Audi recently published a blog post discussing its online learning initiative and partnership with Udacity
Artificial intelligence (AI) promises to revolutionize the automotive industry and, more importantly, the automobile. It’s no surprise that Audi has invested in its employee “data camp” training focused on big data and artificial intelligence. Intelligent robots, digital mobility services, and autonomous cars will all rely on these skills, so Audi is staying one step ahead. The company has partnered with Udacity to help accelerate its transformation into a digital car company.
Today’s businesses are undergoing a digital transformation. The Internet of Things (IoT) is making smart homes, smart factories, and smart cities possible. Autonomous vehicles are changing the transportation industry. Artificial intelligence and machine learning are enabling predictive approaches to decision making and driving business insights.
This digital transformation that is sweeping industries by storm would not be possible without data. Data is the enabler of new technologies and solutions. Data is where important and actionable business insights are derived. In a recent Udacity webinar titled “Shaping the Future of the Workforce,” the discussion centered on how Artificial and data science are the building blocks of digital transformation and there is a massive skills gap and substantial competition for talent surrounding those skill sets.
Regardless of the industry, companies are struggling to find qualified and experienced talent to not only help make sense of all the data but to use the data to be competitive. “How is your company going to deal with all this new information – as quick as your competition? There are key data job openings you need to fill and time is not on your side,” said Andrew Cartwright, Enterprise Sales Lead at Udacity.
Breakthroughs in machine learning, supported by the huge explosion of data are fueling the rapid rate of growth and development of artificial intelligence (AI) regardless of the industry. AI is at the forefront of a tidal wave of disruption. Employees today not only lack the right set of skills, but the ones they currently have are becoming obsolete over time. And, companies want to integrate AI strategies, but the don’t have the right talent with the right skills. In fact, there are less than 10,000 professionals in the world with the skills necessary to tackle AI. “Yet, we know the talent need for AI is over one million and we currently have over 100,000 students studying AI related fields. So, one of the biggest roadblocks in the active adoption of AI across industries is the sheer scarcity of appropriately skilled professionals,” Andrew Cartwright reiterated.
In order for organizations to bridge the talent gap the webinar stressed four key areas:
establish continuous workforce training,
derive proficiency in real-world skills beyond videos and online tests,
establish ongoing workforce assessment and calibration,
generate access to top-tier talent pool, internal and external
Academic institutions, companies, and online education providers are combining their efforts to find and foster talent. Organizations can enrich their staff through internal training, while at the same time creating the right conditions to accumulate and retain new talent.
The concept of lifelong learning is accordingly transforming from a discretionary aspiration to a career necessity. No longer is it a supplemental luxury to learn new skills, and no longer is learning new skills something you do only when you’re pursuing a significant career change. Being relevant, competitive, and in-demand in today’s fast-moving world requires an ongoing commitment to lifelong learning regardless of your role or career path.
At Udacity, we are committed to very similar objectives and strategies. Our industry partnerships are critical to the success of our approach, both in terms of establishing “a true 21st century curriculum,” and for developing a “clearer view on future skills and employee needs.” Our emphasis on learn-by-doing is fueled by our desire to help see every employee we teach be in-demand.
When you invest in the education of your employees, you give your company the gift of a long-term solution to your talent needs
(Originally posted on blog.udacity.com. Written by Christopher Watkins)
The following quote has been variously attributed to everyone from Lao Tzu to Maimonides to Anne Isabella Thackeray Ritchie:
“Give someone a fish, and you feed them for a day. Teach someone to fish, and you feed them for a lifetime.”
Given its ubiquity throughout modern history, it’s clearly a resonant message, and part of its appeal has to do with its broad applicability—it’s germane to so many different use cases.
The quote is generally interpreted as a lesson about self-sufficiency, but it’s also sage advice when thinking about short-term “band-aids” vs. long-term solutions. Why solve something for a day, only to have the same problem again tomorrow? Why not embrace a long-term solution that eliminates the problem once and for all?
Hiring managers and recruiters confront this issue every day. After all, hiring is essentially an act of problem-solving—a company has a need, and the right hiring decision will solve for it. But what IS the right hiring decision? If you’re a company in need of talent, the solution is often right in front of you!
Let’s take the example of a company website.
Company X is a small company. They have a website, but it’s not very good, and it’s becoming a problem. They need a new site, but no one internally has the skills to do the work. What should Company X do? One solution is to hire someone from outside their organization to do the work. In theory, this makes sense, because professionals will know what to do, and how to do it. The challenges with this approach, however, are multi-fold. One obvious issue, is that there’s no real way to know whether the outside entity will do a good job. But the bigger question is, how can you know whether they’ll “get” you? A website isn’t just functional. It’s a symbol of brand identity. It communicates values as much as it provides services. So you want to work with someone who understands who you are as a company. Finding an outside entity that is both reliable, and that understands your brand, is difficult, and even if you DO find someone, they’re not yours for keeps. They do the work, then they’re off to the next client.
