Hi Dave, please tell us a little bit about your role at Upwork. How do you work with AI and other intelligent technologies to build workplace tools?

As GM of Marketplace and VP of Product at Upwork, I oversee the overall product strategy and execution of Upwork’s marketplace, connecting talent and clients all over the world. I lead multiple teams responsible for delivering value to clients who rely on Upwork’s global work marketplace to find and hire the best talent. While we are still in the early days, the rapid rate of change ushered in by Generative AI is certainly impacting both the ways we work to build products, as well as the very products we are building for our customers.

We very much see generative AI as the newest capability in our product development toolkit, and a massive force multiplier for both businesses and talent who come to our marketplace to find and get work done. One of our most ambitious goals is to foster the most AI-empowered independent talent in the world.

As announced on November 6, we are providing both the best third- and first-party tools and educational resources to enable talent to harness the power of generative AI to work smarter, and ultimately get more done. One example of this is the launch of Upwork Chat Pro, a new GPT-4-powered app currently live as a limited-release beta and developed by our Upwork Labs team to allow professionals to start and complete work faster and more effectively.

How has Upwork evolved in the GPT era? What are your key offerings in the AI space?

At Upwork, we’re seeing firsthand the transformative impact generative AI is having on professionals and companies alike, supercharging productivity and efficiency for talent and businesses that need to get mission-critical work done.

AI is the fastest-growing category on our platform this year. Our goal is to become the preeminent destination for AI-related talent and work, while also improving the efficiency, effectiveness, and speed to match on our platform through improvements to our core product experiences and capabilities.

We first welcomed the era of generative AI at Upwork with the launch of the AI Services hub, a singular destination for customers to source the AI talent they need, and get matched with AI-powered solutions and expert talent across virtually every category of work. We also aim to ensure talent on Upwork has access to the most modern generative AI tools to dramatically increase productivity and quality of work. The AI Services hub has seen a 10x increase in average monthly visitors since it debuted in July.

Recently, we built on our offerings with the announcement of an extension of the hub with a new suite of generative AI apps, offers and educational content specially designed for talent this week.

Could you tell us more about your latest generative AI offerings? How do you differentiate your AI apps in the education marketplace?

As I shared above, we introduced a new set of AI apps and offers, alongside new educational content so that independent talent on Upwork can harness the power of generative AI to supercharge their productivity and improve the quality of their work.

Additionally, we launched limited access to Upwork Chat Pro, a new generative AI application embedded directly on Upwork’s platform and powered by GPT-4, developed to allow independent professionals to start and complete work faster and more effectively.

Upwork’s unique position as a two-sided marketplace allows us to introduce our global talent pool to a comprehensive array of best-of-breed AI-based tools and resources. We are partnering with industry-leading developers like Adobe, Amazon, ClickUp, and Miro, that have incorporated Gen AI into their products.

In making these tools available for trial or discount, we are ensuring that our talented professionals have every opportunity to leverage AI tools to do their best work.

In addition to offering these apps to independent talent, our learning center, Upwork Academy, is adding educational content in the new AI Education Library, including AI-related courses, AI learning paths that cover the basics of AI, as well as mini courses. It’s this combination of apps, tools and educational resources for talent that will help upskill their capabilities and leverage the power of generative AI so they stay competitive and become more productive.

What has been your most memorable experience related to Generative AI capabilities in 2023?

Upwork has been fueled by cutting-edge technologies since the company started more than 20 years ago.

We were founded on the idea that technology could break down barriers and borders and bring people together to unleash their uniquely human potential to work together in ways made possible by the technological advances of the last few decades.

Think about the most significant technology shifts in our lifetime – from personal computers to the Web, mobile devices, and cloud computing as the foundational building blocks underlying our own work marketplace.

Today, we’re undergoing another seismic shift with the advent of generative AI and how it will directly impact the future of work. I am particularly excited about the transformative possibilities already unfolding for professionals and businesses tapping into generative AI.

It’s a game-changer for work, and for Upwork, as we seek to help so many professionals and companies embrace this moment of opportunity to deliver major critical business outcomes and ultimately work smarter and more efficiently. It’s truly an awesome and memorable experience to be at a company that is working tirelessly towards empowering millions of professionals to embrace the power of generative AI to continuously serve their respective customers.

Thank you, Dave! That was fun and we hope to see you back on AiThority.com soon.

Hi Steve, welcome to the AiThority Interview Series in 2023. Please tell us about your two decades of tech experience so far. How did you arrive at Mastercard?

My career has had several phases. For the first 10 years or so after graduating, I worked at various – mostly small – independent, software companies and consultancies. My position evolved over the years; I started as a developer before advancing to the role of a software engineering manager and then eventually becoming a CTO.

Next, I worked for Science Foundation Ireland (SF), Ireland’s national science funding agency, where I led our investments in topics such as computer science, data science, software engineering, and artificial intelligence.

In 2014 I started at Mastercard, which is where I still currently work today. Initially, I supported and grew a team called Start Path, an engagement program for innovative startups in the fintech space. A few years later, I joined Mastercard Foundry, the innovation and R&D arm within the company, leading research and development for AI, ML, and now also quantum computing. This July, I was appointed to Mastercard’s first class of Distinguished Engineers, a recognition for select Senior Vice President technical experts as part of the company’s continuing commitment to technology, innovation, and career growth. With this distinction, I continue my work with a focus on artificial intelligence and quantum computing. 

You are in charge of Mastercard R&D’s strategy and execution of AI and ML in new product development efforts. What is the biggest challenge to Digital Transformation in the market you cater to?

Of the many years that I’ve worked in technology – this current period is distinct for the speed and scale of innovation taking place. This dynamism is exciting because we’ve only just scratched the surface of what is possible for businesses and consumers, but with it also comes new challenges for enterprises.

