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Edge AI Summit 2019
20-21 Nov 2019
COMPUTER HISTORY MUSEUM, MOUNTAIN VIEW, CA
Limitations of cloud-based AI, such as latency, power consumption, security and cost, have become bottlenecks for the deployment of AI products and services in environments close to data sources. The Edge AI Summit focuses on the challenges of disaggregating AI processing across the edge computing paradigm, from cloud to device via localized ‘fog’ compute nodes near the network edge. Themes for this year’s summit focus on challenges such as embedding tiny machine learning models on battery-powered devices, using AI for network slicing, applying machine learning to streaming data, and deploying cohesive infrastructure to empower developers to build AI software for the edge. The Edge AI Summit attracted 150+ technology leaders from across the globe in December 2018, and returns this November for tech companies, device manufacturers and enterprises who are deploying machine learning to the edge.
 
17-18 Sep 2019
COMPUTER HISTORY MUSEUM, MOUNTAIN VIEW, CA
Take advantage of over 9 hours of dedicated networking time to meet key industry leaders, whilst also exploring:  Luminary Keynotes: Unique perspectives from industry luminaries in hardware (John Hennessy), AI (TBC) and investment (Lip-Bu Tan).Innovations and Optimizations of Silicon & Systems for AI Training & Inference: Presentations and product launches from C-level executives from AI chip start ups, semiconductor companies and systems OEMs.Training & Inference at Hyperscale & AI Accelerators in the Data Center Hardware Environment: Deployment & maintenance of AI infrastructure in data centers, hardware requirements for training & inference at scale.Inference in Client (Edge) Computing: Applications for AI accelerators in cameras, consumer electronics, autonomous vehicles etc.Beyond Compute: AI’s Impact on Memory, Storage & Networking: Innovations in HBM, on-chip memory and NVM, I/O bottlenecks, data transfer & high-speed interconnects.The Impact of Future ML Models on Hardware Design: Machine Learning co-design, robustness & reprogrammability, model standardization & interoperability.AI Chip Design & Commercialization: Design, testing & manufacturing, form factors & routes-to-market.Financial & Industrial Analysis: Market growth and maturity, VC investment trends & dynamics, the commoditization of the inference market, benchmarking & metrics.“Two overarching efforts are indispensable in this AI chip development frenzy: objectively evaluating and comparing different chips (benchmarking), and reliably projecting the growth paths of AI chips (road mapping).” White Paper on AI Chip Technologies: Tsing Hua University & Beijing Innovation Center for Future Chips, December 2018.
 
4-5 Jun 2019
HILTON BEIJING CAPITAL AIRPORT, BEIJING, 100621
The AI Hardware Summit is the first and only conference dedicated solely to the ecosystem developing hardware accelerators for neural networks and computer vision.Join 200+ senior technology leaders from AI chip start-ups, semiconductor companies, system vendors/OEMs, data centers, end users, financial services, investors and fund managers, to build a comprehensive architectural roadmap of the emerging AI chip market.Take advantage of unique networking opportunities to meet key industry leaders 1-2-1, whilst also exploring:  Innovations and Optimizations of High-Performance Chip Architectures: GPUs, ASICs & TPUs, FPGAs…Alternative Approaches: hybrid digital/analog computing, neuromorphics & neuromemristive systems, quantum computing.The Role of Software: assistance software, software frameworks, ecosystems, and applications. Generating user-friendly native code and linking open source machine learning frameworks like TensorFlow & Caffe.Industry Developments: Start-up & Corporate R&D, Venture Capital and Corporate Venture Capital investment trends, strategic acquisitions & partnerships.Forecasts predict that the AI (chipsets) market is expected to grow from USD 7.06 Billion in 2018 to USD 59.26 Billion by 2025, at a CAGR of 35.5% from 2018 to 2025 (Business Wire, 2018), the chip market is no longer standing still. As we approach a paradigm shift in computing, there is little doubt that a combination of the processing units currently in development will accelerate AI research and development, far beyond the capabilities of current platforms.  There is need for sharing knowledge on the best way to turn this shift into an opportunity and roadmap the future ahead.
 
Edge AI Summit
11 Dec 2018
San Francisco, USA
Data has gravity.It is well known that the network edge, in the Internet of Things, is where the critical mass of digital data resides, and where it is collected. Scalability bottlenecks to ubiquitous AI, such as power consumption, bandwidth, latency, connectivity and security have led to recent innovations in on-device processing and edge infrastructure such as micro-data centers and distributed computing architecture.The Edge Computing market will reach $34 billion by 2023, growing at 35% annually, unleashing a wave of services and applications at the network edge that can be optimized with artificial intelligence. As a recent explosion in hardware innovation provides the necessary compute to migrate diverse AI workloads to the Edge, a new generation of edge-native and edge-enhanced software applications is emerging.The Edge AI Summit will bring together 200+ key thought-leaders and industrial practitioners to discuss the challenges and opportunities of decentralized, distributed intelligence. Join us to examine use cases of edge-based artificial intelligence applications and explore this new computing paradigm that promises to accelerate and democratize AI adoption across the globe. This event is intended for Senior Director/VP-level attendees and above, and is a high-level networking and business development meeting, with content tracks focusing on both business and technology.
 
AI Hardware Summit 2018
18-19 Sep 2018
Computer History Museum, Mountain View, CA
The AI Hardware Summit is the first and only conference dedicated solely to the ecosystem developing hardware accelerators for neural networks and computer vision.Join 250+ senior technology leaders from AI chip start-ups, semiconductor companies, system vendors/OEMs, data centers, end users, financial services, investors and fund managers, to build a comprehensive architectural roadmap of the emerging AI chip market.Take advantage of unique networking opportunities to meet key industry leaders 1-2-1, whilst also exploring:  Innovations and Optimizations of High-Performance Chip Architectures: GPUs, ASICs & TPUs, FPGAs…Alternative Approaches: hybrid digital/analog computing, neuromorphics & neuromemristive systems, quantum computing.The Role of Software: assistance software, software frameworks, ecosystems, and applications. Generating user-friendly native code and linking open source machine learning frameworks like TensorFlow & Caffe.Industry Developments: Start-up & Corporate R&D, Venture Capital and Corporate Venture Capital investment trends, strategic acquisitions & partnerships.Forecasts predict that the AI (chipsets) market is expected to grow from USD 7.06 Billion in 2018 to USD 59.26 Billion by 2025, at a CAGR of 35.5% from 2018 to 2025 (Business Wire, 2018), the chip market is no longer standing still. As we approach a paradigm shift in computing, there is little doubt that a combination of the processing units currently in development will accelerate AI research and development, far beyond the capabilities of current platforms.  There is need for sharing knowledge on the best way to turn this shift into an opportunity and roadmap the future ahead.

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