Edge compute maker SIMA.ai hires former AWS exec as new CBO. Read our exclusive interview.

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San Jose-based edge computing startup SiMa.ai has made waves recently with the release of Palette Edgematic, its no-code, drag-and-drop system for deploying AI on low-power edge computing devices, for which it also designs its own chips (fabricated by TSMC).

Now, the company is pushing further ahead to bring its devices and software to market, announcing the hire of Elizabeth Samara-Rubio as its new Chief Business Officer.

Samara-Rubio comes with an accomplished background, having worked previously as Global Head of Language, Vision, Industrial, Applied AI Go-To-Market and Business Development at Amazon Web Services (AWS). Prior to that, she worked as managing director of strategy and consulting at Accenture, which also recently committed a significant investment toward AI tech.

VentureBeat had the chance to interview her about her background and new role as competition in the AI and edge compute market only heats up, with big players such as Lenovo also entering the fray. The following is our Q&A that Samara-Rubio completed over email.


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VentureBeat: What led you to SiMa.ai and what unique skills from AWS and Accenture do you bring to the table? 

Samara-Rubio: My career in high tech has spanned many domains. I worked with natural language processing for customer experience applications and for the better part of six years, computer vision in the industrial and manufacturing sectors. 

At AWS, I led the global go-to-market specialist team for AI services to accelerate adoption and scale across Language, Vision, Industrial, and Edge ML including generative AI. At Accenture in Industry X.0, I was responsible for its growth through acquisitions, new digital manufacturing capabilities, and Vision/AI powered industry solutions. 

What I bring to the table is more than just a list of roles and accomplishments. My guiding principles are the bedrock of my career, and something I’m excited to bring to SiMa.ai. First, an obsession with prioritizing the customer’s outcomes and working backward from their goals. Second, diving deep in work with customers to build a blueprint for the solution and the change introduced into their business processes. 

I already saw these things at play in my introduction to SiMa.ai, which only heightened my excitement to work at the company democratizing AI and ML for anyone at the edge. 

Given SiMa.ai’s recent success with Palette Edgematic and MLPerf tests, what are your initial goals as Chief Business Officer? 

It’s the perfect time to join – we’ve made huge strides to-date in bringing ML and AI to the edge with technology that rivals or beats incumbents, and we’re ready to put our collective foot on the gas. We have completed the requirements for qualifications of our hardware and software and now it is time to 100% focus on the customer journey. 

I am excited to help the team focus on working backward from our customers’ success stories. Part of this journey involves proactively sharing the infinite possibilities of SiMa’s edge AI system with the world. I believe we are only just beginning to narrate this story. 

Can you share your view on the market size for edge computing and edge AI? How much of that market does SiMa.ai aim to capture? 

The edge computing market was valued at $9.1 billion (USD) in 2022, and I believe it will only expand with the innovation of wearables, smart devices, robotics, and other products.

Use cases for artificial intelligence are expanding every day, but the people building these AI products cannot get far without a solution that ensures their technology can run effortlessly across devices. SiMa.ai has made its case for addressing this gap, and we’ll only get better from here. 

Are there plans for SiMa.ai to diversify its offerings beyond edge computing and edge AI? If so, could you provide some insights?

At this time, SiMa.ai is focusing on bringing computer vision to low powered devices at the edge. As the use cases for generative AI on edge devices proliferate, we’ll explore the best options for our customers to access the technology’s power and potential via SiMa hardware and software. 

You’ve worked in business development and AI implementation. How will that experience guide SiMa.ai’s strategic growth? 

With our combined AI implementation experience and commitment to customer and partner outcomes we will 1/ define and build repeatable solutions, 2/ provide applications and models that accelerate customers and partners time to value (revenue, savings), and 3/ lead the industry by developing highly efficient, multi-modal models at the edge. 

What are some of the most significant challenges currently facing the AI and edge computing sectors, and how do you plan to overcome them at SiMa.ai?

The challenges currently facing the AI and edge computing sectors are multifaceted and require innovative solutions to overcome. The industry’s shift towards ‘collaborative intelligence,’ where AI serves as an assistant to human tasks, is shaping our perspective, but several key hurdles must be addressed to achieve this vision. 

The journey towards this goal presents significant challenges including cost considerations, customer readiness to adopt AI at the edge, data access, and governance in edge model management. 

  • Multi-modal (text, audio, vision) AI means the tech deployed has to do all of these things efficiently and accurately. Has to be trainable and models need to be maintained. Security of data and user identities. 
  • End-customers today often find that they require not just one or two but many partners with specialized expertise to build, deploy, and manage their AI-power edge solutions. 

Overcoming these challenges necessitates a strategy like ours. SiMa.ai provides customers the hardware and software tools to 1/ select the right models for their applications, 2/ determine the most efficient and cost-effective architectures to run them, and 3/ ensure privacy and security.

Our approach enables customers to leverage current vision models (CNN) and emerging multi-modal models. SiMa.ai partner network assists customers to deploy and manage these applications at scale. 

How do you see the role of SiMa.ai in shaping the future of these sectors, especially in delivering high-performance solutions to various industries?

SiMa.ai is playing a pivotal role in shaping the future of AI and edge computing by delivering high-performance solutions to various industries. Our focus is on enabling AI-driven “collaborative intelligence” in automotive, healthcare, industrial automation, and more. We believe that AI’s potential impact is immense, and our technology empowers companies across these industries to harness the benefits of AI at the edge. 

Can you discuss your approach to business strategy and how you aim to steer SiMa.ai through its next growth stages?

There are three key principles that guide my approach for SiMa.ai success:

  1. Customer Outcomes: By focusing solely on outperforming the competition, the conversation can eventually become one of imitation. We prioritize accelerating time to value for customers, leading industry through innovation, and scaling with partners. 
  2. Prioritization and Trust: Within SiMa.ai, we encourage open discussions about what’s working and what’s not working and emphasize prioritization, ensuring that team members focus on the most critical tasks for SiMa.ai. We carry forward this same approach with our partners. This approach shortens the cycle for innovation and value-creation. 
  3. Lead Vision: Align the ecosystem around a viable and compelling narrative and timeline for technology evolution. The AI landscape is evolving rapidly and each customer will be deploying AI in phases over the coming decade. Sima.ai leadership in efficient and accurate multi-modal edge AI is the beginning of this journey. 

These principles will guide us through our growth stages, enabling us to lead in the industry while delivering value to our customers. 

What is SiMa.ai’s plan to make an impact across different industries, given its focus on high-performance solutions?

By bringing ML and AI to the edge, SiMa.ai is giving every day devices new capabilities that will improve business processes, cost inefficiencies, give computing more sustainable alternatives, provide new job opportunities, and create outlets for potential for innovation we never thought possible. Soon, giving machines computer vision will be table stakes as these devices become multimodal, understanding direction based on multiple inputs or “senses.” 

Applying generative AI, LLMs, and advanced computer vision into industries spanning manufacturing, healthcare, defense, robotics and agriculture requires a new form factor where hardware and software work seamlessly together to increase performance and conserve energy. From better harvesting technologies, to smart factories and manufacturing with automated quality inspection, to drones that find and transport medical supplies to remote locations, the future of machine intelligence has endless applications if only the right technology is applied. 

10. Are there any upcoming projects or initiatives at SiMa.ai that you’re particularly excited about? 

We definitely have some exciting projects in the pipeline. While I can’t reveal specific details at the moment, I can tell you that we are continually enhancing our hardware and software offerings to bring even more powerful and efficient AI solutions to the market. We’ll definitely send more details your way before we announce publicly!

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