Speaker 1: If you are hearing the sound of my voice, then
Speaker 1: you are not actually hearing my voice at all. What
Speaker 1: I mean is that the voice you are hearing is
Speaker 1: actually an assistive text of voice cloning tool that my
Speaker 1: company created, and it is completely powered by AI. There
Speaker 1: are many different types of AI tools to help people
Speaker 1: who are differently abled. For me, it has restored my voice,
Speaker 1: but there is so much more it can do. I'm
Speaker 1: excited to see how it grows. Hey, there, I'm grain
Speaker 1: class and this is technically speaking an Intel podcast. The
Speaker 1: show is dedicated to highlighting the way technology is revolutionizing
Speaker 1: the way we live, work and move. In every episode,
Speaker 1: we'll connect with innovators in areas like artificial intelligence to
Speaker 1: better understand the human centered technology they've developed. As early
Speaker 1: as the discovery of fire and the invention of the wheel,
Speaker 1: technology has always been an innovation to improve people's lives. However,
Speaker 1: sometimes leaders and technology unintentionally exclude those who may deal
Speaker 1: with uncommon issues such as physical immobility, neurodivergence, visual impairments,
Speaker 1: or even old age. While governments usually put systems in
Speaker 1: place to acknowledge and care for these communities, it has
Speaker 1: been the role of technology to create advancements necessary for
Speaker 1: those dealing with disabilities to thrive just as much as
Speaker 1: they abled counterparts. With the revelation of artificial intelligence, there
Speaker 1: are many new advancements that are providing accessibility to these
Speaker 1: communities in the ways we never thought possible until now.
Speaker 1: And I have two experts with me who are leading
Speaker 1: the charge to more accessible future. Lama and Ackmann is
Speaker 1: a visionary leader at the intersection of technology and human experience.
Speaker 1: With a distinguished career spanning academia and industry, Lama has
Speaker 1: consistently pushed the boundaries of technology to enhance our daily
Speaker 1: lives and redefine the way we interact with computers. Her
Speaker 1: innovative work has not only advanced the field of AI,
Speaker 1: but has also paved the way for more intuitive and
Speaker 1: human machine interfaces. As an Intel Fellow and director of
Speaker 1: its Human and AI Systems Research Lab, she leads the
Speaker 1: team defining and executing the research for contextually aware and
Speaker 1: personalized computing, developing sensing systems, algorithms, and applications to make
Speaker 1: it all possible.
Speaker 2: Welcome Lama, thank you very nice to be here.
Speaker 1: We're also joined by Jagadesh Mahendram, a visionary entrepreneur and
Speaker 1: tech innovator who has made significant contributions to the fields
Speaker 1: of artificial intelligence, renewable energy, and sustainable development. With a
Speaker 1: relentless passion for cutting edge technology to address global challenges,
Speaker 1: Jakodesh has emerged as a driving force in shaping a
Speaker 1: more sustainable and inconnected world. Most recently, he joined Camera
Speaker 1: LLC with his founding partners and a team of visually
Speaker 1: impaired volunteers. He uses AI to develop solutions and assistance
Speaker 1: for those dealing with site lost and low visibility. Welcome, Jaggedesh,
Speaker 1: Thank you very much. It's so honor to be here. Okay,
Speaker 1: I've just start with Lama. Lama, how did you get
Speaker 1: your start in tech and AI?
Speaker 2: And I would say that I've been in love with
Speaker 2: tech probably since I was like two years old, you know.
Speaker 2: I've always been into kind of like the latest and
Speaker 2: the greatest technology growing up. But then after I graduated
Speaker 2: from UW Madison, I actually joined Intel out of college
Speaker 2: and then I worked there for a while. I went
Speaker 2: out and did a few startups and then came back
Speaker 2: to Intel specifically focused on that intersection of sensing and
Speaker 2: understanding the world through that to create really compelling technology.
Speaker 2: So that's been kind of like almost like a very
Speaker 2: long career progression that brought me back to what I
Speaker 2: was excited about.
Speaker 1: Excellent, and then in terms of the AI component, how
Speaker 1: did you start to get involved in that?
Speaker 2: Yeah, so early on when I went back to Intel,
Speaker 2: actually in two thousand and three, I started to look at,
Speaker 2: you know, how do we make sense out of the
Speaker 2: world around us? So to be able to understand a
Speaker 2: lot of that sensor data that we were processing, whether
Speaker 2: it's vision or audio or tex or whatever, right, that
Speaker 2: really required work and AI to actually make sense out
Speaker 2: of that data. So that's where it kind of started
Speaker 2: around two thousand and four, and then since then it's
Speaker 2: kind of looking at different ways of intersecting AI and
Speaker 2: HCI to actually bring about really compelling experiences for users
Speaker 2: and helping them perform all sorts of things in their lives.
Speaker 1: Excellent and Jackets, how did you get your start in technology?
Speaker 3: I have a very different story here. I was not
Speaker 3: interested in technology or all. Actually wanted to become a doctor,
Speaker 3: but you know, it's very competitive in India, so I
Speaker 3: didn't really get good ranking, so I couldn't join the
Speaker 3: college that I wanted to join, and the second option
Speaker 3: was engineering, and I chose to do the computer science.
