Prioritizing curiosity, customer success, and continuous learning to human-centered design and advanced AI drives transformations.
Curiosity gets one to ask several questions and further solve big problems. And these are the fundamental values on which Vianai Systems is built. Believing in customers’ success, the team is never off-focus and is in continuous pursuit of learning. It brings together human-centered design and advanced AI techniques, to help its customers drive breakthrough transformations. To learn how the organization is accelerating AI adoption we interviewed its Chief Design & Strategy Officer– Dr. Sanjay Rajagopalan.
Below are the interview highlights:
1. Kindly brief us about yourself and your journey as the Chief Design & Strategy Officer at Vianai Systems.
I have extensive experience and background in human-centered design as it relates to the enterprise – in products, processes, organizations, and services. As Chief Design & Strategy Officer at Vianai Systems, I head up our corporate design team and drive both customer and special projects. Before Vianai, I was the SVP and Head of Design & Research at Infosys, where I worked on strategic design and innovation initiatives internally and with dozens of customers, and I helped with training over 150K Infosys employees on concepts of design thinking, human-centered design, and innovation. Previously as the SVP of Design and Special Projects at SAP, I led 30+ corporate innovation initiatives. I hold a Ph.D. in manufacturing and design from Stanford University.
2. Tell us your source of inspiration for venturing into the field of human-centered design.
My technical field, prior to arriving at the Stanford ME Design program, was in the area of Computer Aided Design. My job and training involved the use of advanced CAD tools to model, simulate, analyze, and design automotive components like transmissions for heavy earth-moving equipment. At Stanford, I was exposed to a whole new way of thinking about design in the context of human-machine interactions. I was there in the early days when concepts on design methodology, HCI, design thinking and new paradigms for manufacturing and collaboration were forming. I was heavily influenced by the ongoing work at the Product Design program and the Center for Design Research at Stanford, which was the crucible in which the Stanford d.school was forged. I brought those ideas into the companies that I worked at subsequently which, being situated in the Bay Area, ended up being software and technology companies, specifically enterprise software companies. I was an early member of the newly formed Design Services Team at SAP – and worked there with Dr. Vishal Sikka and Dr. Hasso Plattner, who were instrumental in the formation of the Stanford d.school (also called The Hasso Plattner Institute of Design at Stanford). Many of the top design leaders in the industry, including at places like Facebook/Meta, Google, Twitter, ServiceNow, JP Morgan, Infosys, Cisco, and many other leading companies around the world worked together during those days at the DST at SAP.
3. Brief us about Vianai Systems and give us an overview of how it is humanizing AI for enterprises.
Vianai Systems is a Palo Alto, California-based Human-Centered AI platform and products company launched in 2019 to address the unfulfilled promises of enterprise AI.
Human-centered AI refers to scenarios where humans work closely with AI systems, augmenting and amplifying their capabilities. It serves as the main focus in the design of our products at Vianai. We work to bring the power of human understanding – like judgment and collaboration – together with the best data and AI techniques, to create intelligent systems that can greatly improve business outcomes and processes. We make monitoring and continuous operations tools, which help enterprises running a large number of models with high inference throughput track the performance of their models, and also diagnose and fix problems quickly. Our teams at Vianai have developed, and are continuing to develop, advanced tools and techniques to help enterprises implement safeguards that promote the responsible use of AI/ML – including in the incorporation of the very exciting advances in large language models, such as ChatGPT and Bard, into the mainstream of their businesses, but in a reliable, responsible and trustworthy manner.
4. What are the core values on which the organization is built and what is the mission of the organization?
Vianai’s mission is to bring human-centered AI to life in enterprises worldwide, and help companies realize the full potential of their AI investments. While AI has made some notable recent advancements, the significant potential of bringing the power of human understanding, judgment, and collaboration together with data and the best AI techniques remains untapped. We believe in a future where the most valuable use of AI technology will be as a partner or co-pilot that enhances, improves, augments, and amplifies the capability of humans. Vianai was founded to bring this unfulfilled potential to the enterprise at scale. We refer to this as a “world full of life and intelligence,” meaning that all life on the planet will benefit from human and artificial intelligence working in partnership.
