Daniel Lenton, Founder & CEO, Unify

Daniel Lenton is the founder and CEO at Unify, on a mission to accelerate AI development and deployment by unifying the fragmented AI stack. Prior to founding Unify, Daniel was a PhD student in the Dyson Robotics Lab, where he conducted research at the intersection of Machine Learning, Computer Vision and Robotics. During this time, he also worked at Amazon on their drone delivery program. Prior to this, he completed his master’s in mechanical engineering at Imperial College, with Dean’s list recognition.

Recently, in an exclusive interview with Digital First Magazine, Daniel shared his professional journey, the mission and vision of Unify, how should aspiring entrepreneurs leverage AI in their business initiatives, his favorite life lesson quote, personal modern-day hero, future plans, and much more. The following excerpts are taken from the interview.

Daniel, can you tell us about your professional background and areas of interest?

I started my career in mechanical engineering but quickly realized that working on planes and engines wasn’t as appealing as I had initially imagined, and that I was much more interested in tinkering with the deeper layers of the software infrastructure. The research I conducted during my PhD further cemented this inclination as I struggled with the fragmentation in the machine learning stack which I wanted to do something about given the lack of straightforward solutions back then. To date, I am still enjoying deep diving into this increasingly complex engineering rabbit hole, with Unify being the natural manifestation of this interest.

Tell us about the mission and vision of Unify. What sets it apart from other market competitors?

I mentioned how Unify is the extension of my desire to unify the ML stack and this is really the fundamental mission behind it. Before the company Unify, I started working on our open-source framework, Ivy. When I started Ivy, there was a deep fragmentation at the frameworks level and while there seems to be somewhat of a convergence on that front nowadays, the reality is that the massive growth in machine learning has given rise to deeper divisions across all the layers involved in a typical model life cycle. From compilers and hardware to orchestration tools and model optimization, the industry has witnessed a surge of competitive solutions with conflicting dependencies and partially overlapping boundaries, forcing the end-user to navigate through a complex map of ambiguously connected tools.

More than ever, we want Unify to be the trustworthy, impartial reference for practitioners to rely on when building or deploying their models efficiently. Naturally, this translates into a unique position with opinionated competitors that are either backing up certain technologies or trying to become a one-stop-solution themselves. We remain firm on our commitment to independence and hope to empower people to choose the tools that work best for their use-cases and their constraints.

What has surprised you about entrepreneurship so far?

Being a first-time founder with a purely technical background, it would be fair to say that the range and diversity of topics that should be kept on top of felt somewhat overwhelming in my early days as an entrepreneur. I had to learn everything about management, funding, marketing, etc. on the job and quickly realized that entrepreneurship was much more than coming up with a bright idea.  Fortunately, I had the chance to work with an impressive team of highly dedicated individuals from day one, which really helped me handle the workload and start building my intuition around business management.

The daily grind remains but today I think I’m more astonished by the pace at which the industry is evolving, with the machine learning landscape radically changing from one quarter to the next. While this makes navigating through the maze of opportunities and setbacks more complex, I’m also pleasantly surprised to notice how exciting it is to take on this challenge and how satisfying it can be to reach new milestones as Unify keeps growing.

Can you speak about some of the ways your company is currently leveraging AI? What are the use cases? Is AI living up to the promise in your experience?

While we plan on using AI at some point to augment our product with new features and make it more efficient, we are currently using AI mostly internally but finding it to be tremendously useful on many fronts. From simplifying knowledge sharing through AI-powered documentation to productivity boosts from AI-assisted coding and content creation. Whether external or built in-house, we have integrated various AI-based solutions into our processes and the overall impression we are getting as a team is one of increased focus on fundamental value creation and more time to tackle the complex engineering challenges.

How should aspiring entrepreneurs leverage AI in their initiatives?

I think it’s important for new entrepreneurs to understand what AI can and can’t do for them when it comes to building their business. As powerful as AI technology can get, fundamental value-creation has to be built on top of thoughtful product design and deep understanding of the business needs of potential customers, and these components simply cannot be left for an AI tool to determine on its own.

