Virtual CogX: The Festival of AI & Breakthrough Technology

Elutions is proud to announce their Lead Partnership of The CogX Global Leadership Summit and Festival of AI & Breakthrough Technology, June 8th- June 10th. In a world that is constantly in flux to adapt to impacts of COVID-19, CogX made the difficult decision to virtualize their event. We fully align with this decision as they themselves said,

“There are important, and in some cases urgent, topics to discuss: both the immediate challenges presented by COVID-19, and to play our part in helping restart the economy by connecting, collaborating and supporting each other.”

Relevant, now more than ever, is CogX’s 2020 Event Theme- How Do we Get the Next 10 years Right? Outlined below are the ways in which the conference aims to address this massive question:

– Move the conversation forward with concrete actions

– Reframe the climate emergency as the biggest economic opportunity in the last 200 years

–Increase understanding of the current Covid-19 pandemic and champion innovative solutions

The global pandemic has allowed many of us, corporations and individuals, to pause and re-evaluate what the next ten years will look like. It is clear now that the businesses that successfully and swiftly adopt to automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage.

We will be hosting a virtual expo booth across the three days, June 8th through June 10th, where attendees can reach out to our team to learn more. We will also be hosting virtual lunch and learns, happy hours, and coffee chats. Our Managing Director of EMEA, Jamie Devlin, will also be a featured speaker on Industry 4.0 and sustainable supply chain, Monday, June 8th, 5pm BST (12pm EST).

For a limited time, we are offering our readers, interested in attending our speaking events, the chance to receive a Gold Pass, free of charge. Please click here and provide your full name, title at your company, email address and phone number to receive a Gold Pass.


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College and University Campuses can Combat COVID-19

It’s graduation season around the world and for what seems like the first time, graduation will not commence per usual. The celebratory hustle and bustle of college campuses at this time of year is now replaced with empty classrooms, haunted hallways and desperate hopes that students will return in the Fall. The truth is, nobody knows what will happen in the Fall semester, but students aren’t the only ones feeling the immediate impacts of campus closures. Colleges and Universities are now scrambling to address not only the concerns of parents, students, and staff but also the significant impacts on endowments, revenues and their budgets going forward.

An Inside Higher Ed survey of 172 campus leaders shows that the number one concern remains bringing the students back to campus safely and continuing their high standards for education off campus. However, the financial focus is right up there, “more presidents citing a desire for financial health and operational planning support (60 percent) than for anything else.” Artificial Intelligence can address operational concerns while freeing up financial resources for other concerns such as faculty training and instructional technology.

Source: Inside Higher Ed

While revenues are experiencing immediate impact, the need to protect buildings and assets, ensure environmental compliance is met, and reduce building baseloads becomes more critical as staff and services are less present. After all, students need a campus to return to. Artificial Intelligence, and Maestro specifically, is primed to not only address these impacts in the immediate term but provide long-term stability and digital transformation.

At an operational level, buildings have been closed but the need to maintain them to prevent asset degradation and compliance requirements still need to be met. With fewer people onsite to identify and manage issues and IT stretched with online learning, now more than ever AI and autonomous or remote adoption of solutions need to be applied. At this point, it is likely that there are already significant maintenance backlogs, which AI can address and mitigate future negative impacts of.

The short-term, mid-term and long-term impacts can all be addressed through Maestro artificial intelligence in the following ways:


Short Term: Reduce costs, ensure compliance and protect assets through improved approach to managing assets with limited onsite staff. Optimize baseloads. Identify and prioritize critical failures. Iron out inconsistencies in data. Move to PPM.

Mid Term: Significant cost savings in resource efficiency, maintenance, increase asset life use, reduced capital expenditure.

Long Term: Enhanced scenario modelling for space optimization and asset acquisition ROI assessments.

Benefits like this can be achieved through Maestro’s artificial intelligence and neural network computing capabilities to target significant energy and maintenance cost reduction opportunities through automated, no-cost measures across the campus, eliminating the need for direct human interaction with the on campus assets. A run-rate to deliver a benefit of >$20m annually could easily be achieved in as little as 60 days through a rapid deployment of the technology and the prioritization of the highest energy cost consuming facilities.