Hiring an outside entity often results in a “fed for a day” solution. If all goes well, you’ll get your new site, but as your company expands and evolves, you’ll be hungry again soon.
So what’s the alternative?
If you’re in a Company X kind of a situation, take a moment to look around you. What do you see? Chances are, what you see are dedicated, reliable, hardworking individuals who are committed to your company, and who most definitely “get” you. But at first glance, you might not be seeing the people who can build your new site.
Or are you?
Here at Udacity, we think you are! We think there are people at your company right now, who are just a Nanodegree program away from giving you exactly what you need. Don’t believe us? Poll your employees today. Find out whether someone at your company harbors an interest in web development. Chances are, there’s someone who’d jump at this kind of opportunity.
So, here’s a suggestion for companies in need of talent. Instead of investing in a one-time, short-term approach, invest in a Nanodegree program on behalf of one or more of your employees instead, and give your company the gift of a long-term solution to your talent needs.
Employees, this is an action item for you as well. If you’ve got a passion for something, and you think pursuing your passion can help your company, speak up! That’s what Kat Halo did. Her company hired someone else to do their marketing, but Kat knew she could do a better job. She took it upon herself to learn digital marketing with Udacity, and now, she’s doing marketing for her company!
There are a great many tangible benefits to hiring from within. A recent CareerBuilder article affirms that you’ll save money and see better performance, and Adam Foroughi, writing for Entrepreneur, notes the following:
Motivated employees work harder.
Opportunity, happy people = higher retention.
Internal hires adapt better to new roles.
And finally, as noted in a recent article from Inc., “Wharton research shows that external hires cost18 to 20 percent more than those promoted from within.”
In a world marked by rapid technological advancement, more and more companies all across the hiring landscape are embracing digital transformation initiatives, and this is leading them to look anew at the talent within their own ranks. At Udacity, our Enterprise team works directly with hundreds of different companies who are investing in their employees by proactively offering opportunities to reskill and upskill through our Nanodegree programs. If you’re not yet investing in the talent you already have, now’s a really good time to consider doing so!
Let’s now return to our quote:
“Give someone a fish, and you feed them for a day. Teach someone to fish, and you feed them for a lifetime.”
The key lesson here lies in the distinction between “a day” and “a lifetime.” As a company, when it comes to making hiring decisions, you want to invest in a long-term solution that works for the long term, and that’s what investing in the development of existing employees is all about. When you need talent, you often need look no further than the people right in front of you.
Solving problems and answering questions through data analysis is quickly becoming the norm in today’s data-driven world. As real-world experiments become ubiquitous in modern business, data scientists have become the beating heart of the big data economy. It’s not just that they are designing new systems; they are going to bat for new sources of data and new ways to use that data.
Yet, with the ever-increasing demand for skills, the talent gap has widened. In a recent annual survey of employers, Deloitte and the International Society of Certified Employee Benefits Specialists (ISCEBS) remarked, “The shortage of qualified talent and the skills gap has emerged as the biggest challenge facing employers over the next three years.”
This skills gap continues to widen, despite the available pool of domestic and H1B job applicants. How can employers expect to fill their needs for such capabilities in emerging technologies?
More and more smart companies are training their existing employees to acquire the skills they need in the technologies and disciplines that are critical to their evolving business objectives.
Use training strategically to fill skills gaps
As technologies rapidly evolve and corporate initiatives change, talent development is proving to be a faster and more cost-effective solution than talent acquisition. “Upskilling”—investing in the skills of front-line workers—has upfront costs, but it can save employers time and money in the long run. When employees are always learning, it has the effect of reducing turnover and improving employee retention, helping a company keep pace with or outdo its competition. Upskilling also allows companies to retain employees who fit within the company culture; it’s much less risky than bringing in someone new.
And while upskilling can be used in many circumstances, it can have big returns if a company:
Is looking to find more efficient processes;
Finds that machine learning, big data, and data science are playing an increasingly important role in the workplace;
Is in an industry that is under tough competitive pressure or that evolves quickly;
Wants to find new ways of doing business;
Is looking to offer new products and services
Re-Skilling Existing Employees
Here at Udacity, we’ve developed a solution for Enterprises that enables them to assess their workforce, understand their skills gaps and deploy transformational, hands-on and cutting edge curriculum personalized to their employees. The costs of re-skilling employees far outweigh recruiting, training and ramping a new employee.