For one – leveraging emerging technologies to build new products and services.

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Part of the equation is to understand and introduce technologies like web3, spatial computing, PETs, and AI/ML, while also maintaining and upgrading legacy systems, and aligning with ever-evolving legislation and regulation governing their application.

AI specifically has been top of mind for our market, especially following the fairly recent explosion of generative AI.  Mastercard has been putting AI to work for years, particularly in our products and solutions across open banking, routing, personalization, and fraud that enhance the safety and security of the payments ecosystem.  Although the step change between AI and generative AI is exponential in terms of what you can do with it, our deep roots in AI have afforded us the capabilities, talent, framework, and partnerships to keep a pulse and execute on emerging technologies.  

As a leader in the payments space, and as with any nascent technology, Mastercard has a responsibility to set the precedent for exploring generative AI responsibly.  We developed an AI governance program and guidelines for our data scientists to minimize risks in AI and best serve our customers, invested in partnerships with key institutions like RIT In Dubai and Howard University, and actively encouraged our employees to safety test and learn. 

What technologies within AI and computing are you interested in?

The idea of being able to control a computer system and anything connected to it through programming has fascinated me since I was a teenager.

Today I’m looking at how AI, mixed reality, spatial computing, and web3 have unlocked an entirely new frontier in technology. We’re likely to see several key trends, such as the rapid increase in computational power, both at the edge and in the cloud, and the tokenization of assets to start to coalesce around some of these new computing paradigms.

For AI, the incredible advances born from generative AI and Large Language Models (LLMs) are also contributing to the transformative period we’re in.

Currently, Mastercard is engaging in test-and-learn with generative AI applications to enhance operational efficiency and improve data quality, aggregation, entity resolution, and categorization.

We’re also using ML for certain models that support our open banking solutions, such as credit scoring, financial management insights, account opening, and payments. It enables us to extract, identify, and classify data quickly and more efficiently than rules-based models alone.

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In the longer term, I’m paying close attention to both quantum computing and AGI. With quantum, I’m tracking developments in both hardware and software, to understand how these new devices will help us to solve ever more complex computational problems, and what use cases will arise in our industry. With AGI, at some stage, we may be looking at the prospect of human-like machines that can solve a wide range of complex tasks at scale. 

In the current analysis, it is reported the global quantum computing (QC) market will be at $900 million. How do you see QC disrupting the digital market in the next couple of years? 

At $900m, quantum computing is still a very small part of the overall computing market.

Over the next few years, we’ll see quantum computers – inclusive of quantum annealers – get progressively more performant, capable, and reliable.

Currently, our best guess is that the earliest use cases in banking and payments will most likely be in the optimization space, with other applications such as machine learning coming later.

Rather than a disruption, it’s more probable that we’ll see quantum technology adopted gradually, across industries and companies, as the technology continues to improve, becomes more usable, and its primary use cases become more evident. 

What steps can young technology professionals take to enhance their proficiency in collaborating effectively with Cloud, Automation, and AI-based tools? 

Nothing beats getting “hands-on-keyboard” experience using these technologies.  One of the amazing benefits that all young tech professionals have today is readily available online learning materials. There are tutorials on YouTube for just about every emerging technology imaginable, and through cloud computing, there’s also access to the resources required to explore those areas. Many cloud and tech companies also offer cheap or free trial accounts to help young developers learn their technologies at little or no cost.

On the Mastercard Developers platform, for example, you’ll find a quick start guide that will walk you through how to create a new project using Mastercard’s APIs, and gain access to the Sandbox environment. So, armed with nothing more than a laptop and an internet connection, people can get access to all the technology they could imagine, even quantum computers!

One of the tried and tested ways to build skills in these areas has been through the open-source community – whether it’s contributing to an existing project that you find interesting or relevant, or starting a personal project that scratches your own itch. 

What are your predictions for AI/ML and other smart technologies heading beyond 2024?

As machine and deep learning evolve, so too will their role within our sector. This past year has been about experimentation. In 2024, we expect generative AI to continue to gradually integrate into business operations and products.

Companies are currently focused on internal generative AI applications, like software development co-pilots, knowledge bots and operational efficiency drivers that are serving as testbeds and laying the groundwork for what’s to come. This phase is likely to continue throughout the year, as companies start building the foundations for implementation. As challenges like data privacy, information accuracy and bias are addressed, we anticipate that the range of use cases will expand to include more ambitious and public-facing deployments.

 

One of the most compelling use cases for generative AI in the financial services industry is in open banking. With the aid of fine-tuned LLMs, generative AI can enable the cleaning and categorization of data at a significantly higher through-put and with more accuracy than previously available.

In line with informed data consent protocols, generative AI could streamline personal financial management, for example, by acting as a personal wealth manager to create an encompassed view of an individual’s financial well-being, help formulate college savings plans, procure loans and implement financial strategies – empowering people to navigate their financial lives more adeptly.

Thank you, Steve! That was fun and we hope to see you back on AiThority.com soon.

Hi, welcome to the AiThority Interview Series. Please tell us a bit about yourself and your company, RelationalAI.

I am the founder and CEO of RelationalAI. I have three decades of AI experience and I often share insights on the rise of the data cloud, knowledge graphs, generative AI and other new-gen technologies. My company brings together decades of experience in industry, technology, and product development to advance the first and only real cloud-native knowledge graph data management system to power the next generation of intelligent data applications.

How do you see the Data Cloud industry shaping in 2024?

In 2024, we will witness the rise of the Data Cloud to advance AI and analytics.

While data clouds are not new, I believe there will be a continued emergence and a clear distinction made between data clouds and compute clouds in 2024. With compute clouds like AWS or Azure, we have had to assemble and stitch together all the components needed to work with AI. So with data clouds, like Snowflake or Microsoft Fabric, users have it all prepackaged together in a single platform, making it much easier to run analytics on data needed to build AI systems. The rise of the data clouds will offer a better starting point for data analytics, Artificial Intelligence (AI), and Machine Learning (ML).