In an effort to focus on creating a stable environment for students to come back to, Higher Education Institutions must turn to AI as a remedy for immediate negative financial and operational impacts caused by COVID-19. To learn more about how AI can turn your business operations around, stay tuned for our COVID-19 & AI series or contact our team today to learn more.


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AI & COVID-19: Stabilize & Survive

In the midst of the COVID-19 pandemic, why are corporations accelerating rather than delaying their digital transformation initiatives? The pandemic’s unprecedented impact on demand, workforce, supply chain, short-term costs and liquidity has forced corporations to take immediate, strategic action to maintain operations. In exploring their means of stabilization and survival, corporations found that Artificial Intelligence is uniquely positioned to ensure business continuity in the short-term, with its proven value in improving employee safety & security, short-term costs and liquidity.

While no industry has proven immune to the pandemic, the depth and breadth of its disruption in the manufacturing vertical clearly demonstrates why corporations have adopted transformational technologies over traditional solutions to beat COVID-19. Manufacturers have felt the acute pressure of COVID-19 in their plants and across their value chains.

  • Demand: Sharp declines in demand across non-essential product segments have disrupted each step of the value chain, driving significant earnings adjustments; essential goods producers are struggling to continue operations with heightened risk, and to satiate demand with unprecedented operating and supply chain limitations.
  • Supply Chain: Despite the geographic diversity of supplier networks, sudden overseas supplier shutdowns and domestic fulfillment delays have disrupted if not halted downstream activity, depleting on-hand inventory, prompting a rapid search for market alternatives, and driving material and part shortages, price increases, and an expected spike in upstream transportation costs as restrictions lift.
  • Workforce: Rapid adoption of new distancing protocols, shift structures and offsite resourcing arrangements have ensured employee safety & security, but constrained operating efficiency, quality, throughput and yield; deferred critical asset maintenance and replacement have increased downtime risk and may increase mid-term CAPEX obligations.
  • Short-Term Costs: Essential and non-essential product manufacturers have made significant adjustments to minimize variable costs, maintain business operations, and operate in an environment of significant macroeconomic and trade policy uncertainty, including layoffs, furloughs and temporary plant closures.
  • Liquidity: With strong macroeconomic headwinds, demand and supply side disruption, and constrained operational agility, liquidity is a principal concern of manufacturers that will not be alleviated at the moment restrictions are lifted, but gradually as the supply chain and broader economy rebound.

How is Artificial Intelligence empowering corporations with substantial value chain disruption to act fast and weather the storm?

Elutions’ highly-automated and autonomous Artificial Intelligence solution, Maestro, leverages historical data, deploys rapidly and delivers immediate improvements in safety & security, short-term costs and liquidity. The following Artificial Intelligence use cases are paramount to ensuring business continuity in manufacturing.

  • Remote Operability, Operational Automation & BEP Adherence: By enabling remote asset and process control, visualization and planning, and automated system-driven asset and process optimization, corporations ensure operational continuity, resilience and efficiency, improving employee safety & security, reducing labor requirements and operating costs, and increasing cash-on-hand.
  • In-Line Quality Assurance & Scrap Reduction: By enabling automated quality prediction and dynamic operating parameter adjustment at each stage of production, manufacturers autonomously ensure end-product quality, minimize scrap and rework, and optimize the Unit Cost of Production as conditions change, improving operating margins, yield (revenue), and liquidity through minimized waste.
  • Dynamic Downtime Prevention & Predictive Preventative Maintenance: By enabling dynamic, system-driven alternate control sequencing in the event of a sensor, asset or process failure, corporations autonomously avoid unplanned downtime, associated repair and replacement costs, and foregone revenue. With system-driven Predictive Preventative Maintenance and automated Work Order creation, corporations minimize downtime and production risk, extend asset use life, generate significant savings through right-time, right-size maintenance, and improve safety & security through truck-roll consolidation.
  • Market, Demand & Capacity Driven Procurement & Inventory Management: By continuously predicting raw material costs, sales and capacity alongside the live environment, and enabling automated procurement and IM directives, corporations optimize operating productivity, inventory levels, and the margin value of Inventory on-hand. Similarly, by continuously predicting replacement part costs, process demand alongside forecasted utilization, and automating replacement part purchasing, corporations optimize part inventory levels, reduce short-term costs and improve liquidity.