In addition to saving time and money, reskilling employees maintains established corporate culture, enables uninterrupted employee productivity, and provides other benefits to your organization, including:
Improved employee engagement and retention by building self-esteem with a culture of higher promotion potential and refreshingly novel or challenging responsibilities.
Better company brand reputation (on employer review sites like Glassdoor.com) as a place for career development and longevity for future candidates.
Reduced dependency on outside consultants or vendors for necessary skill sets.
As Henry Ford, founder of Ford Motor Company, professed, “The only thing worse than training your employees and having them leave is not training them and having them stay.”
Find out how much your organization can save using Udacity for Enterprise to transform your workforce.
Emerging areas, such as machine learning, artificial intelligence (AI) and big data, require special skill sets in high demand. Beyond traditional four-year degrees and time-intensive training programs, the alternative paths to developing those skills are limited. The learning required is not something that can be accomplished through a Netflix or YouTube-style exploration of a catalog of videos. Training in machine learning or AI requires deeper, more structured learning and commitment.
As AI moves beyond proof-of-concept and sandbox implementation, companies are looking to recruit top machine learning talent, cultivate AI skills across their workforce, and begin to use this amazing set of technologies for incredible outcomes. There’s just one problem. There’s still not enough AI experts out there to make this a reality – and a huge AI skills gap is opening up as a result. Continue reading “Enabling companies to bridge the Artificial Intelligence gap with Nanodegree programs”→
Udacity Artificial Intelligence and Data Industry Advisory Board
As we look forward into a future we know will be shaped by the transformational impact of artificial intelligence and data technologies, we can clearly see the birth of a new knowledge ecosystem within which education, industry, and technology form a powerful partnership. That these three arenas will be interrelated goes without saying, but how they inform one another, and how these relationships take shape and evolve, remain open questions.
At Udacity, we recognize the singular role we occupy, existing as we do at the crossroads where education, industry, and technology meet. We are a learning provider that teaches AI and data skills, in partnership with industry, and as such, we see a unique opportunity—and feel a special obligation—to both facilitate and contribute to the global conversation around critical issues we face as we move into our AI and data-powered future.
We are very excited to have recently formed an Artificial Intelligence and Data Industry Advisory Board with the expressed goal of bringing together leading experts in the field to consider the opportunities that lay ahead, to address the challenges we face, and to answer the questions we must answer.
We believe that through combining experiences and skills, sharing insights and ideas, and producing solutions and strategies, we can lay out a plan for the future that is beneficial to all—a plan that nurtures and supports emerging generations of learners to master artificial intelligence and data skills, encourages and incentivizes industry to adopt beneficial AI and data practices, and guarantees a pipeline of highly skilled individuals who are committed to social good ideals, and the ethical adoption and implementation of transformational technologies.
Among the experts who have joined our board is Armen Pischdotchian, the Academic Tech Mentor at IBM. In his role, he mentors university faculty and students, and conducts enablement sessions—both in and outside of the company—pertaining to the IBM Watson Solution offerings. Here is Armen on why he wanted to be a part of the board:
“I strongly believe that the Advisory board, at its core, is addressing a gap that needs to be erased, and that is the space between industry and education. Udacity has the unique pedigree of listening to the needs of tech giants and startups and asking the question, what does your candidate need to be proficient so the firm will succeed?”
Armen is joined by an incredible roster of individuals who come to us from leading organizations such as Amazon, Google, NVIDIA, and more. It is with both gratitude and excitement that we introduce the inaugural members of the Udacity Artificial Intelligence and Data Industry Advisory Board:
Armen Pischdotchian, Academic Tech Mentor, IBM
Brad Klingenberg, VP of Data Science, Stitch Fix
Bryan Catanzaro, VP of Applied Deep Learning Research, NVIDIA
Cyrus Vahid, Principal Deep Learning Solutions Architect, Amazon
Dan Becker, Head of Kaggle Learn
Derek Steer, CEO, Mode
Jeff Feng, Product Lead, Data, Airbnb
Joe Spisak, Product Manager – Artificial Intelligence at Facebook
Jon Francis, VP of Customer Marketing Analytics & Optimization, Starbucks
Josh Gordon, Developer Advocate for TensorFlow, Google
Mike Tamir, Head of Data Science Uber ATG & Data Science Faculty member at University of California at Berkeley
Warren Barkley, GM, AI and Research, Microsoft
While each of these individuals brings to the board a wholly unique set of experiences and insights, they are united by a shared passion for learning, and for building a better future through the beneficial use of transformational technologies.
