- Data from a phase 0 trial
- Informing patient-centered trial design
- Effectively implementing digital wearable technologies
Xuefang Wang
Associate Director, Digital Strategy
Takeda
Kevin Galinsky
Associate Director, Quantitative Sciences
Takeda
Jake Hillard
CEO and Co-Founder
Red Leader Tech
Jake Hillard is an expert in Signal Processing and has launched multiple laser satellite missions to space. He is a Peter Theil Fellow and currently the CEO and Co-Founder of Red Leader Technologies
Andrew Coppin
Co-Founder & CEO
Ranchbot
Olivier Martinon
Vice President External Innovation & Research Alliances
Zoetis
Chip Design
Developer Efficiency
Edge AI
Enterprise AI
ML at Scale
NLP
Novel AI Hardware
Systems Design
Data Science
Hardware Engineering
Software Engineering
Strategy
Systems Engineering
As customer success stories from AI accelerator start ups starting to proliferate, and traction starting to ramp up, it is starting to become clear which ML workloads are most amenable to domain specific architectures, and which market sectors are most likely to adopt novel AI acceleration technologies.
With one company still retaining the majority of market share in the datacenter, and the edge currently a complete wilderness, it might still be a difficult time to launch a new accelerator company. But opportunities for capturing market share across the cloud-edge continuum definitely exist! In the world of HPC, certain ML and non-ML scientific workloads have seen extraordinary, demonstrable speed ups on novel ML systems architectures, and the scientific community only sees demand for acceleration of these types of workloads growing. At the edge some AI chip companies are already shipping in volume, while new applications emerge continuously.
This panel will look at what it takes to make it in the AIHW game, what might shift the balance of power in the datacenter, and how companies can find a niche at the edge.
Enterprise AI
Novel AI Hardware
Strategy
Industry & Investment
Brett Simpson
Co-Founder & Senior Analyst
Arete Research
Brett is a co-founder of Arete (formed in 2000) and is based in the firm's London office. He focuses on the global semiconductor component sector. Brett is a regular public speaker at industry events and after 17 years looking at the sector, has a wealth of experience to draw on. Prior to Arete, Brett spent two years at Goldman Sachs in an equity analyst role, specialising in European technology following three years with Ericsson UK, working in business development, covering all aspects of wireline and wireless telecom infrastructure.
Gayathri Radhakrishnan
Partner
Hitachi Ventures
Gayathri is currently Partner at Hitachi Ventures. Prior to that, she was with Micron Ventures, actively investing in startups that apply AI to solve critical problems in the areas of Manufacturing, Healthcare and Automotive. She brings over 20 years of multi-disciplinary experience across product management, product marketing, corporate strategy, M&A and venture investments in large Fortune 500 companies such as Dell and Corning and in startups. She has also worked as an early stage investor at Earlybird Venture Capital, a premier European venture capital fund based in Germany. She has a Masters in EE from The Ohio State University and MBA from INSEAD in France. She is also a Kauffman Fellow - Class 16.
Karthee Madasamy
Founder & Managing Partner
MFV Partners
Samir Kumar
GM & Managing Director
M12
Samir is a managing director at M12, leading investments globally where artificial intelligence or machine learning is a key point of leverage.
He also stewards the fund’s Vanguard Bets investment category—startups aiming for breakthroughs that will result in generational shifts in the technology landscape. Samir’s other investment focuses include quantum computing, robotics, autonomous systems, transportation and silicon—especially for AI. Samir manages a team developing theses for new technology areas and oversees the fund’s technical and scientific advisory board.
Prior to joining M12, Samir was a senior director of business development and product management in Qualcomm’s corporate R&D division. There, he led early-stage product validation, partnerships, acquisitions, and strategy for embedded machine learning, computer vision and heterogeneous computing. Samir started his career at Microsoft, where he spent several years leading product management and product planning efforts for enterprise mobility before joining Palm and Samsung.
Samir is a regular conference speaker on his investment focus areas. He has served on or moderated panels of VCs and subject matter experts at LDV Vision Summit, tinyML Summit, and Cybersec&AI Connected.
As AI makes its way into healthcare and medical applications, the role of hardware accelerators in the successful deployment of such large AI models becomes more and more important. Nowadays large language models, such as GPT-3 and T5, offer unprecedented opportunities to solve challenging healthcare business problems like drug discovery, medical term mapping and insight generation from electronic health records. However, efficient and cost effective training, as well as deployment and maintenance of such models in production remains a challenge for healthcare industry. This presentation will review a few open challenges and opportunities in the healthcare industry and the benefits that AI hardware innovation may bring to the ML utilization.
Developer Efficiency
Enterprise AI
ML at Scale
NLP
Novel AI Hardware
Systems Design
Data Science
Software Engineering
Strategy
Systems Engineering
Hooman Sedghamiz
Senior Director of AI & ML
Bayer
Hooman Sedghamiz is Director of AI & ML at Bayer. He has lead algorithm development and generated valuable insights to improve medical products ranging from implantable, wearable medical and imaging devices to bioinformatics and pharmaceutical products for a variety of multinational medical companies.
He has lead projects, data science teams and developed algorithms for closed loop active medical implants (e.g. Pacemakers, cochlear and retinal implants) as well as advanced computational biology to study the time evolution of cellular networks associated with cancer , depression and other illnesses.
His experience in healthcare also extends to image processing for Computer Tomography (CT), iX-Ray (Interventional X-Ray) as well as signal processing of physiological signals such as ECG, EMG, EEG and ACC.
Recently, his team has been working on cutting edge natural language processing and developed cutting edge models to address the healthcare challenges dealing with textual data.