2023 was all about Generative AI and its impact on the Cloud computing platforms. Where is GenAI headed in 2024?

The extreme hype around Generative AI will diminish in 2024. True Generative AI deployments will emerge as its augmented replacement.

In the new year, we will also begin to see the extreme over-hype around generative AI start to diminish. I’ve been working in, and around, AI since the early nineties, AI has always been prone to be over-hyped. Having said that, I think we are going to see enterprises deploying generative AI in more measured and meaningful ways. As with most new technology adoption in the enterprise, it’s going to take longer for these kinds of AI systems to become part of enterprise software in the ERP or HCM sense, but real value will start to be created next year.  We will be able to calibrate our expectations appropriately once we begin to see its true impact.

Please tell us about your predictions about AI startups and the VC landscape.

The venture capital climate has been tough as of late and will be even more so in 2024. I believe we will begin to see a shift in the industry when it comes to the survival of AI startups, as AI startups start to get “acqui-hired” by the big tech companies for their talent. This has already started to happen and in the last few months we’ve seen higher than normal venture-funded companies big and small either shut down or quietly get acquired by bigger players.

I think there will be an evolutionary cycle for the companies that can survive the next 18 months or so. It has been said before that some of the best and most valuable companies are usually created in difficult times, like during the 2008 recession and in 2000 when the dot-com bubble burst, as they usually tend to have better products and more disciplined companies. Companies that can run efficiently, be agile, and adapt quickly to tough situations will be better positioned. At the end of the day, companies that have a strong product, and a demonstrated value proposition, will be in a better position to outrun the competition.

How should IT leaders approach Knowledge Graph solutions? 

Knowledge Graphs will help users eliminate “Data Silos.”

As enterprises continue to move more data into a data cloud, they are collecting hundreds, thousands, and sometimes even tens of thousands, of data silos in their clouds. Knowledge graphs can easily drive language models to navigate all of the data silos present by leveraging the relationships between various data sources. In the new year, we will see a variety of established and novel AI techniques that support the development of intelligent applications emerge.

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Thank you, Molham! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi, welcome to the AiThority Interview Series. Please tell us a bit about yourself and what is D-Wave.

I am Dr. Alan Baratz, President and CEO of D-Wave (NYSE: QBTS).

D-Wave is a leader in quantum computing technology and the world’s first commercial supplier of quantum computers. Our technology has been used by some of the world’s most advanced organizations, including Volkswagen, Mastercard, Deloitte, Siemens Healthineers, Pattison Food Group Ltd, DENSO, Lockheed Martin, the University of Southern California, and Los Alamos National Laboratory.

How do you see the quantum, computing market shaping in 2024?

The global quantum computing market is rapidly growing and some market analysts project it will reach upwards of 6 billion + by the end of this decade. As 2023 closes, it would be interesting to see how quantum computing influences 2024. The future of quantum computing would largely relate to a rapid government adoption, the future of work, and quantum supremacy.

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Will the economic recession affect the quantum computing industry in 2024?

With economists projecting a shallow recession in 2024, organizations will seek new technologies, such as quantum computing, to navigate adversity and bolster business resilience. Quantum technologies can accelerate problem-solving and decision-making for a wide range of common organizational processes, such as supply chain management, manufacturing efficiency, logistical planning, and employee scheduling. Amidst a challenging economic environment, quantum’s ability to fuel operational efficiencies is critical.

How can organizations achieve supremacy with quantum computing in 2024?

The industry will achieve a proven, defensible quantum supremacy result in 2024. Ongoing scientific and technical advancements indicate that we are far from achieving quantum supremacy. 2024 will be the year where quantum definitively outperforms classical, full stop. There will be clear evidence of quantum’s ability to solve a complex computational problem previously unsolvable by classical computing, and quantum will solve it faster, better, and with less power consumption.

The breakthrough we’ve all been pursuing is coming.

What would be the role of the US government in pushing the bar higher in quantum computing innovations and adoption?

The US government’s usage of annealing quantum computing will increase given the anticipated passing of legislation including the National Quantum Initiative and the National Defense Authorization Act. 2024 will see a rapid uptick in the quantum sandbox and test bed programs — with directives to use all types of quantum technology, including annealing, hybrid, and gate models. These programs will focus on near-term application development to solve real-world public sector problems, from public vehicle routing to electric grid resilience.

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Could you define the international alliance needed to expand quantum computing?

The global quantum race will continue to heat up, as the U.S. and its allies aggressively push for near-term application development. While the U.S. is now starting to accelerate near-term applications, other governments like Australia, Japan, the U.K., and the E.U. have been making expedited moves to bring quantum in to solve public sector challenges.  This effort will greatly expand in 2024.

Top public sector areas of focus will likely be sustainability, transportation and logistics, supply chain, and health care.

In 2024, what would be the impact of quantum computing technology and applications on the future of work? 

Quantum computing will show proven value and utility in daily business operations through in-production applications.

As we close 2023, companies are beginning to go into production with quantum-hybrid applications, so it’s no stretch of the imagination to see corporations using quantum solutions daily for ubiquitous business challenges such as employee scheduling, vehicle routing, and supply chain optimization. In time, it will become a part of every modern IT infrastructure, starting with the integration of annealing quantum computing.

Thank you, Dr. Alan! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi Michael, Please tell us about the latest trends in IT security budgeting.

Hi, Sudipto. In 2023, IT security leaders are facing tighter budgets and they will need to optimize and consolidate the tools they have already procured. When looking at new tools, they will have to be able to take out two or three existing products to fit within budgets in 2024. It means cybersecurity vendors will need to double down on technical innovations that drive productivity while keeping costs top-of-mind.

