AI & Machine Learning
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.
ContinueExecutive Foresights
IBM Announces US$2 Billion Investment in AI Campus, Hinting at Reentry into the Semiconductor Business
1Q 2019
The AI Hardware Center at SUNY Polytechnic Institute campus in New York will focus on computer chip research, development, prototyping, testing, and simulation. The new center is being built in partnership with New York State, which hopes the center will attract new companies in the field of AI and create several hundred new jobs. The investment marks IBM focusing more on the hardware side of its business. It also shows IBM’s increased appetite to invest in human capital and to address one of the stickiest problems currently facing the AI community.
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.
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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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Disruption and Opportunity Ahead for Semiconductor, Generative Design, and Private LTE Markets
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Moving AI Processing to the Edge Will Shake Up the Semiconductor Industry
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The Bright Ideas Visionaries Should Have Learned at CES 2019
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Accelerated Growth Opportunities Identified for Telco, Smart Factory, and Enterprise Video Markets
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Deep Learning-Based Machine Vision Accelerates the Drive Toward the Smart Factory