Beyond short-term survival, corporations have placed their bets on Artificial Intelligence to thrive in the mid-to-long-term. Stay tuned for more market intelligence on how AI is helping corporations build resilience and optimize operations.


Up Next: AI & COVID-19: Transformation


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AI & COVID-19

Throughout modern history, several infectious diseases have spread with sufficient speed, scale and severity to be considered pandemics. Malaria, Smallpox, H1N1, and HIV/AIDS, which remains active, made the list. COVID-19, however, is in a league of its own. The last pandemic of comparable economic impact, if not on human life, was the Spanish Flu, which directly followed WWI and wrought havoc in a significantly less interconnected world than the one in which we live today.

The Global Impacts of COVID-19 have already been unprecedented. “Stay-at-home,” “social-distancing” and travel and trade restrictions imposed to protect public health have had devastating impacts on the global economy, supply chain and employment. How and when this pandemic will end remains unclear. What is certain is that businesses now face an existential threat, and their leaders must take immediate action to set and execute strategies to weather the storm and ensure they are prepared for future economic, operational or human crisis.

In a time when “non-essential” businesses have been forced to shutter operations or shift to remote collaboration, and “essential” businesses face unparalleled demand alongside novel operational and supply chain challenges, how can manufacturers, O&G companies, airports, utilities, universities and other major businesses survive?

If they adapt quickly, can they thrive?

The answer to this question for industry lies in the adoption of end-end Artificial Intelligence.

Over the next few weeks, we will dive into the major business impacts of COVID-19 and how Elutions Artificial Intelligence platform, Maestro, is addressing them across multiple verticals.  We strongly believe that businesses that successfully and swiftly adopt automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage once we return to a “new normal”.

Inspired by industrial trends a multitude of sources, reports by McKinsey and many others, Elutions’ AI & COVID-19 Series will specifically address the themes of Survival, Optimization, and Transformation. 


Survival: Artificial Intelligence applied immediately to stabilize business operations.

Optimization: Artificial Intelligence’s intermediary impacts, growing and preparing for a “new normal.”

Transformation: Artificial Intelligence’s long-term impacts in a post-pandemic landscape.


Check back in with us weekly for new content on how to address the business impacts of COVID-19 through the strategic application of end-end Artificial Intelligence.


Up Next: AI & COVID-19: Transformation


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Why In-House Artificial Intelligence Projects Fail

Companies all over the world, from giant corporations to start-ups, are keen to cash in on the vast value of Artificial Intelligence. With an intent to capture as much of that value as possible, many spend millions on in-house AI solution development rather than outsourcing to address their most critical business challenges. In a world where there’s a feasible DIY solution for almost everything, Artificial Intelligence is most often the outlier. The complexity and cost of AI solution development demands experience to reduce financial risk and ensure speed to benefit, especially in highly competitive sectors.

Think of your business as a human body, and your business challenges as illnesses of varying severity. Some challenges, like some illnesses, are treatable with over the counter medications, while others require a visit to the doctor, prescriptions, long-term treatment or intensive care. If you had an illness that required extensive medical attention, you wouldn’t hesitate to seek out the best medical team for treatment. Should you treat your business any differently?

In deciding whether to go in-house or outsource, it is important to consider how a strategic AI implementation will impact your business. If it’s done right, it will reduce costs, increase revenue and enhance competitive advantage. If it’s done wrong, to what extent is your business at risk?

