedback.”

Colin Crowley, CX advisor, Freshworks

2: AI apps to replace Google

“We will see a proliferation of apps built on top of AI-generated content (text and images) through tools like Dall.E and Stable Diffusion. It will be interesting to see the impact of open-sourcing stable diffusion on the AI community.

“I see ChatGPT replacing Google in many ways and OpenAI emerging as a big tech giant on top of this product. It will be interesting to explore its impact on education, healthcare, and personalised software. It will transform our society in many ways.”

Ali Chaudhry, chief technical advisor, Infini8AI

3: AI pair programmers will transform software engineering

“What’s exciting about the new AI pair programmers such as GitHub Copilot or TabNine is that we’re witnessing the invention of a new and fundamentally more expressive language. These new tools, trained on billions of lines of code, can use that learned context to auto-generate the code a developer is writing, thereby transforming their workload.

“We’ll see many more developers creating an entire application by writing a single line of natural-language English, and then watching the AI pair programmer complete the rest of the work. This technology offers developers one of the most profound advancements in software engineering in the last half-century.”

Adrien Treuille, head of Streamlit, Snowflake 

4: Composite AI will add data value

 “Composite AI is a new approach that generates deeper insights from any content and data by fusing different AI technologies. Knowledge graphs are much more symbolic, explicitly modelling domain knowledge and, when combined with the statistical approach of ML, create a compelling proposition. Composite AI expands the quality and scope of AI applications and, as a result, is more accurate, faster, transparent and understandable, and delivers better results to the user.

“It’s a major advance in the evolution of AI, and marrying content with context and intent allows organisations to get enormous value from the ever-increasing volume of enterprise data. Composite AI will be a major trend for businesses in 2023 and beyond.”

Dorian Selz, CEO, Squirro

5: AI to marry human perspective for improved accuracy

“As AI becomes more ubiquitous and used in more industries and situations, we’re likely to see a greater commitment to, and understanding of, ‘augmented intelligence’. A concept that Gartner defines as a design pattern for a human-centred partnership model of people and AI working together to enhance cognitive performance, including learning, decision making and new experiences.

“As we see more human intervention in AI, and use of larger data sets based on human experiences, we’ll see improved accuracy and personalisation of experiences. And where in some circumstances, this improved accuracy is nice to have from a user experience perspective, in others – such as healthcare – it is essential to get it right.”

6: Foundation models will become the bedrock of AI

“In 2023, we’ll see foundation models further transforming AI implementations, which will exacerbate the need for governance, compliance and testing. Foundation models are based on deep learning algorithms that have been trained with giant datasets made up of everything from images, words and even voices.

“This may dramatically accelerate AI adoption, but the need to ensure that the correct data is being used ethically and equitably increases as more data becomes available. Building in compliance and ongoing testing as part of the development process can help teams regularly assess whether the data is accurate or not and can even help to prevent bias. This is especially critical for AI use cases in banking, healthcare and other areas where faulty information can result in major problems.” 

7: AI will infiltrate many industries

“AI is becoming more prevalent in many industries but expect to see AI playing a bigger role in frontline healthcare next year. This will be particularly true in the UK and Europe where there’s a shortage of doctors and general practitioners.

“During Covid chatbots were used to diagnose symptoms, and in the future we’ll see more instances of AI filtering patients through to the correct medical professionals, once the initial diagnosis has been identified.

“Travel is another area where we’ll see more adoption in the form of AI assistants. These automated assistants will help to create a more consistent travel experience. They will manage the entire process from arriving at the airport to boarding a flight, to booking a taxi upon arrival at your destination and checking you into your hotel. They will even provide you with information on where to visit and where to eat during your stay.”

Adonis Celestine, director of automation, Applause

“If previously AI was only seen as a way to automate mundane tasks, today companies are exploring creative opportunities of AI in art and even care homes (using AI to recognise the emotions of residents), and that will only continue expanding in the next year and beyond.”

Elena Davidson, CEO, Liberty Comms

8: AI to upskill existing business processes

“With businesses facing an economically challenging year, CIOs and IT leaders will be under pressure to do more with their existing talent and technology. The year will likely see increased investment in the data tools and technologies that automate manual processes, deliver efficiencies for all teams and empower individual users, such as data meshes and advanced data management platforms.

“This will require businesses to look inwards at their most valuable assets, which are the data and information they hold and operationalise day to day, as well as outwards to data sets that can be harnessed for innovating new products and services. To this end, we will likely see a continued hiring surge focused on the data science skills needed to derive value from data and deliver advanced automation and insights through AI-powered solutions.”