Speaker 3: I think the very best turn out to me is
Speaker 3: good that we're enjoying artificial intelligence and more than doctor.
Speaker 3: I think I'm a bettery engineer than a doctor.
Speaker 1: Oh that kind of makes sense with your I guess
Speaker 1: love of medicine and the type of projects that you've
Speaker 1: come up with. So we'll talk about that in a
Speaker 1: little bit. But one thing I'll go back to Lama
Speaker 1: in terms of AI improving the human experience you've mentioned HI.
Speaker 1: First of all, if you can define for the audience
Speaker 1: what HDI is and also how do you address solutions
Speaker 1: and maybe you could educate me around what's the difference
Speaker 1: between accessibility and accommodation when you're designing a system.
Speaker 2: Yeah, so, first of all, HDI is a human computer interaction,
Speaker 2: So it's really trying to understand how would people directly
Speaker 2: interact with technology. And sometimes that technology is something that's
Speaker 2: actually physical that you're picking something on a computer or whatever.
Speaker 2: But a lot of times, you know, some of the
Speaker 2: work that we really work on is embedding it into
Speaker 2: the environment so that it almost becomes like invisible. And
Speaker 2: that's kind of one of the most interesting things is
Speaker 2: like to really architect for interactions of things that are invisible. Honestly,
Speaker 2: if you think about any technology that you're developing, you
Speaker 2: have to think about how you're making it accessible, how
Speaker 2: the interfaces are accessible, how different people with different types
Speaker 2: of disabilities and abilities can actually interact with your technology
Speaker 2: throughout like the development cycle. In some sense, part of
Speaker 2: what I've really been focused on is creating technologies for
Speaker 2: people who are severely disabled, where you really need very
Speaker 2: different ways of interacting with the technology to enable that
Speaker 2: to happen. Really, that focus specifically on the work with
Speaker 2: ACAT and the workforce even Hawking, has really been about
Speaker 2: how do you get around these on strengths to enable
Speaker 2: people to access the technologies just like all of us.
Speaker 1: Lama mentions Intel's ACAT, which stands for Assistive Context Aware talkit.
Speaker 1: This technology was key in enabling Stephen Hawking's ability to
Speaker 1: continue to communicate and inspire people around the world. Listening
Speaker 1: to Lama speak about the human computer interaction processes, she
Speaker 1: sounds less like a tech person and more like an anthropologist.
Speaker 1: We often think of data and algorithms as being this
Speaker 1: cold and personal assessment of people. But Lama has such
Speaker 1: a passion for her programs, it makes me wonder just
Speaker 1: how impactful that passion is to the way AI tools
Speaker 1: interpret how to assist us. While she has spent so
Speaker 1: much time learning how to program and manage computers, it
Speaker 1: seems her real passion is in trying to understand humanity.
Speaker 2: My passion has really been focused on how do we
Speaker 2: bring more equity with technology. The work towards specifically extreme
Speaker 2: disability really came about from my interaction with Professor Hawking.
Speaker 2: So before that, a lot of the work that I
Speaker 2: had focused on in terms of accessibility is really bridging
Speaker 2: where people's needs were as they're doing different aspects of
Speaker 2: their lives. Right you're driving, for example, how can that
Speaker 2: be contextually aware so it can help support you without
Speaker 2: assuming that you have all of your abilities there. But
Speaker 2: once I started working with Professor Stephen Hawking, it became
Speaker 2: very obvious to me that to bridge that extreme disability
Speaker 2: you really have to think very differently about how technology
Speaker 2: comes in. And that's what really got me excited about
Speaker 2: that work.
Speaker 1: Okay, and in terms of the involvement you had with
Speaker 1: Professor Hawking's technology to help him interact with the world,
Speaker 1: What were the areas that you looked at?
Speaker 2: The lab I lead is actually a multi disciplinary lab, right,
Speaker 2: so we bring social science, design, and AI together. So
Speaker 2: the first place you start is we needed to understand
Speaker 2: how Stephen interacts with the world, what he is trying
Speaker 2: to accomplish, and where are his bottomnecks in terms of
Speaker 2: being able to do that with existing technology that he
Speaker 2: was using. So there was a lot of observation to
Speaker 2: try to understand how do we define the problem and
Speaker 2: from there for people who are not aware of this, right,
Speaker 2: Professor Hawking really didn't have an ability to speak, and
Speaker 2: he didn't really have an ability to move, so he
Speaker 2: couldn't really utilize many of the technologies that are available.
Speaker 2: You couldn't do, for example, ASR where he could speak
Speaker 2: and then the computer could be controlled by speech, Nor
Speaker 2: could he type because he had no control over his hands.
Speaker 2: So then we started to basically look at if we
Speaker 2: really had a very very tiny signal, and in this
Speaker 2: specific case for Professor Hawking, it was actually his ability
Speaker 2: to move his cheek. Can we get access to that
Speaker 2: one signal and then turn that into a complete access
Speaker 2: for his whole machine? And then we went onto that
Speaker 2: path of essentially building a software platform and a sensing
Speaker 2: subsystem that allowed for that to happen. All he can
Speaker 2: do is confirm something with the movement of a cheek,
Speaker 2: and now he can type, he can email, he can
Speaker 2: serve the web, he can give lectures, he could do all.