Further, it can be tempting to off-load as much as possible on AI in an effort to optimize processes, especially when dealing with unfamiliar topics, but this can quickly end-up becoming more harmful in the long-term if not properly supervised. AI can massively help deal with straightforward-to-relatively-complex tasks, but I believe it’s fundamental for aspiring entrepreneurs to take the time to tackle some of these tasks themselves to get a stronger feeling on when a specific task can best be left for an AI to handle, and how AI can specifically help with it if so.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

I would say the simple sentiment “Make your bed” has had a big impact on me over the years. Everyone has ups and downs in life, and everyone has the propensity to feel burnt out, overwhelmed, or feel as though they’re not doing or achieving enough. I think it’s very important to create a strong foundation upon which to build, and you can’t do this unless you celebrate the little things, even as small as making your bed in the morning and going out into the day with the intention of having a small positive impact in whatever way you can. Big achievements only arise through the culmination of little things over time anyway. Personally, my only goal every day is to dive into each new challenge with full energy and enthusiasm, with the intention to execute to the best of my ability, without fear and without regrets if things don’t work out as I originally hoped. Regardless of whether this culminates in outward success, executing like this every day is the best way to lead a fulfilling life, which is the only success that matters on a personal level anyway!

What are some of the industries that AI will most impact over the next decade?

It’s hard to imagine which industries will be most affected by AI at this stage given how it is radically transforming work across all sectors of activity and at all levels. Ironically, I think such industries like manufacturing won’t strictly count among the most impacted industries, if only because of the impact automation already has on them.

I would argue the sectors that could end up feeling the most impact would be deep-tech industries where AI could exponentially increase the prospects of research, massively cutting down on time taken to reach new discoveries and expanding the scope of experiments. One example of such an industry would be biology where AI could do more than just increase the efficiency of processes and actually open up avenues for progress that couldn’t be reachable without the computational capabilities of AI models in dealing with complex biological structures, of course healthcare would stand to greatly benefit as well by extension.

Other industries that could witness great transformations include industries where AI would create the need for re-invented processes and systems. For e.g cybersecurity could be vastly impacted as AI increasingly raises concerns on data privacy and the ethics of building and handling training data in general, fostering the need for radically transformed ways in which cybersecurity is conducted.

Who is your modern-day hero and why?

My (semi) modern day hero is James Baldwin. While not as well known as other thought leaders such as Malcolm X and Martin Luther King, the eloquence, articulation and grace with which he advocated for civil rights during the 1960s has been a source of inspiration to me. Similar to Martin Luther King, he was able to show deep empathy and understanding even to his biggest adversaries, who were belittling the plight of those lacking civil rights in the US. His ability to show compassion and respect to those who thought very differently, or even to those who were actively causing direct harm through their beliefs, was inspiring. I think the world would be a much better place if more people practiced critical thinking, understanding and empathy.

What is your biggest stress reliever?

Spending time with my friends and family is my biggest anchor in life, and maintaining these relationships is essential to anyone such that the stresses of work never take center stage. Aside from this, I find exercise to be a big stress reliever.

What is your biggest goal? Where do you see yourself in 5 years from now?

I actually don’t see myself in 5 years time as much different than today. I am very much enjoying the hustles of building a fully-remote company, the freedom of movement it provides and, ironically, the strong human component of meeting people around the world for various opportunities and avenues. I do expect Unify to have grown tremendously by that time obviously and I think materializing the company’s vision to make it a world-adopted tool for streamlined machine learning innovation is my biggest goal in the coming years, probably even the foreseeable future given the scale of the task at hand!

Have you got any advice for companies that are looking to employ AI tools and techniques?

I talked about the fragmentation across the ML stack and how I see it as one of the biggest issues in the space currently so if I had to give any advice to companies leveraging AI technology it would be to take the time to understand this fragmentation and how it can implicitly hurt their business.

I think most companies who don’t want to spend time assessing their exposure to the various components of the stack don’t fully realize how much they are leaving on the table in terms of performance loss and inflated costs. Unfortunately, these issues tend to build-up unnoticed and by the time they start to have a significant impact on the bottom line, the company is generally too tied to its current infrastructure and switching to something more adapted to its size and needs can be costly at that point. While we strive to help companies navigate through the maze, they still need to get a sense of their actual needs regarding the tools and techniques they want to leverage, and this is something that can only be achieved through proper understanding of the various factors involved.

Speaking of changing infrastructure, another point that could be useful for companies to keep in mind is to remain flexible with their systems. The AI space is changing at a rapid pace and efficient tools can become obsolete in a matter of weeks, so staying alert and striving to maintain this flexibility for change can be a great asset.


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