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Beyond product enhancements, we will also see continued partnerships and integrations between vendors to meet this need and reach more customers.

That’s great! Does it mean Security leaders would find it more economical to leverage AI tools for their mission-critical operations?

Yes. AI will have a huge impact in 2024.

A huge issue for organizations (especially education, healthcare, and other industries) is that trained cybersecurity talent is scarce and expensive. These organizations struggle to hire and retain best-in-class talent. ISC2’s 2023 Cybersecurity Workforce Study found that the cybersecurity workforce grew by 8.7% to 5.5 million but open cybersecurity positions increased 12% to over 4 million. With this in mind, organizations will seek to leverage AI to help compensate for the talent gap.

Generative AI has the opportunity to generate training content specific to various roles and deliver that content on an ongoing and interactive basis to ensure every employee is best equipped to be a protector of their organization.

AI makes it possible to apply adaptive learning techniques across organizations at scale.

Which areas would continue to pose challenges to security leaders in 2024?

Cybersecurity, for sure…

Gaining access to any enterprise via valid credentials remains the preferred method of access for cyber actors.

As Generative AI matures over the next year and beyond, social engineering attacks fueled by Generative AI will become easier to perpetrate, will increase in scale, and will be increasingly realistic. No amount of training will be able to prevent some of these tactics, so we will surely see an increase in cyberattacks. Therefore, over the next year, we’ll see how many organizations have built their defense strategy around a cyber resilience mindset, e.g. micro-segmentation, passwordless authentication, phish-resistant MFA, moving from privilege escalation to separate privileged user accounts, and when it all fails, having immutable data backups.

How do you see AI and regulations shaping the security marketplace in 2024? Are CISOs ready to meet these regulations?

The recent SEC action against SolarsWinds and more importantly against the CISO Tim Brown shows that CISOs are increasingly in perilous situations. There will never be enough resources devoted to cybersecurity in any enterprise yet CISOs have to make risk-based decisions every day. If that were not difficult enough, add to that the threat of criminal charges if you get it wrong and it only adds to an already incredibly stressful environment.

Will we see more and more CISOs leave the profession?

Will we see an increase in CISO turnover?

How will the relationship between the CISO the board and the executive leadership team change?

On a positive note, New York recently announced a new cybersecurity strategy that will mandate comprehensive cybersecurity programs, vulnerability assessments, access controls, and security awareness training for hospitals, offer $500 million in funding for healthcare IT, and expand the cyber resources of state-wide criminal investigative entities. This is a huge step forward and I can only hope other states and municipalities follow New York’s lead.

Thank you, Michael! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi Hendrik, welcome to AiThority.com’s Predictions Series. Please tell us about the evolution and ever-changing role of Artificial Intelligence (AI) capabilities in sales enablement.

I think Sales enablement companies are taking AI to the next level already. 

As buyers get smarter with more information at their fingertips, sellers will need to leverage AI to keep up. 2023 was undoubtedly the year in which AI entered the mainstream consciousness, but the nuances and the advantages that AI can offer in a business environment, are still being worked out.

To maximize the almost unlimited possibilities that AI can offer, sellers will need to harness it in their sales meetings to drive better buyer interactions, stay one step ahead and be ready to add meaningful value to the conversation.

Whether it’s using AI to instantaneously surface the most compelling pitch deck, talk track, or playbook, AI will enable sellers to show up as trusted advisors, earning buyer confidence and becoming indispensable to the customer journey. In addition to sales meetings, AI will also be leveraged to augment the role of the internal sales coach, making sales development programs smarter and more scalable. The latest innovations mean that AI can provide actionable insights on seller skills and behaviors, helping define a baseline for sales readiness, and deliver targeted support to the reps who need it most. And if you’re not integrating AI into your sales strategy, you will be opening yourself up to a brief creep from your competitors.

With AI, can we finally expect alignment between Sales and Marketing functions? 

Yes, we can finally see a better alignment between Sales and Marketing using AI.

For years businesses have tried and failed [epically] to align sales and marketing teams. In a recent survey, approximately 70% of organizations said their sales-marketing alignment was not very good, leading to frustration and finger-pointing. However, new enablement platforms coupled with AI will finally make this a reality. When sales and marketing teams can better align, they can sustain and nurture relationships with buyers.

Alignment will also ensure maximized revenue and growth opportunities for the business.

Bringing sales and marketing teams together will allow them to collaborate on key business goals and see how each department impacts the other.

Customers will be delighted when their needs are anticipated, understood, and managed in real time.

With alignment, there will be more rapid deal cycles as customers are engaged and ready to buy.

What avatar would the Customer Relationship Management (CRM) solutions take in 2024?

According to me, CRMs would evolve into Sales Enablement Platforms (SEPs).

Customer Relationship Management (CRM) and Sales Enablement Platforms (SEP) are both crucial tools in the modern sales and marketing landscape, but they serve distinct functions. While CRM systems were about managing customer relationships and data, the reality is they have become more about customer record management. Meanwhile, sales enablement platforms are about empowering sales teams to engage more effectively with those customers.

In today’s world, businesses need a system of engagement to complement their system of record, and this has made Sales Enablement technology a must-have. Put simply, it is where the relationships happen. CRM systems are designed to manage interactions with current and potential customers, tracking the history of customer engagements, sales opportunities, and service requests. They are invaluable for maintaining detailed records of customers and long-term relationship building.

On the other hand, SEPs focus on equipping revenue enablement teams with the tools, content, and information needed to sell more effectively. These platforms provide resources like sales training materials, content management, and analytics tools to optimize the sales process.

It’s only a matter of time until SEPs outweigh CRMs in importance and additive value.

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Thank you, Hendrik! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi, Dan. Welcome to the Interview Series. Please tell us about your role at HTC VIVE.

