Strawberry AI: Speed vs Accuracy
Key Points
- “Strawberry” (formerly known as Q or Qar) is OpenAI’s new large‑language‑model project aimed at advanced novel reasoning, reduced hallucinations, and complex multi‑step problem solving.
- The model’s superior intelligence comes at the cost of slower response times, prompting OpenAI to explore compressing it into a faster, smaller version or offering users a choice between a slower, more accurate answer and a quicker, approximate one.
- This speed‑accuracy trade‑off highlights a broader AI usability challenge: higher‑performing models may require new workflows, such as running tasks overnight, rather than the instant‑chat experience users expect from ChatGPT‑4.
- Although Strawberry has already been demonstrated to U.S. national‑security stakeholders and could represent a step toward artificial general intelligence, its practical day‑to‑day value remains uncertain if users must sacrifice speed for correctness.
Full Transcript
# Strawberry AI: Speed vs Accuracy **Source:** [https://www.youtube.com/watch?v=OxUh8dFqfQY](https://www.youtube.com/watch?v=OxUh8dFqfQY) **Duration:** 00:05:23 ## Summary - “Strawberry” (formerly known as Q or Qar) is OpenAI’s new large‑language‑model project aimed at advanced novel reasoning, reduced hallucinations, and complex multi‑step problem solving. - The model’s superior intelligence comes at the cost of slower response times, prompting OpenAI to explore compressing it into a faster, smaller version or offering users a choice between a slower, more accurate answer and a quicker, approximate one. - This speed‑accuracy trade‑off highlights a broader AI usability challenge: higher‑performing models may require new workflows, such as running tasks overnight, rather than the instant‑chat experience users expect from ChatGPT‑4. - Although Strawberry has already been demonstrated to U.S. national‑security stakeholders and could represent a step toward artificial general intelligence, its practical day‑to‑day value remains uncertain if users must sacrifice speed for correctness. ## Sections - [00:00:00](https://www.youtube.com/watch?v=OxUh8dFqfQY&t=0s) **OpenAI's 'Strawberry' Model Dilemma** - OpenAI’s newly renamed LLM, Strawberry, promises stronger multi‑step reasoning and reduced hallucinations but struggles with speed, potentially leading to a user choice between slower accurate answers and faster approximate ones. ## Full Transcript
AI can give you so much in news it's
hard to keep up here's four things that
happened just in the past couple of days
number one is strawberry information so
strawberry if you're not familiar with
the rumor mail is what everyone is
calling open ai's new large language
model intelligence project it used to be
called Q or qar and they renamed it to
Strawberry I guess it's more friendly
anyway the idea that dropped this time
the rumor that dropped this time this is
in the information I'll link it is that
this is a model focused on novel
reasoning non hallucinatory results and
complex multi-step problem solving and
there is a big drawback we are so used
to the chat GPT 40 model of
instantaneous responses that everyone
sort of assumes that one of the implicit
constraints at chat GPT is they will
keep the speed as they increase the
intelligence that's according to the
rumors apparently proving very difficult
and they're now trying to figure out can
we compress this large model into
something smaller and more performant
that we can put into a chat window to
meet people's expectations or not and
one of the options could be that they
could choose
to give you two options right do I want
the correct answer slowly or do I want
the approximate answer
quickly and and you might think oh we
always go for the correct answer or
maybe you think you always go for the
fast answer but I bet you there's people
on both sides of the fence there and I
think that's part of what's interesting
about this entire
discussion there is no free lunch here
we are increasing
intelligence but increasing intelligence
at the cost of
usability and this is kind of getting
back to one of my fundamental thesis
around sort of the path to artificial
general intelligence which is that
eventually we may get to a spot where
these machines are able to do really
complex problem solving tasks truly
novel problems strawberry may be a leap
in that direction it's apparently been
demoed to the National Security
establishment in the United States
already perhaps it will be right it'll
be a step in that direction
potentially
but even if it is I'm not sure how
useful it will be day to day if it's
slow if you were already used to working
with chat GPT as a
fallible Junior intern someone who makes
a lot of mistakes and by the way I've
known interns much better than Chad GPT
so that is not a knock on interns at
all if you're already used to working
with it as something fallible and you
check what it does and you get
instantaneous responses it's actually a
whole new workflow it's a whole new
problem space to go back and say what
problems do I have that are complex
enough I would want it to run a long
time maybe I set the prompt up and I run
it overnight and I check check in the
morning it doesn't even feel like the
same piece of intelligence or
intelligence allocation at that point it
feels like two sets of intelligences and
you have to sort of decide which one do
I need for this problem and that gets
back to the idea that fundamentally what
we're going to need as a skill as humans
in the new economy is the ability to
allocate tasks across intelligences is
this a human intelligence task and now
is it a chat GPT 4 for model type
intelligence task or is it potentially a
strawberry type intelligence task where
you need that sort of multi-step
reasoning on the first
try and and the key thing is this not so
many problems are actually in that
multip reasoning
process you you may think that there's a
ton of them and maybe on a global scale
there's a lot of meaningful difficult
multistep problems to be
solved but from a pure knowledge worker
in business persp perspective you're not
solving novel multi-step reasoning
problems all that frequently at work
I've got news for
you so we'll see that's the rumor mail
I'll link the information uh leak
article or inferred rumor article or you
know we'll all see when it actually
comes out article underneath the YouTube
here three other things to quickly get
to uh Gemini released another model no
one is paying attention to Gemini and
they just keep giving you free tokens
and so if you're a developer Gemini is a
great one to build with like that
there's just so much free usage that
they give you I think it's in the
billions now in tokens Claude uh
released artifacts which are their sort
of Standalone little like new UI where
they like write something in the side of
the pain and like you can work with it
separately from the main conversation I
find it really useful and that's now out
on
iPhone
and last but not least speaking of
iPhones uh apparently Apple intelligence
is delayed that came out a couple weeks
ago but what came out recently
is that iPhone is still going to have
iPhone 16 is still going to have some
features of artificial intelligence it's
just not clear what is it a hardware
feature is it a software feature it's
not clear so we will see the main news
is strawberry that's what I put at the
top uh what did I miss tell me what you
think of strawberry what would you use
multi-step reasoning for that's the
question that I'm thinking about