The One Indispensable Training Source for AIs

training AIs image

The next great leap forward for Large Language Models is sensitivity to human feelings.

Bill Harvey, one of the most famed developers of technology products for the marketing, advertising and media industries (ADI/DMA, set top box data, addressable commercials, big data ROI measurement, ROI optimization, and more; resulting in numerous awards) has developed RMT validated advanced technology for making sensitivity to human feelings “computable”.

Bill Harvey, Co-Founder and Chairman of RMT, Research Measurement Technologies, is a famed developer of commercially viable technology products for the marketing, advertising and media industries. Bill Harvey’s technology initiatives include products that utilize ADI/DMA Geo-Mapping, Set-Top Box data, Addressable commercials, “Big Data” ROI measurement, ROI optimization, and more; resulting in numerous awards.

Prior to RMT, Bill Harvey’s company Next Century Media, was awarded an Emmy® for the pioneering development of technology for measuring privacy-protected television/video audience behavior at the scale of potentially every device in the world. This includes a technology for accurately measuring human feelings and motivations based on the content they consume. “Motivations when thwarted cause negative feelings, motivations when abetted cause positive feelings; there would be no feelings without motivations,” says Harvey. The RMT technology, known as DriverTags has been publicly validated by five separate objective parties, ARF Cognition Council, Nielsen NCS, Neustar, 605, and Simmons (links below).

Starting in March 2023, RMT offers our innovative technologies, methods and expertise to the world’s most advanced AI developers. Our intention is to explore relationships and then select one AI provider for exclusive access to RMT technology and methods for integrating with AI LLM.

The proposal has two aspects:

  1. Provide useful technology for training LLM AIs
  2. Collaborate exclusively in R&D to expand the AI technology so that LLM AIs can metatag encode new semiotic and semantic stimuli

What RMT will do immediately is train your AIs to be sensitive to human feelings. This will be training in both semiotic and semantic content. The RMT meta-tagging of content is the secret sauce. This will equip your AIs to dial up or dial down the dimensions of RMT’s 265 DriverTags/human feelings, a science proven in five separate independent studies to be predictive of improved outcomes and ROI.

RMT proposes to agree with one AI company for a “Paid Proof of Concept” as first step.

AI TRAINING SOW TIMELINE – about 7-9 months to market

  1. All existing RMT DriverTagged content available for use in POC
  2. Test involves prompts regarding which Motivations should be expressed and to what degree; AI partner to select objective test method and judges; with dials or other means, dialing this up and that down as prove to be useful
  3. Images input and other new curated content inputted as available
  4. Ongoing testing to maximize the acceptability to judges
  5. Public sneak testing in panel for ongoing testing
  6. Prove that it works via one or more trusted third parties
  7. Finalize productization & “Go to market”


We look forward to meeting you. All the best,

Bill Harvey, Chairman, RMT

Bill McKenna, CEO, RMT