Financial opportunity from AI abounds across sectors (see the figure below), and there is both margin opportunity and market share on the table for the businesses that harness AI to tackle their strategic challenges first. In other words, getting your AI implementation done fast and right matters, and you must weigh your decision to go in-house or outsource accordingly.

Artificial intelligence (Al) has the potential to create value across sectors. 
Al impact, 
$ billion 
700 
500 
400 
Healthcare systems 
and services 
Public and social sectors 
300 
Advanced electronics/ 
semiconductors 
Retail 
Transport and logistics 
Travel 
Consumer packaged goods 
Automotive and assembly 
Banking 
Basic materials 
Insurance 
Media and 
entertainment 
High tech 
O Oil and gas 
100 
20 
Telecommunications 
Pharmaceuticals 
and medical 
products 
30 
Chemicals 
Agriculture 
Aerospace and defense 
40 
50 
60 
McKinsey&Company 
Share of Al impact in total impact derived from analytics, % 
Source: McKinsey Global Institute analysis

With competitive advantage on the line and the clock ticking, corporations place their bets on whether to navigate the AI journey alone or with partners. Instinctively, they are hesitant to collaborate, tantalized by the prospect of minimizing solution costs, while building their own innovative capacity and owning the resulting IP outright.

Logically, they then look to market outcomes and learn why in-house AI solution development efforts fail more often than not, even in the Fortune100 and at tech companies.

Without experience developing and delivering AI solutions, many corporations fail understand the costs, resources, processes, stakeholders, and even the objectives involved from the onset. As a result, in-house projects often lack a clear and viable design and delivery strategy, roadmap and KPIs, dramatically reducing the speed to benefit if not inhibiting benefit delivery altogether. Program costs and timelines become a driving force for failure. With little transparency into which aspects of the solution will drive the most value, there is no clear way to prioritize spending. Costs either spiral out of control, or corners are consecutively cut in design, development, testing and delivery, resulting in piecemeal solutions that impair data quality, promote bias and diminish solution accuracy, functionality, utility and outcomes.

More often than not, successful AI adopters partner with proven providers on a combination of off-the-shelf solution tailoring, ground-up solution design and solution delivery. How do they decide to partner rather than go it alone?

First, they recognize the competitive imperative for AI—the opportunity cost of following rather than leading in their market—along with the direct costs of failure, and their lack of in-house knowledge and experience with AI solution design and delivery. Second, they find a provider with a successful track record in similar or analogous environments. Third, they develop trust with that provider by laying the groundwork for a happy marriage in contracting. Then they see it through. From the leadership level-down, they commit to the partnership and collaborate from end-to-end to ensure project success.

Strategic AI implementations are broad in scope, capturing data and impacting activities across corporate ecosystems. This complexity is readily apparent in industry, where AI not only provides data-driven direction for decision-making at every step of the value chain and in every organizational department, but directly informs control and automation strategies in production, testing, packaging, distribution and even purchasing.

In recognition of the immense value and complexity of AI in industry, and the competitive need for speed in adoption, the World Economic Forum, in collaboration with McKinsey & Company, has published a toolkit of “practical recommendations” for industrials to accelerate their AI journey at scale. Appearing in The Next Economic Growth Engine Scaling Fourth Industrial Revolution Technologies in Production, this toolkit advocates the adoption of proven AI solutions and related technologies through a partnership and acquisition approach rather than in-house development.

Figure 6: Industry toolkit for accelerating adoption of technology 
Value delivery engine 
Intelligence 
• Predictive maintenance 
• Machine learning-supported, 
root-cause problem-solving 
for quality claims 
Connectivity 
Augmented reality-guided 
assembly operations 
Real-time IOT-based 
performance management 
Flexible automation 
• Robots to automate 
challenging tasks 
• Real-time product release 
39 high-impact digital applications ready for deployment 
Scale-up engine 
Mobilize 
Mobilize the 
Organization 
Strategize 
Set the vision and the 
value to capture 
Innovate 
Spark innovation by 
demonstrating the 
value at stake 
Scale up 
Capture full value 
& Company, Fourth in With the World

With more and more data available for exploit across industries, the opportunities for its monetization through AI are greater and increasingly complex. So too is the risk of getting your implementation wrong.

