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Featured Research
Artificial Intelligence and Machine Learning
This report delivers a quantitative assessment of Machine Learning (ML) usage across numerous consumer, commercial, and industrial device markets. The assessment was informed by, and further refined by, a qualitative analysis of the technological, business, and political drivers and constraints impacting the use of Artificial Intelligence (AI) technologies.
Detailed shipments and segmentation are provided in product-based Market Data (MD) research deliverables spanning automotive, mobile devices, wearables, smart home, robotics, drones, manufacturing, retail, video systems, buildings, and energy. Device categories, segmentation, and annual shipment volumes used in this Artificial Intelligence and Machine Learning MD are derived from existing device and product data sets.
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Executive Foresights
Deep Reinforcement Learning Gets Boost with Dopamine, but Still Requires a Technology Paradigm Shift.
4Q 2018
Google has released an Artificial Intelligence (AI) framework for Deep Reinforcement Learning (deep RL) called Dopamine, giving the field of AI a much-needed boost.
Insights
IBC 2017 Preview – Artificial Intelligence (AI) and Machine Learning (ML) in Media
3Q 2017
The International Broadcaster Conference runs from September 15th to 19th. One of the most significant new trends promoted at this conference will be related to the implementation of artificial intelligence (AI) and machine learning (ML) in video services. Some solutions targeted as AI or Machine Learning simply migrate from editor- or developer-coded optimization methods to neural-network trained solutions, a host of new solutions leverage video analytics to generate metadata.
Analyst Support
Every client is assigned a key member of our research team, based on their organization’s needs and goals. And, an unlimited number of Analyst Inquiry calls are available to answer your specific questions.
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Webinar
Market Forces Driving Edge AI: Enabling Technologies, Value Proposition and Key Use Cases
AI is going to see a dramatic growth in adoption in many verticals. However the currently popular model of having AI inference and training take place in the cloud is simply not appropriate for many use cases, creating a sizable opportunity for edge AI hardware to flourish. In this webinar Malik Saadi, Vice President of Strategic Technologies and Jack Vernon, Industry Analyst, will cover the main drivers for shifting AI to the edge, how the technology stack for AI is changing to reflect the shift, and the market opportunity in edge AI.
This webinar will address the following questions:
- How is AI currently being implemented?
- What is the case for shifting AI processing to the edge?
- What are the use cases that will drive edge AI?
- What are the hardware options for implementing AI at the edge?
- How big is the market opportunity in edge AI implementation?
News
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ABI Analysts to Provide Strategic Guidance About Transformative Technologies to CES 2019 Attendees
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Big Changes for Autonomous Vehicles, Deep Learning and Augmented Reality Markets
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Deep Learning Set to Ignite the Machine Vision Market to a US$193 Billion Opportunity by 2023
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ABI Research’s IMTS 2018 Report Highlights How the Manufacturing Landscape Is Set for ‘The American Industrial Revolution’
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ABI Research’s September 26 Webinar Explores Quantum Computing