Matt Eustace, head of solutions engineering & data protection officer at Aiimi   

The post 2023 Informed: AI and machine learning predictions appeared first on TechInformed.

According to the report, only 18% of data leaders expect to receive the full amount of funding they say is necessary to get or stay ahead of the competition in data analytics, even though almost all (98%) say it is needed.

Alation’s State of Data Culture Report proved there to be a correlation between a strong data culture and an organisation’s ability to reach or exceed revenue goals.

Over 600 data leaders across the world participated in the study, with the report finding that organisations with a ‘top-tier’ data culture remain the most likely to meet or exceed their revenue goals, with 90% achieving their goals over the past year.

However, 66% of data leaders believe company leaders are the biggest obstacle to getting necessary funding, with 42% saying the C-suite do not keep to their promise to invest in programmes that help drive data culture.

Additionally, only 29% of data leaders are confident that their CEO knows that there’s a link between investment in data and analytics and staying ahead of the competition. The report states that this suggests there is a strategy gap where C-level executives will promise to invest in data and analytics, but will look over it as a priority.

“If these organisations fail to recognise the power of data-driven decision making, and don’t fund data and analytics initiatives properly, at best they’ll introduce significant risk to their organisation; at worst, be disrupted by competitors their threaten their existence,” said Alation CEO Satyen Sangani.

Core areas data leaders said they would like to see investment includes data catalogs (87%), which they believe to be essential, creating data processes (44%), creating an inventory of existing data (43%), and fixing data quality issues (38%).

The post Data leaders want their CEO’s to invest more in data and analytics appeared first on TechInformed.

The Covid-19 pandemic has also played a role in accelerating interest in online education either. As lockdown’s shuttered people in, education became an increasingly important component of the tech sector. Key tech trends such as the internet, AI and machine learning all were introduced to make the online experience an even more customer-friendly place. 

FutureLearn’s newest CEO Andy Hancock spoke with TechInformed about just how technology and education have weaved together to create an advanced online marketplace for education. 

How has tech turned education into a marketplace? 

Like many industries, the education sector is undergoing its own digital transformation, especially due to impacts of COVID. The importance of tech and digital learning in education is already demonstrating its influence today, with our recently launched report on the Future of Learning showing that online learning is the most popular way for one-third of UK adults to build their skills today. The demand from a global audience for renowned courses is also growing. We are no longer bound by our geographical location and instead have the choice through platforms like FutureLearn to gain an education anywhere and any time. 

From my experience in helping to bring the financial sector into the digital age and making it easier for the customer to navigate, I can already envision a similar path for the education sector. Education is now well on its way to becoming a marketplace where both learners can choose their learning pathway to suit their life and career goals, and educational and industry partners can serve bite-sized learner-focused content to enable the building of these pathways. In terms of how we build on this marketplace for the future, it’s all about continuing to optimise it with technologies such as AI and machine learning, in order to make the process of choosing a course or uploading content as seamless as possible for learners and partners respectively. 

How has the digitalisation of education strengthened learning?  

Online learning has expanded beyond its debut as the ‘MOOC’ over a decade ago. Where platforms once looked to service large cohorts of learners via synchronous courses, the industry has naturally progressed towards a more asynchronous, personalised experience that’s more tailored to the individual.  

Through this increased customer focus, online learning has placed more power into the hands of the learner, enabling them to find what they want to learn whenever they want to learn it. This is something that will only grow within the sector as consumer expectations around what they can do digitally continues along this trajectory. For educators, universities and learning platforms like us, this means we’ll need to leverage the vast amounts of data and customer behaviours we have, using tech, namely AI and machine learning to understand and help guide their experience on the platform. 

These technologies not only have the potential to benefit learners, but, harnessed in the right ways, they can also give partners the tools they need to refine and grow their digital offerings. I see an opportunity here to make it even easier for partners to be on the platform. 

Where does data, AI and automated models come into online education? 

As mentioned above, the education space is ever-changing due to the changing needs of the learner and as such technology will play an instrumental role in delivering this effectively. Namely through AI and machine learning to understand and help guide their experience on the platform. 

How will FutureLearn invest in the modern-day student? 