Can your business afford the DIY approach?


Challenge us to solve your unsolvable business quandaries.


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Facial Recognition, Literally?

Artificial Intelligence is transforming the way consumers purchase, the way business is conducted across industries, and the multi-billion dollar beauty industry is not getting left behind. In fact, there are a multitude of companies using AI to personalize and revolutionize skincare, haircare and everything in between.  Using AI to personalize the experience may prove to be one of the best ways to differentiate in a heavily saturated market.

Is AI the answer to not only changing how consumers interact with beauty product, but also the answer to future product development?

In a market as personal as cosmetics, specifically skincare, where everyone has unique concerns and desires, the ability to use Artificial Intelligence to personalize could be truly revolutionary. Is it possible that the key to ageless, flawless skin is Artificial Intelligence? The women behind PROVEN skincare believe that it is. PROVEN uses AI, aggregating data into the world’s largest skincare database, The Skin Genome Project, 8 million consumer reviews, 100,000 skincare products, 20,000 ingredients and 4,000 academic journals, to tailor skincare products to consumers’ specific needs. Consumers go to PROVEN’s website, take a three-minute skincare quiz and are provided with a skincare routine, taking the guesswork out of which products will deliver the best results.

“Using your answers to our Skintelligence QuizTM, our database instantly sifts through this incredible amount of information to select the best ingredients for your skin. This means you won’t waste time and money trying out products that may or may not work. And if your skin changes, your skincare can evolve right along with you.”

Proven

Taking the concept of Facial Recognition quite literally, FOREO, a tech-enabled skincare and oral care corporation, has recently launched a product that uses facial mapping and artificial intelligence to up your skincare routine. The Luna Fofo analyzes your skin and produces real-time readings that in turn customize your smart facial massage and cleansing routine. The Luna Fofo doesn’t do a one time analysis, rather it continuously analyzes your skin and constantly customizes your routine to your skincare concerns, even tracking your skin’s hydration levels. All of this is stored in a user friendly app so you can track your daily skin health with ease.

These are just a few consumer product-enhanced forms of AI that are transforming the beauty industry and the way consumers interact with AI daily. Beyond customer interaction, could AI enable advanced data capture and analysis to drive product development?  Manufacturing?  Sourcing?

Where is the limit of expansion for AI technology in business?


Challenge SolvetheUnsolvable to change your industry with AI.


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DNA Testing: Is knowing your heritage worth risking your privacy?

Consumer data is becoming a form of currency for most corporations. If it seems like every company is constantly trying to get you to share your data, it’s because they are. Data, especially when it’s connected to your specific demographic profile, is extremely valuable to companies to gain insights about a multitude of trends in order to target advertising and more. But what makes our personal genetic data so valuable? And why are we so willing to give it to genetic-testing companies?

Do we realize what personal rights we are forfeiting in the future when we eagerly dive into knowing about our past?

If data is so valuable, we should be protecting it the way we would protect our wallets, but often there is little care given to our personal data or meta-data. When genetic-testing companies exploded into the market, consumer response was huge. It felt like every one of our family members, friends, and co-workers were finding out more information about their genetic makeup and sending the kits out as gifts. All the hype and the benefit of having a deeper understanding of genetic history was enough for many people to jump on the trend without giving much thought to the risk.

“The key thing about your genetic data … it is uniquely yours. It identifies you, so if you are going to entrust it to a company, you should try to understand what the consequences are”

Jennifer King, director of consumer privacy at Stanford Law School’s Center for Internet and Society

The risk of giving so much genetic data to these companies, whether they are helping you learn more about your allergens or genetic makeup, may outweigh the benefits. One of the biggest risks with data privacy is when third parties get involved and both Ancestry and 23andMe have been investigated by the Federal Trade Commission over their third party policies.  Most of the third party sharing is able to be opted in or out, but many consumers choose to opt-in regardless of if they know what they are truly sharing.