I am the General Manager of the HTC VIVE Business for the U.S. region which is inclusive of Product Management, Sales, Marketing, and Operations. I have oversight and responsibility to deliver our full portfolio of HTC VIVE Products, Services, and Solutions for all our Consumer and Enterprise customers.

What has changed in the AR VR technology development landscape in the last three years?

I think it’s safe to say that for all tech, advancement and miniaturization go hand in hand. The XR industry is starting to hit its stride in this regard, with smaller and more powerful devices coming to market. HTC VIVE released the first glasses-style VR headset, VIVE Flow, in 2021. We followed it this year with VIVE XR Elite, which is also foldable and compact, but much more powerful.

Mixed reality (MR) is also in the spotlight these days. That’s largely thanks to improvements in passthrough technology, and the addition of depth sensors to headsets. VIVE XR Elite was our first headset with a sharp, color passthrough that makes MR not only practical but also fun. We’re starting to see some groundbreaking applications developed by our partners Taqtile, HAVIK, and more. But we’ve only scratched the surface of MR; there will be advancements in cameras and computer vision techniques in the coming years to bring these experiences even closer to natural human eyesight.

There are also big changes happening on the wireless infrastructure side. You need powerful, high-throughput connections to run immersive content in a secure environment – much more than what’s needed to stream movies. 5G and eventually 6G antennas will be integrated right into VR headsets. In the interim and to meet market needs, we’ve developed a Private 5G solution called REIGN CORE that can blanket a 10,000 m2 warehouse in a secure 5G signal. Recently, we attended the Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) demonstrating secure XR training solutions for defense, military, and law enforcement.

Connectivity was part of every conversation as government organizations looked to implement training solutions and scale in a secure environment. This Private 5G solution then enables organizations to run VR training with almost no latency.

Could you tell us about the XR product roadmap at HTC Vive? Which industries are you currently focusing on?

We count a lot of great partners in the defense vertical, as well as in healthcare and training. The technology trends I mentioned before – miniaturization and better passthrough – lend themselves well to all different types of training scenarios.

At I/ITSEC, we had up to 30 partners showcase their immersive training simulations that replicate real-world scenarios, giving trainees a safely controlled space to learn and advance their skill sets for mission-critical procedures on VIVE devices. 

In terms of products, we launched our newest device, the VIVE Ultimate Tracker recently. It’s a “self-tracking” tracker which means it knows its own position in 3D space and can thus be used to track your body parts in VR precisely. You can also attach it to physical objects and bring them into VR experiences. This is extremely useful for a lot of different vertical partners: healthcare, industrial training, defense, design, and more.

According to HTC VIVE’s latest report, 80% of active military-duty trainers said that XR enhances their education plans and empowers trainers to be more effective. Can you please explain what this means for realism-based training programs in critical operations?

XR training is kinesthetic in nature. It’s the most effective learning method for lots of people, as opposed to reading or listening to lectures. According to the National Training Laboratory, the retention rate for VR learning is 75% compared to 10% for textbooks and only 5% for lectures. In other words: humans learn by doing. XR makes it possible to go through potentially dangerous scenarios in the headset, without any actual safety risk, and get better prepared for real-world missions.

How is HTC VIVE eliminating work silos in remote settings? 

We have an enterprise platform called VIVERSE for Business, which lets employees with all different kinds of roles collaborate remotely. We built it with enough features to make it as powerful as you need – for example, for group visualization of 3D objects – but also with many core productivity features like scheduled meetings, support for 2D video calls on Zoom and Teams, and Microsoft Office file support.

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The whole idea is for VIVERSE to be an extension of the conventional office, particularly for globally distributed and remote teams.

Sales and Marketing organizations are steady users of XR technology for their lead-gen campaigns. How do your customers use VR to improve their lead gen operations?

It’s a great question as we use the workflow tools from VIVERSE for Business applications for our meetings as well as reviewing the content and preparing presentations for our customers and training on new products. We are also integrated with Salesforce in our VIVERSE for Business application and we can review customer information and engagement plans and strategy in our XR Headsets. In addition, we have integrated over five MDM partners as well as our own native solution for commercial customers looking to bring better management and security. Overall, we’re seeing great results with training, collaboration, and integration of useful applications like Salesforce. There’s a lot more to come on applications we are integrating and how we’ll continue improving workflows and efficiencies.

Your predictions on the future of AI in the XR industry that requires highly optimized and CX-driven workflow automation: 

AI will make our interactions with XR technology easier and more natural. Working with virtual input methods like keyboards is tricky, with a learning curve. AI can help us more naturally interact in VR through speech and gestures, in a human-centric way. Soon, we’ll probably be able to speak things into existence – like virtual objects and worlds. This means that the advent of AI will make it much faster and easier for businesses to develop intuitive, customer-first workflows.

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Thank you, Daniel! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi, Rita. Welcome to the Interview Series. Please tell us about your role at Cloudflare. How did you arrive at Cloudflare?

I joined Cloudflare seven years ago as a solutions engineer, helping our customers achieve success with our technical deployments for our performance and security services at the time. Before Cloudflare, I was working as a software engineer, so when Cloudflare Workers was released it seemed like it could present a massive opportunity to change the way applications were built, so I joined the product side to work on it, and have been helping grow our developer offering since (which now includes our AI products).

What has changed in the AI data engineering landscape since the launch of ChatGPT? How are generative tools transforming DevOps and programming techniques?

On the DevOps and programming side, we’ve started seeing generative AI transform the way developers were building before ChatGPT, with the release of Github’s Co-Pilot.

We’re already seeing massive productivity gains from developers using code-generation tools to accelerate development, especially when it comes to generating boilerplate code, tests, and tasks that have been solved many times but are time-consuming. The other big shift we’re already starting to see and I believe we’ll see even more of is generative AI opens up the door for more collaboration amongst developers, and designers, and a lower barrier to entry for beginners.

