Foundation Models Are The Bedrock Of A Generative AI Strategy – Forrester
Rowan Curran, Senior Analyst
Charlie Dai, VP, Principal Analyst
Mike Gualtieri, VP, Principal Analyst
Leslie Joseph, Principal Analyst
Aaron Suiter, Researcher
OpenAI’s ChatGPT set the record for fastest-growing consumer application, and there are now scores of other models similar to GPT-3.5 available (both proprietary and open-source), but don’t be fooled: The market for foundation models powering generative AI (genAI) and predictive AI is still in its infancy. For any language-related genAI task — be it writing code, supporting customer service, or creating ad copy — enterprises are relying on what Forrester is calling AI foundation models for language (AI-FMLs). These are the pretrained (typically) large language models (LLMs) that can ingest and generate text, though multimodal models, which can also ingest and produce audio, images, or video, have crested the horizon. This market is evolving and changing quickly, and tech leaders must understand how to navigate it.
Foundation models are the bedrock of genAI-powered applications, and there will be many models (large and small) targeted at different parts of data pipelines and workflows. Forrester clients can learn more about key concepts related to foundation models in our report, The Technology Leader’s Primer For AI Foundation Models, but all readers searching for AI-FMLs with which to build their applications need to know that:
For the foreseeable future, most enterprises will source their foundation models from third parties and not pretrain their own. Forrester clients can start building their AI-FML purchasing strategy using our new report, The AI Foundation Models For Language Landscape, Q2 2024, which includes information on how AI-FML vendors differ in terms of offerings, size, and market focus. When choosing an AI-FML, enterprises must:
We will release a Forrester Wave™ evaluation covering AI-FML this summer, looking at the leading vendors based on scoring criteria such as data preparation, training tools, and model governance. Forrester clients can discuss our evaluative research — or foundation models generally — in more depth by scheduling a guidance session with an AI analyst.
Stay tuned for updates from the Forrester blogs.
Stay tuned for updates from the Forrester blogs.
This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
Charlie Dai, VP, Principal Analyst
Mike Gualtieri, VP, Principal Analyst
Leslie Joseph, Principal Analyst
Aaron Suiter, Researcher
OpenAI’s ChatGPT set the record for fastest-growing consumer application, and there are now scores of other models similar to GPT-3.5 available (both proprietary and open-source), but don’t be fooled: The market for foundation models powering generative AI (genAI) and predictive AI is still in its infancy. For any language-related genAI task — be it writing code, supporting customer service, or creating ad copy — enterprises are relying on what Forrester is calling AI foundation models for language (AI-FMLs). These are the pretrained (typically) large language models (LLMs) that can ingest and generate text, though multimodal models, which can also ingest and produce audio, images, or video, have crested the horizon. This market is evolving and changing quickly, and tech leaders must understand how to navigate it.
Foundation models are the bedrock of genAI-powered applications, and there will be many models (large and small) targeted at different parts of data pipelines and workflows. Forrester clients can learn more about key concepts related to foundation models in our report, The Technology Leader’s Primer For AI Foundation Models, but all readers searching for AI-FMLs with which to build their applications need to know that:
For the foreseeable future, most enterprises will source their foundation models from third parties and not pretrain their own. Forrester clients can start building their AI-FML purchasing strategy using our new report, The AI Foundation Models For Language Landscape, Q2 2024, which includes information on how AI-FML vendors differ in terms of offerings, size, and market focus. When choosing an AI-FML, enterprises must:
We will release a Forrester Wave™ evaluation covering AI-FML this summer, looking at the leading vendors based on scoring criteria such as data preparation, training tools, and model governance. Forrester clients can discuss our evaluative research — or foundation models generally — in more depth by scheduling a guidance session with an AI analyst.
Stay tuned for updates from the Forrester blogs.
Stay tuned for updates from the Forrester blogs.
This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