Another large risk we take when using genetic- testing is the physical sample submission. With Nest or Alexa, often times we can delete our data and profile but how could our society regulate the destruction of our physical sample if we decide we no longer want companies to have it. The physical sample has also been something of major interest to law enforcement. This could definitely be viewed as a positive, considering the suspected Golden State Killer was identified due to a DNA partial match. This technology allowed a partial match to shrink the suspect pool from millions to one family tree.

But is law enforcement looking to these privatized genetic-testing companies a violation of our rights? Is the regulation of technologies quick enough to protect us?

Artificial Intelligence combined with the in-home healthcare testing industry could very well be the key to solving the global healthcare crisis, as discussed in previous articles at solvetheunsolveable, but data protection remains a key concern. Artificial Intelligence is allowing patients and doctors to connect to vast databases and learn more about their personal diagnoses in just moments, something that not too long ago could take months or years. However, the data harnessed could be used for the wrong reasons when in the hands of for profit organizations. When consumers opt-in to sharing their data under the guise of finding the cure to a disease, they believe they are making the world a better place but who really stands to profit from that data?

People do think they are helping the world, helping society, even though they may not as an individual benefit. But if your DNA helps develop a drug for a pharmaceutical company, there is nothing governing what they do. It could be a drug they sell at a high profit but doesn’t help the world become a better place.

Jennifer King, director of consumer privacy at Stanford Law School’s Center for Internet and Society

The lack of transparency is confusing to consumers and this is often an intentional strategy from companies in order to profit off of consumer data. Consumers should be very careful of releasing their most intimate data, their very own DNA. In the effort to learn more information about our history using our genetic data, we could be negatively impacting our future.


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Up Next: AI & COVID-19: Transformation

Facial Recognition, Data Privacy and Your Identity

For age old reasons, the government issued ID or passport has been the official link between our facial features and our identification. And the two in combination have been the traditional way of both authenticating and identifying us on an ad-hoc and transient basis at bars, banks, airports, and so much more…

The range of how our identity and facial features can be used in both private affairs and civil procedures is virtually endless, even without our knowledge or explicit consent. The regulation of usage is a difficult topic for unanimous agreement surrounding our privacy and safety in the same world where freedom of expression, movement and liberty contribute to our livelihoods.

Then we introduce technology to the equation.

Where technology adds a level of magic, comfort and efficiency to our lives, never experienced before relieving us of the boring, mundane and impossible it also adds a level of risk to our data privacy and security. And we all know that once something has been introduced to the internet, it’s near impossible to remove.

Take Google Nest Hub Max – we entrust it to connect us to our homes when we are far away for us to track and see for ourselves key events – saving energy, ensuring comfort and convenience whilst maximising the surveillance and security of our babies, dogs and homes. But can we trust where Google is storing our most sensitive data and what they are doing with it? Nest uses Face Match, facial recognition software, which is enabled by the front facing always-on camera for security, to understand which user is using it and for video calls. If the feature is on, the detection is constant and the security of our data, how it is being processed and stored, cannot be guaranteed. The detection can however be turned off, but at the detriment to functionality.

Turn to Apple photos, Google Photos and Facebook tagging – instances where facial recognition is applied to data you provide, aka your photos. The ease of photography, the popularity of the selfie and the constant desire to update your friends, family and followers on your day-to-daymeans bulky streams consisting of hundreds if not thousands of photos. Manually organising these photos is administrative and time-consuming, in other words, something AI and automation can now do for us. So when Apple’s algorithms can identify the faces of your family and friends, even your pets, organise them and allow you to search by face, does this functionality make the security risk worth it?  

Facebook’s facial recognition feature notifies you when others upload photos of you. Whilst recent developments enable an individual to opt-out of this function, there is no guarantee that Facebook itself is not scanning and processing your image. Harnessing your identity to potentially create an online profile of you to sell to advertisers and who knows what else. Likewise with Google – which uses facial recognition and automation to autotag photos of you and your friends – you can also choose to opt out, but you have no control over what your friends may decide to do with photos of you and where that data publicly ends up.

