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Hot Tech Innovators: AI and ML
The AI Hot Technology Innovators looks at 14 different AI technology companies, delivering a mixture of solutions to end users and developers. The report gives an insight into the disruptive potential of each company's technology and business model, at the cutting edge of the AI start-up area.
ABI Research has been impressed by a number of companies coming to the fore with what it would describe as non-traditional AI techniques outside of established machine learning – companies highlighted here using automate reasoning, and unique neural language processing are some of the most exciting challengers in the area of AI.Continue
Reports & Data
Automated reasoning has played second fiddle to Machine Learning (ML) in terms of industry attention, research, and productization. However, automated reasoning is beginning to create a huge amount of market opportunity and needs to be taken seriously.
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.
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.
July 11, 2018, 2 p.m.
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:
- What are the most successful AI frameworks?
- What is the difference between the frameworks, and why have some been more successful?
- What direction should frameworks commercial supporters take frameworks in?
- What is the market opportunity for AI at the edge?
- What direction should frameworks ecosystem leaders progress forward in?
AI to Save Healthcare Sector US$52 Billion in 2021
Hardware Vendors Will Win Big in Meeting the Demand For Edge AI Hardware
AI Frameworks Move Toward Interoperability in Order to Compete With TensorFlow
ABI Research Analysts to Provide Strategic Guidance About Transformative Technologies Impacting Industrial Manufacturing to Hannover Messe 2018 Attendees
Future of the Mobile Industry: A Reality Check from Mobile World Congress 2018