Startup highlight: Interview with Kevin Conley, CEO at Applied Brain Research (ABR)
Applied Brain Research (ABR) is a fabless semiconductor company founded by a team from the University of Waterloo’s Centre for Theoretical Neuroscience, under the leadership of Dr. Chris Eliasmith, the Centre’s founding chair, to commercialize brain-inspired AI inference solutions.
Can you introduce Applied Brain Research and its mission?
ABR’s mission is to bring advanced time series inference out of data centers by empowering edge devices with advanced time series AI capability. Out of its research, ABR invented the Legendre Memory Unit which has established a new chapter of state space models for advanced time series processing. To enable low power edge devices with advanced capabilities like low latency natural language interfaces, ABR has developed an LMU powered time series processor AI accelerator ASIC that will enter the market this year. Our CEO, Kevin Conley, is a semiconductor vet who has built billion dollar businesses in the past and plans to do the same with ABR’s cutting edge technology.
What challenges did ABR face before partnering with OVHcloud?
Our business depends on its ability to train advanced AI models for edge device applications creating technical and financial challenges. This requires the availability of advanced GPUs for network training. Successfully optimizing neural networks for our chip is critical to our success. Our main challenges have been budgetary and scaling our R&D efforts. We decided to explore cloud solutions because investment in our own training capability would be prohibitive both from a cost and management perspective.
How did OVHcloud and the Startup Program help you overcome these challenges?
The Startup Program has let us explore different ways of leveraging OVHcloud’s resources in order to train next generation models, and fine-tune them in ways that would be very difficult to do in house. It lets us quickly expand or focus our efforts without having all of the infrastructure headaches that come along with that typically.
Which OVHcloud services or features do you use, and how do they stand out from other solutions?
We use the Public Cloud service from OVHcloud. Compared to other services from Google, Amazon, etc., OVHCloud provides the most cost-effective solution per FLOP.
How has OVHcloud’s support helped you evolve your infrastructure to meet the demands of your business?
The nature of our AI development cycle means that our usage of AI training hardware fluctuates over time. OVHcloud’s public cloud allows us to dynamically scale up and down our AI training hardware in a cost effective manner.
What tangible results have you achieved since collaborating with OVHcloud?
We have pushed our networks to be the smallest possible ASR networks with the highest accuracy. This was possible because we could do hyper perimeter, searching, using OVHcloud’s infrastructure. Specifically we’ve gotten less than 5% word error rates on full vocabulary speech transcription with a tiny 8 million parameter quantized network. We have built other state of the networks for TTS and Voice Control using the same infrastructure, but we haven’t announced their general availability yet on our platform.
Providing these networks as starting points for customers to use our chip, greatly reduces the barrier to entry for taking advantage of our technologies. Broadening our pre-trained library available customers will only improve that going forward, and this will be much more efficient using OVHcloud than doing it in house.
What are your ambitions for the future of your startup, and how do you see it evolving within the cloud ecosystem? What future challenges do you foresee?
We plan to offer our no code environment to all of our customers, which will effectively scale as we grow, and allow customers to build, train, and deploy all manner of models on our chip. This SaaS offering will be crucial as we deploy our chip to many markets. Our fundamental advantage is for time series processing, i.e. problems where the order of the data in time is important for making decisions. This includes everything from speech and language processing to heartbeat monitoring and fall detection. As a result, we are building a versatile, cloud-hosted development environment that will require rapid scalability.
What advice would you give to other growth-stage startups considering the cloud or joining a support program?
Probably the most important piece of advice is to take advantage of everything that’s provided. This requires some commitment on the side of the startup, but going to the meetings, asking questions, and leveraging the resources is the only way to get the most out of the program.
Applied Brain Research’s journey with OVHcloud, joining the Startup Program then AI Accelerator, highlights how a startup can make the most of available resources to overcome challenges, achieve sustainable growth, and scale. If you’re a startup looking to transform your business, we encourage you to join the OVHcloud Startup Program or contact OVHcloud to discover how our solutions can support your journey!
Katya Guez is the Startup Program Manager for Canada and Latin America. Passionate about innovation, tech and sustainability, she works to support her local tech ecosystems.