CONSTELLATION RESEARCH

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Generative AI and large language models (LLMs) have received plenty of buzz, but enterprises need to stay focused on how domain-specific models develop. Why? That's where the returns will be.


At Constellation Research, we've kicked around small language models, safeguarding corporate data while tuning LLMs and how the real wins will be for specific use cases. Generative AI is nice for search and consumer use cases, but the magic happens when enterprises drive returns.


Fortunately, domain specific models are developing quickly. For instance, Google Cloud outlined Med-PaLM 2, a medically tuned LLM, that's aimed at healthcare. Google Cloud launched a bevy of AI tools at Google Cloud Next for CIOs to digest.


Bayer is using Google Cloud’s Vertex AI Search and exploring Med-PaLM 2 use cases. Hospital giant HCA is working with Google Cloud to leverage Med-PaLM to support doctors treating patients. Google Cloud fleshed out the HCA collaboration a bit more in a release, but the gist is that the two parties, along with Augmedix, is tuning models to support doctors and nurses. HCA is targeting:


  • Using generative AI to improve patient handoffs between nurses.
  • Bolster speech to text with ambient medical documentation.
  • Using Google AI to document key medical information more easily from conversations during patient visits. 


According to Google Cloud, prompts were designed to guide the LLM toward topics such as medication changes, lab results, vital sign fluctuations and patient concerns. HCA is collecting nurse feedback to refine the tool. Ultimately, HCA wants to use Med-PaLM 2 LLM to support caregivers.


8 takeaways from Constellation Research's Healthcare Transformation Summit


My bet is that these domain-specific LLMs are going to be the real win for enterprises since they can leverage models and refine with their own data. These large LLMs such as PaLM, ChatGPT and LLama will have versions for various industries and use cases.


And this trend is going to go beyond healthcare. See:



Aneel Bhusri, CEO of Workday, said during the company's second quarter earnings call that it is using customer anonymized data to train LLMs. "We can then do domain-specific large language models, and those are smaller and less expensive. And we turn around and use those models to either make our products more competitive or they're the basis of new SKUs like the Skills Cloud," explained Bhusri. The real takeaway is that Workday isn't going to go add-on happy with charges.


He said:


"I think you see us more in the mode of new SKUs like Skills Cloud rather than actually charging for any insight from the data -- that it's the customer's data. They allow us to use it in an anonymized way and we give them the results back. But I think what it allows us to do is train these large language models and then domain specific ones that will create new SKUs."


Intuit CEO Sasan Goodarzi was also bullish on domain-specific LLMs. Goodarzi said that Intuit "has incredibly rich longitudinal, transactional and behavioral data for 100 million customers."


Goodarzi added:


"For small businesses, we have a 360-degree view of their business and customers. We have 500,000 customers and financial attributes per small business on our platform and this data gives us insights into behaviors, income streams, expenses, profitability, and cash flows, enabling us to provide personalized experiences and recommendations to help them prosper.


Additionally, we have 60,000 financial and tax attributes per consumer on our platform. We are using our data to fine-tune our own financial large language models that specialize in solving tax, accounting, cash flow, marketing, and personal finance challenges."

Supernova Finalist Futures Recovery Healthcare: 5 AI Takeaways from Dr. Tammy Malloy

Dr. Tammy Malloy PhD, Chief Operating Officer of Futures Recovery Healthcare, a Palm Beach, FL alcohol and drug rehab treatment center, implemented an AI-based assessment technology from Aiberry to improve quality of care.


I recently did a deep dive on the project with Malloy, Linda Chung, Co-CEO and Co-Founder of Aiberry, Co-CEO Johan Bjorklund, and Dr. Jason Shumake, PhD, director of data science and clinical research at Aiberry. Here are five lessons learned and you can see the PDF for the whole story.

  • AI can be more engaging in a clinical setting. One surprise in the project was that many clients chose AI-based assessments over human interaction. AI stayed with clients, who felt less judged, said Malloy.
  • Healthcare transformation depends on people who know healthcare as well as technology. Aiberry, which worked with Futures Recovery Healthcare to implement AI-based assessments, is led by co-CEOs, Bjorklund focused on technology and operations, and Chung who is a clinician and understands the workflows. Malloy said knowing the healthcare challenges and workflows were critical to the project.
  • Keep it simple. Aiberry and Futures Recovery Healthcare focused on a workflow and user experience that was simple for clients. You didn't want to put people through a 3-hour assessment when they're going through a detox.
  • Transparency matters for clinician adoption. Aiberry didn't walk clinicians through models and weightings of variables, but they did show how the algorithms reached an answer. Tuning of the system was made with the guidance of therapists in the field.
  • AI is a multidisciplined team sport. Aside from knowing healthcare and technology, Aiberry and Futures Recovery Healthcare had people who were familiar with multiple disciplines and data strategies.


Download the full customer story here.

NOTEBOOK


πŸ”„ More than half of manufacturers (54%) said their annual rate of turnover is above 20%, according to a new survey from UKG Workforce Institute.


πŸ’» 2023 PC shipments are forecast to decline 13.7% year over year to 252 million units, according to IDC.


☁️ Google Cloud customers use more than 13 products on average, according to presentations at Google Cloud Next.


πŸ“₯ Another Google Cloud Next fun fact: Yahoo is migrating 500 million Yahoo Mail mailboxes and 550PB of data to Google Cloud.


πŸ—ΊοΈ Intel said its data center roadmap is on track with 5th Gen Intel Xeon processors (code-named Emerald Rapids) sampling with customers for a fourth quarter of 2023 launch. Intel Xeon processors with E-cores (Sierra Forest) are on track for delivery in the first half of 2024.


πŸ₯ͺ In the yum department. J.M Smucker reported first quarter earnings and said on an earnings conference call that its Uncrustables business is booming and should hit $800 million in sales for the year.

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