Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: You're listening to Bloomberg Business Week with Carol Masser and
Speaker 2: Tim Stenovek on Bloomberg Radio.
Speaker 1: Garbage in, garbage out.
Speaker 3: What could you be talking about, mister Stenevak.
Speaker 1: Well, it's like you know computer science term from back
Speaker 1: in the day, but we talk about it a lot
Speaker 1: with AAI, like if data that goes into something is flawed,
Speaker 1: the data that comes out is flawed. It's only as
Speaker 1: good as the data that goes in.
Speaker 3: Yeah, we do talk about this in the context of
Speaker 3: artificial intelligence hallucinations. It's like when an LM gives you
Speaker 3: an answer that you know is totally off base, or
Speaker 3: gives you a picture image that's way off the mark
Speaker 3: as well.
Speaker 1: Sorry, I was just thinking to my friend, like, actually
Speaker 1: asked for an invitation to want you go on to
Speaker 1: create an invitation for a Halloween party, and he was
Speaker 1: like he wanted the image generator to be to really
Speaker 1: mess it up, like.
Speaker 2: Oh totally.
Speaker 1: He's like, no, make it more messed up, mess it
Speaker 1: up even more.
Speaker 2: Oh yeah it did.
Speaker 1: Yeah, sometimes it does what it tells you to do.
Speaker 3: Oh yeah, it worked.
Speaker 2: Now I'm curious. Tvd'll find it one. I bet she's
Speaker 2: AOKI thinks about this stuff a lot. Not the halloween
Speaker 2: part of this, but you know, the hallucination stuff. She's
Speaker 2: the founder and CEO of bio Render. It's a company
Speaker 2: that creates software to generate scientific images and illustrations. It's
Speaker 2: important that those are accurate. She was formerly the lead
Speaker 2: medical illustrator for National Geographic. She did that for a decade.
Speaker 2: She joins US from Toronto. She is welcome to the program.
Speaker 2: I'm by a very interesting company. We don't talk about
Speaker 2: this part of AI a lot. You've got this recent
Speaker 2: partnership with Anthropic, the maker of the Claude LM. You
Speaker 2: have this incredible background Johns Hopkins School of Medicine, a
Speaker 2: dual BFA and fine Art and pre med from Queen's University.
Speaker 2: Why is scientific imaging important in the context of AI.
Speaker 4: Yeah, Firs, thank you for having me, Carly and Tim,
Speaker 4: and you know, for science in particular, accuracy is really paramount,
Speaker 4: and so we're really excited to partner with companies like
Speaker 4: Anthropic because this is just actually one big step in
Speaker 4: making AI safer and more reliable for science. You said
Speaker 4: that you know your friend made some Halloween invites or
Speaker 4: garbage in garbage oe and that, and that truly is
Speaker 4: the case right now. It really doesn't do scientists work justice.
Speaker 4: How bad the state of bioimages are today and actually
Speaker 4: the you know, Dario Nthropic CEO said that AI could
Speaker 4: compress the next fifty to one hundred years of biological
Speaker 4: progress into just five to ten, which means that the
Speaker 4: bottleneck really ships from computation to human comprehension.
Speaker 1: Do you talk about Dario Amiday, I'm sixty minutes last night. Yeah,
Speaker 1: I've interviewed him before over in the in March in
Speaker 1: San Francisco. Do you believe him? Do you believe Do
Speaker 1: you agree with him?
Speaker 4: I do? I do, and I agree with him in
Speaker 4: that we know that AI is great at helping with
Speaker 4: discoveries written form, and I think you'll agree that we're
Speaker 4: still not quite there with making visuals, particularly in science
Speaker 4: where it matters so much to be accurate. We've seen
Speaker 4: horrific diagrams of you know, legs with extra bones or
Speaker 4: maybe less obvious mistakes, but you know, more dangerous ones
Speaker 4: are like protein folding the wrong way. It can actually
Speaker 4: mean the difference between a functioning cell in Alzheimer's disease,
Speaker 4: or even like one arrow moving in the wrong direction
Speaker 4: and about metabolic pathway could mean that, you know, we're
Speaker 4: feeding the tumor instead of starving it. And for buyer renders,
Speaker 4: you know, it turns out that this is exactly what
Speaker 4: AI needed. We've been spending the last eight nine years
Speaker 4: building the world's largest library of expert expert vetted biovisuals,
Speaker 4: and we're very proud to be sort of the trusted
Speaker 4: source now, the foundational layer for going forward. You know,
Speaker 4: all the frontier models where accuracy is really non negotiable
Speaker 4: in science.