All of these technologies and instances of applied facial recognition also enable facial mapping, providing swift and secure entry into our smart phones – deeming them impenetrable when in the wrong hands. Once unlocked, a further safeguarding layer of facial recognition is provided for mobile payments like Apple Wallet, which unlike other touch-less forms of payment, has no limit.

Whilst there is an enigma surrounding where our facial image data actually lives inside of Google, Facebook and Apple’s servers, how secure it is and how effective is the encryption?  One thing is certainly clear, the multi-purposes of our devices and their built in sensitivity to our changing environments that simplify and augment our lives  – be it Nest which knows, in real time, the occupancy of our homes and our preferred weather, or our phones which house our banking details alongside thousands of images, text and browser history – the future of our data privacy begs the question:

Is the cost of convenience and our need to publish and document our life’s moments  worth more right now than the risk of jeopardizing our privacy and possibly identify?


Up Next: AI & COVID-19: Transformation


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Enterprise Artificial Intelligence – Academic Theory or Ready for Primetime?

Solvetheunsolvable has already explored various aspects of consumer AI and products purporting to leverage AI technologies, but is AI for Enterprise ready for primetime?

Investors aren’t the only ones betting big on Artificial Intelligence, it turns out Higher Education is also investing heavily into the space. With heavy investment in research and development, enterprise level AI seems to be having a rocky start.  Earlier this month Northeastern University allocated $50 million to an Institute for Experiential Artificial Intelligence. This institute will be dedicated to uniting leading experts to solve the world’s unsolvable problems.

“This new institute, the first of its kind, will focus on enabling artificial intelligence and humans to collaborate interactively around solving problems in health, security, and sustainability. We believe that the true promise of AI lies not in its ability to replace humans, but to optimize what humans do best.”


Northeastern President Joseph E. Aoun

This isn’t Northeastern’s first step into the world of Artificial Intelligence and Automation. They already have an Institute for Experiential Robotics that is bringing together engineers, sociologists and other experts, including economists, to design and build robots with abilities to learn and execute human behaviors.  Northeastern isn’t just building Institutes for experts to conduct research, they are making it a priority to prepare their students for success in the age of artificial intelligence. They have an entire curriculum dedicated to what they call, humanics which is a key part of their strategic plan, Northeastern 2025.

Northeastern 2025 Promo Video

“We are building on substantial strengths across all colleges in the university,” said Carla Brodley, dean of the Khoury College of Computer Sciences. “Experiential AI is highly relevant to our mission.”

Though Northeastern is an example of one university betting heavily on AI, they are not alone in their quest to equip students with proper education for the AI-enabled future. In fact, government agencies are getting involved in funding AI in Education. The UK has pledged to invest £400 million in math, digital and technical education through the government’s AI sector deal to protect Britain’s technology sector amid Brexit and an additional £13 million for postgraduate education on AI. In the US, just a few days ago, the National Science Foundation announced a joint federal program to fund research focused on artificial intelligence at colleges, universities and nonprofit or nonacademic organizations focused on educational or research activities. 

The National Science Foundation is awarding $120 million to fund planning grants and support up to six institutes, but there’s a catch. Each institute must have a principal focus on at least one of six themes:

  • Trustworthy AI
  • Foundations of Machine Learning
  • AI-Driven Innovation in Agriculture and the Food System
  • AI-Augmented Learning
  • AI for Accelerating Molecular Synthesis and Manufacturing
  • AI for Discovery in Physics

As universities and governments bet big on the future of AI and education, it underscores the importance of AI on a global scale in the future, but does it call into question the current existence of AI solutions ready to take business to the next level? Utilizing AI and automation will be imperative for corporations to remain competitive and for the advancement of business, but when will the floodgates be swept open, and by who, remains a mystery.

Will you leap into the future and embrace AI now? How do you see the futuristic vision of enterprise AI transform your business? Challenge Solvetheunsolvable with your business conundrum or leave your thoughts in the comments below and let’s explore what AI can do for you. 


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