As we know, the very nature of being a student is changing. FutureLearn is always looking to understand the learner of tomorrow and we’ve recently done research as part of our Future of Learning report into identifying what exactly the needs and expectations of the future learner are. The report’s findings around the importance of online learning to consumers really tells that people want more flexibility, accessibility and affordability from their education, which are the exact areas FutureLearn will continue to invest in and strengthen as a core part of our strategy.  

We also know that learners value being able to interact with their peers while they learn, and the impacts this type of social learning has on their educational outcomes speaks volumes. At FutureLearn we’ve found that those who interact with social learning on a course are six times more likely to complete their course than those who do not. As education becomes increasingly blended between in-person and online delivery, investing in this social aspect will be a crucial part of ensuring the best outcomes for the modern-day student. 

How do you feel about joining FutureLearn and what are you excited about?  

I joined the company towards the end of 2021 and, having previously worked within the fintech sector at one of the UK’s biggest price comparison platforms, I’ve spent the last few months really getting to know the education sector and all its challenges and opportunities better. So far, what I’ve seen is very promising and I’m excited to be joining FutureLearn at a time when I believe we can make an even bigger impact on the sector through continuing on our mission to transform access to education. 

I’m particularly excited to see all of the opportunities around scaling the platform and its offerings to our learners, educators and partners alike in order to deliver a robust lifelong learning experience. The career for life has become a thing of the past, especially with recent trends like the ‘Great Resignation’, which is why it’s more crucial than ever that we can continuously deliver career-relevant courses for people as they take their next step up, and the next one after that. 

The post Learning online: How tech transformed education during Covid-19 appeared first on TechInformed.

Ernst and Young – or EY as it operates – is a UK-based is a multinational professional services network and one of the so-called “big four” accounting firms (along with Deloitte, KPMG and PricewaterhouseCoopers). It also offers tech consultancy business with revenues of close to $13 billion.

I meet Errol Gardner – the global vice chair of EY’s consulting business – at the company’s stand at Mobile World Congress in Barcelona. After almost three decades in consulting, including various roles with PwC and IBM, Errol Gardner joined EY in 2009, moving into his current role in 2020 – right in the middle of the pandemic.

“A lot of what we do is to bring new tech into the light,” he explains. “Around 40% of our professionals are tech professionals but maybe 60-70% of what the consultancy business does is tech-related.”

If it sounds odd that EY – a name perhaps more associated with the finance sector than tech – was at a telecoms conference, it shouldn’t.

As Gardner explains: “In terms of this sector, we are very focussed on the convergence of telecoms and technology. There are some huge opportunities for both of these industries to not just transform themselves but also to act as force multipliers of change across many sectors.”

The question is, how? How can a financial services company, or a manufacturing firm, or a logistics operation, benefit from the convergence of telecoms and tech? That’s something EY has been looking at very closely.

Horizons

“One of our focus areas, in part, is to discover what’s out there and what’s changing. We’ll do surveys periodically with our clients to understand what is our view and what we’re thinking about?”

One recent report from the company looked at the role of TMT (Technology, Media and Telecoms) companies play in a world where global trade is increasingly complex. This found that these firms “frequently lack a robust global trade and operating model strategy that simplifies complexity and drives profitable, sustainable growth” despite the expected rebound following the Covid-19 pandemic.

“Advances in technology are enabling a wider range of seamless forms of trade, which TMT companies should be perfectly placed to exploit,” the report says.

EY has also launched its Tech Horizon’s series of reports, which look into the role tech is playing in digital transformation, and the effects this is having on businesses worldwide. The global survey of 570 companies revealed six habits of transformation leaders: Customer focus; accelerating AI to drive growth; partnerships that drive innovation; nurturing talent with new strategies and incentives; activating governance for emerging tech; and powering innovation by leveraging data and being agile.

This is also having a financial impact on businesses, EY found. Leaders in digital transformation projects were “50% more likely than those not deemed leaders to annually see EBITDA increase by more than 15% on a five-year, CAGR basis.

They were also 45% more likely than those not deemed as leaders to unlock annual revenue growth of more than 10%, and 26% more likely than those not deemed as leaders to enjoy annual gross profit increase by more than 10%.

As Gardner explains, “We do surveys periodically with our clients to see if our views [on technology] resonate with them, and this has revealed some key focus areas, such as cloud and AI, and data and analytics more generally. Plus security, which are all critically important to them.

“We’ve got three waves at the moment. Firstly, you have companies that still haven’t figured out digital transformation, who are operating in a legacy – and arguably antiquated – technology sphere. They have to worry about where do we go next?”