Could you highlight Cloudflare’s approach to innovating with generative AI tools? Please tell us more about Mistral 7B.

The challenges developers face with deploying AI today are very similar to the challenges we’ve been solving with our developer platform for the past 6 years — a lot of developer productivity is wasted on setup, provisioning, optimization of resources, scaling and performance. So we wanted to bring the same serverless approach we brought to generalized compute to GPUs and AI deployments and allow developers to start building applications with AI without having to think about infrastructure.

We launched Workers AI in September with support for several models in our model catalog out of the box to get started with an open-source LLM being as easy as writing a few lines of code. We’ve been expanding our model catalog since launch and recently announced support for Mistral 7B which is an exciting new open-source LLM that outperforms previous LLMs in many ways, despite being a much smaller model.

How do you think AI is going to reach critical mass for businesses?

There’s been a lot of excitement recently about really large language models, however, anyone running or deploying them in production will be faced with reality pretty quickly: it’s really expensive to run them, and hard to even find and provision infrastructure for them. The next wave of innovation we’re going to see will likely go the other way, in getting smaller models (single-digit-billion parameter models, as opposed to hundreds-billion parameter models) to perform better.

With fine-tuning, these models are more likely to provide value to businesses fast, and power better experiences without breaking the bank.

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On a related note, there’s been so much great innovation going on with open-source models, and the tooling ecosystems that have sprung up around them. It will be interesting to see how open-source model adoption plays out compared to proprietary, but I would say open-source is always a good bet.

With models taking multiple seconds to execute, does performance really matter in AI?

AI is still a fairly nascent technology — so our expectations are in line with that. But if AI is to become an integral part of our daily lives, performance is going to improve significantly and become a standard.

The web started out very similarly, with users being accustomed to waiting multiple seconds if not minutes for a web page to load. Today, however, engineers are optimizing for every large millisecond of wait time because as it turns out, there’s a direct correlation between performance and conversion rates.

Especially once AI starts powering more real-time experiences that are meant to emulate humans (think ordering a coffee at a drive-through), we’re going to expect experiences that have processing and reaction times that mimic those of human interaction.

Your predictions for the AI engineering industry in 2024: 

I have two big predictions for AI development in 2024. 

The first is that surging AI bills will land on developers. As AI experimentation skyrockets, so do AI bills.

Developer teams will be required to answer for this AI spend as CFOs will not accept unbounded and unpredictable costs for much longer and there will be added pressure to prove the return on investment. Tools offering insights, guardrails, and monitoring, especially in experimentation, are going to be critical for every dev team’s AI arsenal. 

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The second is that smaller models are going to become the default.

While it’s been exciting to see what we can achieve through the hardware that’s allowed the training of extremely large hundred billion parameter models, the reality is that in production there are diminishing returns to running such large models, while the costs of running them are disproportionately higher. What we’re going to see is more fine-tuning of smaller models, and innovation around customizing them and making them smarter.

Lighter notes:

Burn the midnight candle or soak in the sun?

Neither! I’m a morning person, but I love a cozy day indoors.

Coffee, or Tea?

Coffee

Your favorite Cloudflare offering that you want everyone to know about?

I’m biased, but Cloudflare Workers! It takes just a few seconds to try and you can get an application up and running so quickly and it will continue to scale regardless of how much traffic you get.

First memorable experience in your career as a technology leader?

Shipping workers.dev and launching it at JSConf EU. It was surreal seeing apps pop up the next day built on top of the tools we had just launched.

One thing you remember about your employee (s):

There are so many different ways to be a successful PM. Some PMs are more analytical and live by dashboards, others are great speakers and presenters, some love getting down into the API design. You want a mix of these different skills on your team to both foster different perspectives and learning from each other. I feel so lucky about the team I get to work with, and learn from them myself every day.

Most useful app that you currently use:

Google Calendar – it dictates my entire day.

Thank you,  Rita! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi Ryan, welcome to our Interview Series. Please tell us a little bit about your role and responsibilities at Salesforce.

I’m the SVP of Product Management of Service Cloud at Salesforce, where I oversee the platform and help thousands of companies utilize our trusted AI for customer service to create seamless conversational, predictive, and generative AI experiences for agents and customers.

Could you tell us more about the ideal customer profile of Salesforce Service Cloud? Which industries rely on your solutions and services?

Delivering efficient customer support is crucial to driving satisfaction, loyalty, and positive customer experiences for companies of all sizes, in every industry, around the world. Any company looking to streamline and enhance its customer service operations is a good fit for Salesforce Service Cloud. Service Cloud helps organizations of all sizes, like Heathrow Airport and AAA, deliver personalized customer service with AI-powered insights, recommendations, and productivity tools.

Salesforce Service Cloud also offers industry-specific applications for business across more than 13 industries, from IT to retail, consumer goods, and beyond. Leading solar services provider Sunnova is using Service Cloud to easily track the performance of its hardware, automatically create work orders, and resolve cases faster using predictive AI from Einstein for Service.

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Tell us more about your newly launched Sales and Service AI capabilities. Can you tell us about Einstein GPT’s role in these announcements?

Salesforce recently debuted new AI capabilities for both Sales Cloud and Service Cloud. The Sales Cloud innovations are designed to boost productivity and help sales teams close more deals, faster. Service Cloud boasts a broad set of AI capabilities, including Einstein Copilot for Service, which automates personalized responses based on real customer interactions to help resolve issues faster. The newly launched AI innovations for Service Cloud bring AI-powered insights directly into the flow of work for service professionals. These capabilities transform how service teams deliver value across customer touchpoints — from process and automation to operations — to boost agent productivity, cut costs, and enhance customer satisfaction.