5.Being a thought leader, how do you strategize to bring to light Vianai Systems’ mission and vision?
At any startup, and especially in an area where the technology landscape is evolving very rapidly, driving company and product strategy is a real-time, dynamic, active and relentless challenge. The key to doing it effectively is something that our CEO Dr. Vishal Sikka has called “zero distance.” Zero distance refers to the key decision makers at the company being hands-on with three critical aspects of the company – the end-user/customer (desirability), the product/technology (feasibility), and the sales/business (viability).
All of the senior leaders at the company espouse the zero distance philosophy, work tirelessly and collaborate continuously in order to drive company and product strategy in a way that leverages the opportunity presented by human-centered AI for the enterprise. Our goal is to activate the collective skills and experiences within ourselves and all of our exceptionally talented colleagues to build a transformational company with remarkable products that will ultimately win in the marketplace.
6. What do you think is the most exciting part about working in Human-Centered AI?
We are fortunate to be doing pioneering work in an area that has, in recent times, captured the attention and minds of a very large number of people – especially those in technology, business, government and academia. It isn’t often that the topic of AI, in some shape or form, is not on the front pages of major news publications, and the topmost trending topics on social media and other platforms. The buzz and the hype is everywhere – which is both a benefit and a challenge.
The benefit is that we all come to work every day motivated and excited about what we are working on. We are certainly in the epicenter of a topical, relevant, disruptive and game-changing moment in our history, as it relates to the impact of AI and related technologies on everything around us. We could have the tools at hand to help us solve some of the most vexing problems at a global scale – those related to climate change, energy, war, poverty, injustice, and alleviation of human suffering. We also believe that we are differentiated from our competitors in the understanding and embrace of human-centered AI, as we believe this will be the dominant type of AI in the future. The challenge is that all the hype and attention also results in excessive noise and an overload of misinformation, misunderstanding, and wasted energy. We need to find ways to not get distracted by this noise, and focus on moving forward on our mission without compromising on our core values.
Working in this dynamic environment and balancing these challenges and opportunities is the essential thrill and excitement of our work.
7.Why do you think it is important to craft a smarter and humanized AI ecosystem?
Large AI models, especially those which deal with language and imagery, are exceptionally good at mimicking humans. However, unlike humans, these systems have no real-world understanding, and no model of the physical world they can reference to cross-check and validate their outputs. This makes them (at least the current versions of this technology) quite worthless for tasks that need accuracy, reliability, repeatability or precision. Nevertheless, humans tend to anthropomorphize anything that does a reasonably good job of mimicking us – even in a limited manner. This can be a very dangerous thing, as it may lull us into a false belief that large AI systems are actually “intelligent” in the real sense of the word. Some people even go as far as attributing sentience to a purely mechanical (but high-quality) mimicking of a limited set of human behavior while, in fact, machines are nowhere close to having a human-level understanding of the real world. Most likely, this gap will not be closed anytime soon.
To avoid disappointment, and perhaps disaster, while using such systems, people need to be made fully aware of their strengths and limitations. They need to understand deeply how these systems actually work – at what types of tasks they excel, and at what types of tasks their capability is limited and their performance superficial and illusory. In a smarter and more human-centric AI ecosystem, the goal would not be to impress via mimicry – but to add value and improve outcomes that matter to people. The costs of not doing this through proper design of interfaces, life-cycle management, and governance systems for AI models could be quite substantial.
8. In your opinion, how does trust as a factor playing a crucial role in utilizing AI systems and how is human-centered design bridging this gap?
The guarantee of performance required to entrust a machine with a task is clearly very contextual. For example, if a mistake can make the difference between life and death (like in an autonomously driven vehicle), the level of trust needed between the machine driver and the human passenger would need to be extremely high. On the other hand, if the machine is composing a poem or writing the outline of a news article, then some poor performance can easily be tolerated, and the trust requirement is relaxed a bit. In general, tasks performed in typical enterprises by professionals using AI/ML apps and tools (e.g. decision support for financial, procurement, supply chain, or operational tasks) require a higher level of accuracy and trust than consumer use-cases.