Our mission is to provide companies and their employees with meaningful opportunities to master valuable and in-demand skills. Jeff Feng is the Product Lead for Data at Airbnb, where he leads a team building machine learning infrastructure, data infrastructure, data visualization tools, and their experimentation platform. Here is Jeff on the passion that drives his participation:
“Shaping how people and machines make decisions with data is one of the most critical skills needed in the workforce over the next decade. Thus, providing learners with the practical knowledge needed to work with data is an area I am hugely passionate about.”
We look very forward to sharing more updates about the work of the board, and to furthering our engagement with the important issues and incredible opportunities before us. As we advance our efforts, we are thankful above all else to our board members for their spirit of generosity and goodwill, and for their commitment to the true ideals of education. Josh Gordon, Developer Advocate at Google, put it both perfectly and simply when he stated the following:
“Good teachers are hard to find. I’m grateful for those who helped me out over the years, and it’s always been important to me to give back.”
We are grateful to the members of the advisory board, and we are excited to transfer insights gleaned from their leadership to you, our students, for it is who are the emerging leaders that will define the future we are eagerly building towards.
For more information about how Udacity for Enterprise is helping companies transform their workforce, click here.
Answers to some of the most commonly asked questions about AI
Artificial Intelligence (AI) is the world’s most exciting frontier for knowledge and technology. Everywhere you look, people are talking about intelligent machines improving our lives. For all of the excitement, many of the concepts and applications are still highly technical, and can be confusing if you’re not familiar with the basics of AI. If you, your company and your employees have questions, you certainly aren’t alone!
Read on to learn answers to some of the most commonly asked questions about AI.
What is Artificial Intelligence?
This is an important first question; here are key definitions everyone should know:
Artificial Intelligence
Artificial Intelligence is a branch of computer science focused on building computers and machines that can simulate intelligent behavior. Artificial Intelligence systems are able to perform tasks traditionally associated with human intelligence, such as visual perception, speech recognition, decision-making, and translating languages.
Algorithms
An algorithm is a series of mathematical instructions created for a machine to follow. Think of it as simple step-by-step instructions: do A, then B, then C. In AI, programmerscreate algorithms that tell a computer to look at data, identify a problem, and learn from its attempts to solve the problem.
Machine Learning
Machine learning is one of many algorithms used in AI. The machine learning field is concerned with designing programs that learn to make predictions from data, alone, without requiring assistance from a programmer. These algorithms are used in applications such as music recommendations, spam filtering, and fraud detection.
Deep Learning
Deep learning is built on neural networks, a kind of machine learning model structured in a way that resembles neurons in a human brain. In a neural network, artificial neurons are arranged in interconnected layers. There is an input layer to receive data from the outside world, and there is an output layer which dictates how the system will respond to the information. Between these two layers, there are additional “hidden” layers of neurons, which process data by putting a numerical weight on the information they receive from the preceding layer, and passing this information to the next layer in the network. A neural network can solve very complex problems because of the huge quantity of neurons working together. Deep learning gets its name from “deep” neural networks, with dozens or even hundreds of hidden layers. These networks are powering the AI revolution with state-of-the-art object detection, machine translation, and audio synthesis.
Natural Language Processing
Natural language processing is how we get computers to understand, process, and manipulate human language. To achieve this, a computer needs to be able to “understand” a huge amount of information—from grammar rules and syntax, to different colloquialisms and accents. In a speech recognition system, for instance, human voice input becomes audio data, which then gets converted to text data, a difficult process in itself. This text data can then be used in an “intelligent” system for various applications such as translators, or controlling devices like TVs.
Computer Vision
Computer vision is aimed at helping computers identify and process images in the same way humans do. Just as we learn to distinguish between the faces of different people, computer vision aims to teach machines to recognize different objects that it “sees” through a camera. It does this by looking at individual pixels, identifying different colors, and converting them to a numerical value, then looking for patterns so that it can identify groups of similarly colored pixels and textures. This helps it identify different objects.
Where is AI already being used?
AI is already present in many aspects of our lives. Examples include:
Smart Assistants. Smart assistants, such as Siri, Alexa, and Cortana, use natural language processing to understand voice commands—setting reminders, finding music, answering questions, even adjusting your thermostat—all from a home speaker or your smartphone.
Car “Autopilots.” Cars on the road today already use computer vision to operate a range of safety systems—such as tracking traffic around your car, and braking autonomously if the system perceives a danger ahead. To do this, the car needs to be able to rapidly identify different images, predict what could happen, and make a decision on what to do.