Our latest launch is Service Intelligence for Service Cloud with Einstein Conversation Mining. This innovation uses AI to analyze customer chats and emails to uncover insights. For example, the new solution can analyze a customer’s specific challenges and then asses the likelihood of complaint escalation to proactively address the customer’s issue. It could also identify a trend in customer cases, like if there’s an increase in customers asking about a return policy. With that information, service agents then train a bot to spot similar customer cases and automatically surface a self-help article on returns to help them resolve the issue faster.

How does Service Cloud align with Marketing and Sales Cloud? What are the benefits of using Salesforce for omnichannel customer experience management?

Omnichannel is designed to combine all channels into one seamless experience, whether before the purchase, during the purchase, or after the purchase. Omnichannel helps break down the siloes that can complicate customer interactions. With an omnichannel mix, information is shared between sales, service, and marketing team members to ensure that support staff have information readily available to assist the customer.

Renowned Italian fashion designer, Boggi Milano, adopted the omnichannel mix to improve their customer experience from discovery to service. With this approach, Service Cloud enables Boggi Milano customers to begin shopping online, chat through purchasing decisions with a service rep, and transition seamlessly to a personalized in-store retail experience.

What kind of infrastructure does a financial services organization need to match the demands of modern contact center transformation?

Could you share some use cases from the financial services industry specifically mentioning your differentiated Sales and Service AI products and services?

The customer service demands of modern financial service organizations are unique. Salesforce technology is designed to help these organizations tackle constantly evolving demands by providing the tools to tailor individualized client experiences.

The AI revolution is here, but at the foundation of the contact center transformation is really a data revolution. Industries like financial services need the infrastructure in place to ensure that their customer data can be the basis of next-generation AI experiences. Building a proactive, personalized service experience based on real customer data and interactions can help these organizations solve customer challenges more efficiently.

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For example, Santander UK relies on Service Cloud for automation in the customer support process, which has transformed how it manages relationships. Powered by Service Cloud’s Live Agent feature, Santander helps subscribers of its digital platform Navigator directly connect with support team members via live chat. Every new business contact and each subscriber case is automatically created in Service Cloud, helping Santander streamline other important tasks with intelligent workflows. These AI integrations enable Santander to personalize experiences for each client’s unique journey and build true partnerships with their growing businesses.

Beyond financial services, organizations across industries count on Service Cloud to help support their customer needs. Organizations spanning industries like retail, healthcare, manufacturing, and more use Service Cloud to incorporate automation into the service process and nurture customer relationships throughout every stage of the lifecycle.

Lighter notes:

Coffee, or Tea?

A Chemex Pourover is absolutely part of my morning ritual at home, but a cuppa is always welcome when traveling.

Most useful app that you currently use:

I wouldn’t even know how to answer these questions without Slack’s new Canvas feature for team collaboration.

Your favorite Salesforce product marketing initiative that you want everyone to know about:

It’s difficult to pinpoint just one initiative, but adding new AI-powered capabilities to Salesforce Service Cloud is one of my favorites. Salesforce has long been a pioneer in the AI space and the future holds even more exciting AI-driven developments for Service Cloud.

Your first memorable experience in your Salesforce career

My first time on the main Dreamforce stage was as a partner, where I was meant to silently give a demo on behalf of one of our customer Trailblazers. Marc kept asking me all these great questions… not realizing that I didn’t have a microphone to give him answers!

Thank you, Ryan! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi, Dr. Karin. Welcome to the Interview Series. Please tell us about your role at LinkedIn. How did you arrive at LinkedIn?

I’m LinkedIn’s Chief Economist, leading a team of economists and data scientists who track, analyze, and report on key workforce and labor market trends unfolding on LinkedIn. Before joining LinkedIn in 2020, I held a variety of positions, including Assistant Treasurer for Google, Managing Director, and Head of Macroeconomic Policy at Bank of America Merrill Lynch, and I worked at the Federal Reserve Bank of New York for about a decade. What excited me about joining LinkedIn was the mandate to explore the wealth of data on the global labor market and to apply our insights toward LinkedIn’s mission of creating economic opportunity for every member of the global workforce.

How do you differentiate AI skills from non-AI skills? Which skills would likely improve the quality of life of employees and workers in 2024?

LinkedIn members self-report their skills on their LinkedIn profiles. Currently, more than 41,000 distinct, standardized skills are identified by LinkedIn. These have been coded and classified by our skills taxonomists into 249 skill groupings, which are the skill groups represented in the dataset. AI is one of these groupings in which we track 121 distinct AI skills. The top, most popular, skills within the AI skill grouping are machine learning, natural language processing, data structures, computer vision, and image processing among others.

There is a broad range though, and AI skills can include everything from the skills needed to build and finetune AI models and tools to the skill of knowing how to apply AI tools for various business purposes.

What we’re seeing at LinkedIn is that while AI skills are on the rise in terms of demand, people skills are gaining importance right alongside them. So when we look at the U.S. specifically, the most in-demand AI skills are machine learning, data structures, and natural language processing, while some of the most in-demand people skills across many large economies are communication, analytical skills, and leadership. And employers are increasingly looking for talent who combine these two types of skills –AI and people skills– together.

To prepare for the changes AI and Generative AI (GAI) are bringing to the world of work, businesses will need to thoroughly understand the skills they have and the skills they need. Professionals will need to focus on acquiring and developing AI literacy skills to better position themselves as they go forward in 2024.

AI adoption has grown at lightning speed. How are AI conversations on LinkedIn and other networking platforms shaping the business landscape?

Conversations around AI on LinkedIn have increased by 70% globally since GAI sparked in popularity — a very significant jump when compared to other recent tech advancements like cryptocurrency (which saw a 19% increase at its peak in November 2021) and augmented and virtual reality (which experienced a 5% increase at its peak in October 2021).