Next, he identifies those who are in the process of moving towards digital. That means looking at “how you communicate with customers much more actively, how do you manage operations to deliver on the digital promise?”

Then there are those out front, who are adopting future solutions – cutting edge tech such as edge computing or private networks. Though solutions are “here today” in adoption terms, they are very much “tomorrow’s technology” in terms of wider adoption.

So how far along are most companies in this journey? Gardner says it is vertical specific, with “leaders and laggards” in every segment of enterprise.

“Clearly in in tech, you’ve got more leaders than lockouts. But then the adoption of technology has accelerated substantially in the last five years,” he adds. The Covid-19 pandemic has accelerated this even further, with businesses left with little choice but to transform their operations due to global lockdowns.

Beyond telecoms and technology, he points to finance and banking as quick adopters of new technology.

“If you look at that market, they face complexity in what they have, but they are putting significant investment into technology and the solutions that wrap around that. But there are still a lot of banks that are very much focussed on the traditional, local branch network, ways of working.”

Beyond finance, he points to industries such as automotive as leaders in overhauling their approach to manufacturing, with car manufacturers such as Fisker even making an appearance at Mobile World Congress.

“This highlights that car manufacturers are now becoming technology companies, with less of a focus on driving cars. Look at the likes of Tesla, too,” Gardner adds. “People are now seeing that cars are about technology but also about data. As we move to more autonomous vehicles it will become much more about the experience than about driving from A to B.”

 Green machine learning

I am curious as to whether Gardner or his team have spotted any technology- adoption or business transformation patterns that span several enterprise sectors.

“If you talk to different C-Suite and clients – as we spend a lot of our time doing – you find that most recognise the imperative to transform. They recognise that technology is the means to achieve this.”

There is also huge interest in how to transform in a sustainable way. “There’s a lot of talk about sustainability – for a lot of organisations, the question is how to we leverage our considerable investment into digital transformation to also take a step to become greener.”

This, he adds, might mean looking at supply chains, or even taking in social issues such as diversity. “Really, it is just a question of how and where businesses are on that journey.”

Much of this social drive is coming from a consumer demand which dictates that the companies they buy from are as sustainable as possible, but there is also pressure within organisations from employees.

“If you are an organisation saying we cannot ignore those things that reduce costs, improve sustainability outcomes, and also help us to become a digital organisation, the question becomes “how do we do all three?” instead of just hitting one or two of them,” he elaborates.

“The aim is to do this through the lens of cost reduction to make sure the business is lean and efficient going forward.

“But executives also have to be clear on what metrics they are targeting, from a sustainability perspective, and what is important to stakeholders. It isn’t easy, or straightforward, but that is the conversation C-Suite are realising they need to have because funding is restrained.”

AI leading the way

So, as a man who oversees the transformation of other businesses, what technologies excite Errol Gardner?

He smiles: “I don’t mean to sound blasé but all technology excites me. I’m excited by helping organisations move to the new world we’re all in. Even if that is just a simple move to the cloud, it can be a big change. But right down to companies in retail who are looking at how they can leverage the metaverse to demonstrate what they are doing.”

But surely there must be a current trend that stands out? Some kind of technology that EY’s huge client base is showing interest in more than any other.

“In very simplistic terms, it is automation,” says Gardner. “What I mean by that is it is simplifying business processes through automation. It is the most basic function of AI allowing a reduction in the use of manual labour. Then, rather than just repeating processes over and over, you can use machine learning to train models to be more efficient and more sophisticated.”

The use cases then become more sophisticated but so do the technological solutions. This, he adds, allows for benefits such as cost reduction.

“But perhaps more importantly, it improves the customer experience – it allows for a quicker turnaround to lure customers, by offering real-time analysis and data.

“As a consequence, I think that’s the area that’s probably got the most near term applicability. And again, if you look at this world, in telcos and tech in particular, it’s in the IoT space.”

This, he concludes, will have a real-term impact for both workers on the ground, but also for executives looking to transform their operations.

“Yes, this allows for benefits such as cost reduction,” Gardner explains, “but there is a wider business angle, such as maintenance and how you are tracking it. This could be done internally or it may be through a third party.

“Then there is the plethora of data. AI allows you to use models to organise this, to run through it, and to determine when you have issues that need intervention. Then you can either tell a human worker there is a problem you need to fix, or there is an action that the system needs to take to fix itself.

“These are the big areas we’re seeing a lot of interest in, and it spans across verticals.”

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