You Need to Get
Real With AI and LLMs
Trying to harness all
the world's knowledge to create a sales lead or a new product will only send
your company down a variety of rabbit holes. Industry-specific models are
emerging that will help you narrow your focus.
Expert Opinion By Howard Tullman, General
managing partner, G2T3V and Chicago High Tech Investors @howardtullman1
Sep 10, 2024
Everyone
is talking about ChatGPT, LLMs, and AI, and they all want to know about the
opportunities and risks these new tools and technologies represent to makers,
markets, and, of course, mankind. Most of the conversation seems to be quite
high-level and mainly strategic. You don't hear much about the practical,
operational, and tactical concerns that any entrepreneur who's thinking about
building a new business based on these tools should be addressing. You can
spend your time building castles in the air, but, as Thoreau said, the most
essential task is to put solid and sustainable foundations under them.
Otherwise, you've built nothing of substance or value.
There's
an enormous wave of new AI-focused startups enabled by chat-derived interfaces,
but they suffer from two debilitating deficiencies.
First,
they are sitting on top of too much, rather than too little, information. Even
if you employ the world's best prompt engineers,
they aren't miracle workers, and will soon report back that there is little
likely to be gained by attempting to broadly interrogate vast and largely
irrelevant stores of information. You need to fish where the fish are, rather
than in the entire ocean. The fact that access to the generalized Large
Language Models (LLMs) has been commercialized and simplified isn't a reason to
waste your time and effort, because it won't get you to where you need to be.
It's exactly the same as the old story about the man looking for his lost keys
next to a streetlamp--because the light was better there. 01:49
The
somewhat encouraging news is that at least a portion of the latest
entrants are now starting to offer, market, and fundraise based on
variations of a single theme--the successful implementation of
industry-specific inquiry systems designed to interrogate one or more of the
LLMs that have been built by the four or five tech major players. The idea is
that they will build inquiry tools that limit and focus their tasks only to
those portions of the universal datasets that relate to a given industry, and
use and incorporate distinct terms and particular language.
Building
these "industry-specific" overlays is actually one of the first cases
of a grudging recognition of the obvious fact that asking any general LLM a
detailed question about your specific business is a fool's errand, very much
akin to attempting to boil the ocean. You'll get back vague, broad, and useless
pronouncements (with the occasional hallucination) and not much else. A
proprietary LLM built upon an underlying dataset that relates to your specific
area, interest, business, or industry is the only smart approach. This will
save time, money, and your technical resources, and will be far less costly and
much easier to develop in-house rather than through third-party
vendors.
The
second major concern for many of these new players is that they don't remotely
have control of their own destinies because, at best, they're mere renters of
the powerful LLMs that underlie the entire industry infrastructure. These,
unfortunately, can be altered, limited, withdrawn, or priced in ways that
effectively destroy the operation and the value of the businesses that depend
upon them.
We
have seen this movie many times in the past, perhaps most recently and
glaringly in the various sectors of the digital ad economy. That's where
startups and even well-established companies awoke one morning to discover that
Facebook or Google or Amazon or Apple had abruptly shut off their oxygen, and
their vital traffic, by shifting some criteria, algorithm, or other
categorization, rendering them effectively invisible on the web.
But a
far more telling and direct example of the "platform" problem is the
computer gaming industry, where what began with hundreds of startups aiming to
build computer games ended up a few years later completely dominated by Xbox
(Microsoft), Nintendo, and PlayStation (Sony). They became the only players in
the space because they built and owned the gaming platforms on which every game
(regardless of who built it) needed to be licensed, with fees and royalties
paid to the platform owners.
Today
we're seeing virtually the exact same thing happening with LLMs. The main
LLMs are controlled by the four or five usual tech suspects, who have already
become gatekeepers and toll takers for user access. There's really no way to
avoid or escape them--but, as noted, there's some modest consolation in the
fact that, for many years to come, most businesses won't need access to
such enormous and unwieldy datasets.
The
bottom line is pretty clear. Every new AI startup that is dependent on, and
sits upon, one of these tech giants' platforms for its operations is a tenant
at best, running a business subject to the whims, competitive considerations,
extortions, and other demands. These startups can be cut off in an instant.
It's never smart to build your business on someone else's real estate.