We are seeing these conversations being driven in large part by millennials, professionals in executive or engineering roles, and people based in industries like professional services, technology, and education.

Interestingly, conversations around AI aren’t just happening within one industry or organization — these conversations are top of mind across genders, generations, occupations, and industries. I believe these conversations are helping to bring what used to be a somewhat niche topic into the mainstream, and it’s driving excitement to explore and adopt AI tools. It’s also demonstrating just how widely applicable AI can be — professionals across almost every industry and position can find ways that AI can help them become more productive at work.

Could you highlight key takeaways from your Future of Work Report? Should business owners embrace AI more freely in 2024 to become more competitive?

In general, business owners, business leaders, and professionals at all levels should be developing their understanding of AI and embracing their AI literacy. These are the skills of the future, but they’re also quickly becoming the skills of the present. As of September 2023, 74% of U.S. executives see at least one way GAI will benefit their businesses and employees — including increasing productivity and unlocking more growth and revenue opportunities. But the plans themselves are still very much being formed.

We’re at an exciting place right now where business executives are enthusiastic about AI and plan to increase their use of AI in their organizations within the next year, but more than half of executives do not yet know exactly how their organization is going to use it. It’s very much at a point where businesses are still figuring it out — and like most new technologies, the early adopters will likely have a leg up on the competition. This is why my team at LinkedIn is focusing on this topic — to help business leaders abstract from all the noise and acquire a structured and data-driven way of thinking about the impact of AI on their organizations.

The fear of job losses is getting real. And, so are the dangers of abusing the powers of AI, especially when we talk about deep fakes, ransomware attacks, and copyright infringements. Could you tell us how AI leadership can bring more transparency to the whole job marketplace to meet the above-mentioned challenges?

As an economist, I’m probably not the best person to weigh in on trust and security-related topics, but as we consider business leaders’ responsibilities as this AI transformation begins, there are a couple of things I’d like to mention.

We are just starting to scratch the surface and many companies are just starting to invest in AI training. Employers must be thoughtful about what AI means for their employees, ethical about how they bring in AI, and invest in the needed training for their employees. It is also critical to ensure cross-sector outreach to diverse communities and to invest in skills that can help lead to expanded access to opportunity. Employers will need to be conscious of training both more senior and junior employees in AI.

It’s also important that mitigation and strict guidelines are in place to ensure that AI is not disproportionately impacting one group of people over another. As one example, in terms of representation right now in AI, we are seeing that the artificial intelligence sector is overwhelmingly represented by men (70%) compared to women (~30%) — this makes men more than twice as likely as women to be in the AI industry. So these are some of the things business leaders need to consider and be thoughtful about moving forward as AI becomes more mainstream.

Age is just a number in the digital space. What does your Future of Work report state about the excitement around AI among different age groups?

When it comes to conversations around AI and overall excitement for AI, we see that younger generations are particularly excited about AI and how it could help them in their careers.

We know that Millennials and Gen Z are driving the bulk of conversations around AI on LinkedIn (45% and 26%, respectively). At the same time, Millennial and Gen Z survey respondents globally expressed noticeably higher excitement than their Gen X and Baby Boomer counterparts when it comes to AI’s ability to provide access to knowledge and information faster, improve the quality of their work (copywriting, creating presentations, etc.), and help them summarize a lot of information quickly.

In addition, Millennials and Gen Z professionals globally are the most likely to say they’ve begun experimenting with AI tools like ChatGPT and Microsoft Copilot at work, as well as most likely to say they’ve taken an online course to better understand AI. In the U.S., Gen Z are 1.6 times more likely to want to learn AI skills than Boomers and 1.1 times more likely than Gen X.

Your predictions on AI’s role in democratizing workplace equality globally?

Unlike the rise of machinery and automation, or any number of technological advancements that have largely displaced select subsets of workers, the AI revolution is poised to transform over 50% of jobs across all professional levels, education levels, and industries. So, the impact of AI will be felt more evenly across the workforce than we’ve seen in the past, which is worth noting.

We at LinkedIn believe that the rapid rise of AI will produce opportunities for professionals of all levels of education and years of experience to not only find but excel in their roles. Over the past decade, and particularly during the pandemic when employers were deeply struggling to fill open roles, we’ve observed a steady move away from relying on degrees or years of experience in a hiring situation and towards skills-first hiring among business leaders.

The rise of AI is accelerating this shift. Employers are increasingly looking for professionals who can demonstrate specific skills — both hard skills and people skills. With AI being so new and rapidly evolving, professionals who embrace it early on and begin to gain AI literacy will have the upper hand when looking for a job, even if they don’t have the strongest “traditional” professional background (like a four-year-degree or a decade of experience).

We also believe the rise of AI within the workplace will in some ways reduce the need for specialized knowledge on a certain topic or industry overall, thereby making job mobility more possible. For instance, having the AI skills and literacy to draft a white paper, create a promotional video, or translate a company-wide memo into different languages may become just as valuable to an employer as having a background in film production or fluency in several languages. It therefore becomes a matter of knowing how to use AI to create those things, rather than necessarily needing to know them themselves. If you can acquire those AI skills and learn how to generate the end-result you need, in many ways those skills become industry- and role-agnostic and can be applied very widely.

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Additionally — and this is one of the things LinkedIn members are most excited about when it comes to AI — tapping into AI tools can remove much of the day-to-day busy work that many professionals do regularly. By automating many tedious and time-consuming tasks like note-taking in a meeting, researching, summarizing documents, and scheduling, AI can enable us to unblock our schedules and to-do lists and give us more time to hone our creativity, passions, and people skills. The hope is that AI will ultimately bring us greater satisfaction in our jobs and enable us to make a greater impact in our careers.

Thank you, Dr. Karin! That was fun and we hope to see you back on AiThority.com soon.