Speaker 3: Well, tell us a little bit about your company in
Speaker 3: particular what you're doing and this idea of again, these
Speaker 3: are some of these things I feel like we just
Speaker 3: take for granted images within science, right or medicine. But
Speaker 3: tell us about the need to have these images make
Speaker 3: you know, and are they constantly being updated, Like, give
Speaker 3: us an idea of what you guys are doing and
Speaker 3: what we need to understand about medical imaging, not MRIs,
Speaker 3: but just understanding everything and anything that's in the body.
Speaker 4: Yeah, and that's a great point. You MRIs can take
Speaker 4: us to a certain point, but at the end of
Speaker 4: the day. The body is very complex, surgical fields are
Speaker 4: very bloody. Photos don't cut it, and so we have
Speaker 4: to rely on a little bit more of I guess
Speaker 4: artistically licensed rendered graphics and bio renders, a software that
Speaker 4: help scientists create beautiful biological diagrams really quickly. You can
Speaker 4: think of us as sort of the canva or figma
Speaker 4: for biology for those folks that aren't familiar with the
Speaker 4: scientific graphics world. So you can imagine a scientist coming in.
Speaker 4: They drag and drop like an anatomically correct brain, for example,
Speaker 4: onto the canvas. You can zoom in and then look
Speaker 4: at the details of a brain cell interacting with a
Speaker 4: tumor cell, and then you can zoom in even closer
Speaker 4: and show the biochemical reactions happening within the brain cell.
Speaker 4: But you can see how quickly it's getting very technical
Speaker 4: and complex, and before bio under scientists we're actually using
Speaker 4: and they still do believe it or not, primarily PowerPoint
Speaker 4: of all tools. So they spend you know, days, sometimes
Speaker 4: weeks just trying to create one image with you know,
Speaker 4: like the circles and squares and the lines and arrow shapes,
Speaker 4: and so we thought, you know, there's got to be
Speaker 4: a better way. So my co founders and I, Ryan
Speaker 4: Katty and I launched by a Under about eight years ago,
Speaker 4: hoping to solve this communication gap for scientists.
Speaker 3: Who are your customers and how do you guys make money?
Speaker 2: We do make money.
Speaker 4: Yeah, yeah, we've been lucky to be profitable pretty early. Actually,
Speaker 4: it was very fortunate that the scientific community saw the
Speaker 4: need and just up to and our customers are primarily researchers,
Speaker 4: including leaders. Actually they're in there making PowerPoint diagrams. Hopefully
Speaker 4: not much longer if these biorender in pharmaceutical companies, biotechs,
Speaker 4: academic institutions, and even the publishing world.
Speaker 1: Yeah, I'm curious about copyright with this. There's an article
Speaker 1: in Chemistry World from just about a year ago about
Speaker 1: how thousands of published studies could contain images within correct
Speaker 1: copyright license licenses, and they mentioned some biorender images created
Speaker 1: by biorender. Have you guys figured out the copyright issues
Speaker 1: in terms of what you're looking at and then what
Speaker 1: you're producing.
Speaker 4: Yeah, it's a great question. I think. You know, at
Speaker 4: the end of the day, we have to shift the
Speaker 4: narrative to away from sort of the copyright or it's
Speaker 4: sort of the antiquated era of you know kind of
Speaker 4: who published it first. We're really trying. Our mission is
Speaker 4: to empower the world to communicate science and understand it
Speaker 4: faster through visuals. And so what's happening actually now in
Speaker 4: our library is scientists. We have four million plus users
Speaker 4: on our platform. They've been knocking down our doors wanting
Speaker 4: to share their diagrams in our community library. They say
Speaker 4: they don't care if scientists you know, rip it apart
Speaker 4: and use it. They just feel so compelled to change
Speaker 4: the narrative and change the status quo of how science
Speaker 4: is communicated today that they are willing to share the
Speaker 4: work that they do environ render back into the community.
Speaker 4: So it's almost looking more like instead of the Canva
Speaker 4: or Figma, more of the GitHub or even Wikipedia. Because
Speaker 4: they share their work back into our library and either
Speaker 4: we spot errors or the communities quick to jump on
Speaker 4: those errors, we update those and then get back upload
Speaker 4: into the repository. So we're kind of shifting the focus
Speaker 4: away from you know who said it first, to let's
Speaker 4: be open and share our work and really further neck
Speaker 4: celebrate science.
Speaker 3: Yeh, super interesting. Hopefully we can come back and continue
Speaker 3: this in the future. She is AOKI founder and CEO
Speaker 3: bio Render, joining us from Toronto, Ontario, Canada.