A key thing about trust is that it, like a good reputation, is hard to win and is easily lost. Machines also start from a position of deficit in trust from humans – largely because humans hold machines to a higher standard than they do other humans. For example, humans may tolerate a minor accident from a human driver while they are in a vehicle with them, and get right back into the car to complete the ride. However, they may insist that the car be returned to the service center, fully fixed and reprogrammed before they would reluctantly get back in a car that was crashed by a machine.
Human-centered AI platforms which monitor, govern, diagnose, and retrain errant or deteriorating AI systems ensure that problems (like performance drift) are diagnosed early and fixed before the hard-earned trust in the machine is lost. At Vianai, we have built a platform for monitoring and continuous operations of AI/ML workloads at scale. This system allows for monitoring of various types of drift (input drift, feature drift, output drift, outcome drift, etc.), root-cause analysis to determine the underlying reasons for any detected drift, automated model retraining, and validation prior to the re-deployment of the improved model.
9. Having an extensive experience in the field, please brief us about the emerging trends of the new generation and how you plan to fulfill the dynamic needs of the ever-evolving space.
The next generation of engines that will power applications like ChatGPT and Midjourney etc. is widely anticipated to be orders of magnitude larger and more complex than the current models. The new models will be trained (at great expense) with a vastly larger dataset and will run on a much larger compute footprint. The achievements of these more advanced systems will continue to be impressive, but some fundamental issues are unlikely to be addressed without an overhaul of how such systems are built. Meanwhile, the permeation of these technologies into the everyday lives of ordinary people, and their adoption into enterprise activities and business processes, will also continue to grow – and the human-centricity in the design of the tools will become increasingly important. There is also likely to be some progress in foundational advancement in the science of AI which can address some of the structural flaws of such systems – both within academia and in corporate research labs.
We plan to fulfill the dynamic needs of this evolving space in two ways – first, by architecting our platform and tools to be capable of operating at immense speed and scale, well beyond the median requirement for the enterprise today. Second, we will bring to market capabilities for the massive improvement in the cost and performance both of building and running such systems. As these technologies continue to grow in scale and scope, we hope to remain relevant by investing up-front in those capabilities which will best serve to future-proof our offerings and remain relevant in the long run.
10. How do you envision scaling both–Vianai Systems and your growth curve in the year 2023?
We expect 2023 to be a critical year for the company – both in terms of bringing to market some of the most exciting application and platform features available in the enterprise AI space, and in growing our base of productive and referenceable customers. We believe we are in a great position to take advantage of some of the momenta that have been generated in the space by high-profile players like Microsoft, OpenAI, Google, etc, but also be differentiated in our offering in a way that makes sense and resonates with our enterprise customers. We expect to get more adoption of the applications we have already released into the market (Dealtale.com, hila.ai, etc), introduce new high-value applications which are still under development, and also see significant uptake of our platform for monitoring, continuous operations, and performance optimization.
At a personal level, I fully expect to learn something new every single day and be impressed by what our team of exceptionally talented colleagues will achieve during the year. These are truly unique and disruptive times (in a good way) – and it is a privilege to have the opportunity to have both a front seat view, and even occasionally be in the driver’s seat of the big and meaningful advancements happening in this field.
Dr. Sanjay Rajagopalan
Chief Design & Strategy Officer at Vianai Systems
Dr. Rajagopalan has extensive experience and background in Human-centered Design as it relates to the Enterprise – in products, processes, organizations, and services. He is currently Chief Design & Strategy Officer at Vianai Systems, a Palo Alto, Calif., based company with a mission to bring human-centered AI to life in enterprises worldwide, and help companies realize the full potential of their AI investments. Previously, Sanjay was the SVP and Head of Design & Research at Infosys and the SVP of Design and Special Projects at SAP. He holds a Ph.D. in manufacturing and design from Stanford University.
