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Search ×
Artificial Intelligence, big data, Blog Post, Composite AI, Digital
Transformation, Enterprise Data, Enterprise Search, Gartner, Generative AI,
GPT-3, Large Language Models, LLM, Machine Learning, Report, Unstructured Data


TAMING A STOCHASTIC PARROT

Steven Grinberg

March 28, 2023

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HOW THE ENTERPRISE CAN BENEFIT FROM GENERATIVE AI



In the past few months, we’ve seen record-breaking amounts of news about
ChatGPT. It’s being positioned as the next big disruptor and the questions are
pouring in:

 * Will this replace search?
 * Is it accurate?
 * Is it secure?
 * Can I use this for my business?

That’s just a small sample. Answering the above questions with respect to
ChatGPT in its current state: it's unlikely.

At its core, ChatGPT uses Large Language Models (LLMs) to process input queries
and generate outputs that appear convincingly human. In other - somewhat layman
- words, it finds a bunch of terms that are related to the original input and
recombines them according to the probability of each related term's relevancy to
produce a valid-looking output. This is why it’s often referred to as a
“stochastic parrot.” Consequently, this can result in outputs that are partially
incorrect, a phenomenon that is referred to as hallucination.

Two important elements that can make ChatGPT (and generative AI more broadly)
successful are the scope and timeliness of the data that it is trained on. If it
only has access to a small set of outdated data, the outputs it produces won’t
be able to offer much value - especially in the enterprise. Additionally, LLMs
need to satisfy enterprise’s existing requirements related to security and
Access Control Lists. In case it gets access to internal/confidential
information, companies need assurance that information handling fully satisfies
their requirements. Once these hurdles - and a few others - can be overcome, the
answer to the questions at the top becomes: it’s possible.

Generative AI is having an impact, but not so much on the enterprise's internal
data in its current state. This will happen in conjunction with existing
technologies, namely insights engines. We see the integration of generative AI
with the insight engine being the most successful path for enterprises taking
advantage of this technology

Gartner states: “We expect to see this evolution of the insight engines continue
through the combination of generative AI assistants, metadata-driven knowledge
graphs, and integration via APIs to and from analytics and BI systems. The
result will be a richer and personalized knowledge worker experience across
structured and unstructured data and content.”1

Squirro is helping drive this revolution by introducing its enterprise-ready
generative AI solution. The solution brings all the benefits of generative AI to
enterprises while eliminating its limitations.

Squirro’s solution combines LLMs with its own Composite AI - fusing different AI
technologies, like Machine Learning and Knowledge Graph, - and Insight Engine
technologies. This means enterprises can generate accurate and fully
contextualized results based on their own data and eliminate hallucinations, by
adding the source of information to the LLM response as evidence and providing
transparency and explainability in a secure and compliant way.

To learn more about Squirro’s Generative AI solution, download this e-book and
FAQ.

Read the Gartner report (footnote 1) about the implications of ChatGPT on data
and analytics by completing the form below.





1Source: Quick Answer: What Are the Short-Term and Midterm Implications of
ChatGPT for Data and Analytics?, Rita Sallam, Jim Hare, Bern Elliot, David
Pidsley, Erick Brethenoux, Roxane Edjlali, Radu Miclaus, Pieter den Hamer, Afraz
Jaffri, Kurt Schlegel, Julian Sun, Georgia O'Callaghan, 23 February 2023 - ID
G00786939

Gartner does not endorse any vendor, product or service depicted in its research
publications, and does not advise technology users to select only those vendors
with the highest ratings or other designation. Gartner research publications
consist of the opinions of Gartner’s research organization and should not be
construed as statements of fact. Gartner disclaims all warranties, express or
implied, with respect to this research, including any warranties of
merchantability or fitness for a particular purpose.



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