Artificial Inteligence Machine Learning Technology 
CIO
NOVEMBER 1, 2024
The world has known the term artificial intelligence for decades. Until recently, discussion of this technology was prospective; experts merely developed theories about what AI might be able to do in the future. Today, integrating AI into your workflow isn’t hypothetical, it’s MANDATORY.
CIO
NOVEMBER 14, 2024
Even less experienced technical professionals can now access pre-built technologies that accelerate the time from ideation to production. As a result, employers no longer have to invest large sums to develop their own foundational models. They can lean on AMPs to mitigate MLOps risks and guide them to long-term AI success.
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CIO
JANUARY 9, 2025
Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. These autoregressive models can ultimately process anything that can be easily broken down into tokens: image, video, sound and even proteins.
CIO
MARCH 14, 2025
Much of the AI work prior to agentic focused on large language models with a goal to give prompts to get knowledge out of the unstructured data. Ive spent more than 25 years working with machine learning and automation technology, and agentic AI is clearly a difficult problem to solve. It gets kind of scary.
Advertiser: Data Robot
Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects? Why do AI-driven organizations need it?
AWS Machine Learning - AI
APRIL 9, 2025
Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.
CIO
NOVEMBER 27, 2024
Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.
Advertiser: Data Robot
And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Fostering collaboration between DevOps and machine learning operations (MLOps) teams. Collecting and accessing data from outside sources.
Advertiser: Data Robot
The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data.
Advertiser: Data Robot
The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.
Advertiser: Data Robot
While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? This white paper covers: What’s new in machine learning and AI.
Speaker: Paul Weald, Contact Center Innovator
Learn how to streamline productivity and efficiency across your organization with machine learning and artificial intelligence! Embrace automation, collaborate with new technology, and watch how you thrive!
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations.
Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software
In this session, Eran Kinsbruner will cover recommended areas where artificial intelligence and machine learning can be leveraged. This includes how to: Obtain an overview of existing AI/ML technologies throughout the DevOps pipeline across categories. Understand the future of DevOps tied with AI/ML technologies.
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