Recommending Purchases. Popular shopping websites use AI to track what you browse, what you buy, and what you save to look at later. It then uses this information to better tailor the products and services it recommends to you. As the customer, this saves you time searching for what you want. For retailers, it means being able to predict demand for products so they have the right stock in the right places. This improves delivery times and maximizes their chances they are able to sell you something you actually need.
Protecting your money. AI is used to constantly monitor bank accounts for potentially fraudulent activities. AI systems track all your purchases over time, and build a profile of your spending habits. The system can then rapidly flag any purchases that seem unusual. For example, if 99 percent of your purchases happen in your hometown, then suddenly a slew of purchases in another country show up, your bank can contact you to check if your card has been stolen.
Ride-sharing. Ride-sharing apps like Uber use machine learning to accurately predict when the car you book will arrive. When your app tells you that your driver will be arriving in three minutes, machine learning has been used to analyze the data from millions of previous customer trips to hone that prediction. AI techniques are also used to determine how many cars Uber needs to have on the road at any given time, and in what areas; for example, helping ensure there are extra cars around major stations at peak commuting times.
What AI developments are set to change the world?
Here are some of the most exciting AI developments experts expect to see in the future:
Fully automated transportation. AI will play a major role in the development of fully automated transportation systems—from self-driving cars to flying vehicles. Advanced AI systems will help vehicles react safely and intelligently to variable conditions such as other traffic, weather, and road conditions. This will result in transport that is much safer, quicker, and far less stressful than being in control ourselves. Autonomous transportation solutions will also reduce the amount of time people waste commuting through traffic, and free them up for more productive activities.
Taking over dangerous jobs. Some jobs are inherently dangerous—such as working with hazardous chemicals. As AI develops, robots with the capacity to make intelligent, independent decisions can take over these roles and remove the need for people to risk their lives doing them.
Faster and more accurate medical diagnosis. AI can help doctors increase the speed and accuracy by which they diagnose and treat medical conditions. Doctors will work with AI systems that can access a global database of medical conditions. The AI machine will compare patient symptoms with similar cases, and make recommendations almost instantly.
AI is poised to be the defining technology of the 21st Century. If you are ready to transform your workforce, provide critical upskilling for your teams, and gain competitive advantage, Udacity for Enterprise has a solution that is right for your organization.
Everyone at Udacity is elated with the news from CNBC, that we have been named to their prestigious Disruptor 50 list for a third time—and at #8, our highest ranking yet! It’s certainly thrilling to find ourselves in the company of such world-changing organizations as SpaceX, Airbnb, and Didi Chuxing. We appreciate the continued recognition from CNBC, and are excited that our efforts are having a sustained impact.
Disruption equates to change, and change informed by good intent is a powerful thing.
Udacity has grown from a big dream in a tiny room, to a global community comprised of hundreds of businesses, millions of passionate learners, dedicated educators, and forward-thinking industry collaborators who have come together to create a culture of success and achievement. Growth and change are made possible through collaboration, and the unifying desire to contribute meaningfully to progress.
“Coming together is a beginning, staying together is progress, and working together is success.” —Henry Ford
We collaborate with visionary industry leaders to ensure that what our customers’ employees learn are the most valuable and in-demand skills. And we bring the world’s leading experts into our programs to provide transformative instruction for our community. Together, we create the Udacity experience.
To receive this acknowledgement from CNBC offers us the opportunity to recognize the contributions of every member of our community, and best of all, it provides us the chance to thank our customers, partners and learners. To the 8 million, and counting, of you, thank you! There is no Udacity without you.
To learn more about our Enterprise solutions, click here.
Qualifications, credentials, and experience remain vital considerations when assessing candidate suitability for a key role. We’re not here to debate that. What we ARE here to do is to propose a rethink about what constitutes applicable (read: relevant!) qualifications, credentials, and experience. Because what you really need in your candidates today, can’t necessarily be measured by traditional means. What you need are people with lifelong commitments to learning, the ability to easily and quickly adapt, growth mindsets, and a fluent command of modern tools and technological advances.
There was a time when a college degree was virtually the sole measure of job-readiness. That time is gone. There are simply too many other, more effective ways to find and vet crucial talent. That’s not to say a college degree can’t be a key factor; it can. But in today’s hiring environment, the need for specific skillsets is too intense, the pace of change too rapid, the competition too fierce. Companies often need truly rarefied talent, and they’re realizing a college degree is no longer the best determinant of suitability. Agility and flexibility are vital, real-world experience, critical. There is a genuine need to reevaluate hiring practices, and the most innovative companies are already doing so.