Speaker 1: Of that in What year was that that you were
Speaker 1: working on?
Speaker 2: So we started our interaction with Stephen and twenty eleven
Speaker 2: and it kind of lasted throughout his life until he
Speaker 2: passed away, which was twenty eighteen. So we after a
Speaker 2: couple of years we were able to put together a
Speaker 2: system that he could use that he could switch to,
Speaker 2: and then over the years we just continued to enhance
Speaker 2: it and add more capabilities. We open sourced it so
Speaker 2: that we could take it into the world.
Speaker 1: And yeah, that was my next question in terms of
Speaker 1: the technology that was developed. Have you seen it applied
Speaker 1: more broadly to others.
Speaker 2: Yeah, And initially we were hoping that we could find
Speaker 2: some technology out there we could take and modify slightly
Speaker 2: so that he could use it. And then after being
Speaker 2: proven wrong, we then went onto this path to go
Speaker 2: and develop something from scratch. But from the get go
Speaker 2: our goal was to develop it so that it could
Speaker 2: support a lot of different users and be a platform
Speaker 2: for developers to build on top of, because we realized
Speaker 2: that there was that gap in what existed out there
Speaker 2: in the open world. And Stephen was a huge contributor
Speaker 2: to this project, right he he you know, he was
Speaker 2: a designer, he was a validator, he was you know,
Speaker 2: he gave a lot of his insights. So throughout all
Speaker 2: of this he was really focused on ensuring that that
Speaker 2: actually went to open source because you know, people reached
Speaker 2: out to him all the time because he was, you know,
Speaker 2: an own figure with that extreme disability, and everybody was
Speaker 2: asking him, like, what technology is available to us to
Speaker 2: actually use. So he's been like really focused quite a
Speaker 2: bit on making that available to the world.
Speaker 1: You can really sense how dedicated Lama is to helping
Speaker 1: those with disabilities communicate with others. However, talking is just
Speaker 1: one way we communicate, and moreover, there are a combination
Speaker 1: of ways that we engage and interact with our environments.
Speaker 1: As a way to help people that may struggle with
Speaker 1: another sense is our other guest Jagged Dish originally designing
Speaker 1: a backpack that uses AI to help guide the blind.
Speaker 1: His project expanded into really dissecting what it means to
Speaker 1: be visually impaired. Lama and Jagged Dish both have different
Speaker 1: approaches to their missions. The work compliments each other so well.
Speaker 1: Jagsh I'd like to get you into conversation now, in
Speaker 1: particular the AI powered backpack that has been developed by
Speaker 1: yourself and others. Can you just tell me a little
Speaker 1: bit about I guess the genesis of that idea.
Speaker 3: I've always wanted to do something using the technology that
Speaker 3: can help the society in what way or the other.
Speaker 3: And when it came to Masters in twenty thirteen, one
Speaker 3: of the first things that occurred to me was like,
Speaker 3: you know, we should use EI and use a bunch
Speaker 3: of sensors to help the usually impaired see the world,
Speaker 3: like how sighted people see. And one of the primary
Speaker 3: visions that I used to occur to me was when
Speaker 3: somebody is standing in public places like buz stop, there
Speaker 3: should be a solution in such a way that the
Speaker 3: person who is blind should get totally unnoticed. And around
Speaker 3: that time the technology was not as good as how
Speaker 3: it is now. The real inspiration occurred to me when
Speaker 3: I met my friend. The day when I met her,
Speaker 3: she had a black mark in her face, and I
Speaker 3: was like, you know, what happened to your face? And
Speaker 3: she's usually impair and she was saying, as she was
Speaker 3: walking outside in the sidewalk, she ran into a tree
Speaker 3: branch and then that left a mark in her face.
Speaker 3: And that was such an ironical for me because by
Speaker 3: then I was already a perception engineer, teaching robots to
Speaker 3: see things, you know, do complex us. But at the
Speaker 3: same time, there are so many people who cannot see
Speaker 3: right and that sort of spart my desire to work
Speaker 3: on this project sooner than later. Around the same time,
Speaker 3: this competition of Open Sea Special ai I was going on,
Speaker 3: sponsored by Intel, and I submitted this idea and the
Speaker 3: project ended up winning the first price. And this friend
Speaker 3: has been helping you throughout how to develop a system
Speaker 3: that is more user friendly and actually solves important use cases.
Speaker 3: And through this competition received a lot of attention, and
Speaker 3: this is when we started to think, you know, we
Speaker 3: should probably you know, get incorporated and try to create
Speaker 3: a full fledged open source system so that anybody in
Speaker 3: the world can use it and help in improving the
Speaker 3: lives of the visually impaired. Currently, we are supported by
Speaker 3: Intel's irt A program Intel Rise Technological Initiative program, and
Speaker 3: we are receiving an in collaboration with Accenture. Through this partnership,
Speaker 3: you're able to gain a lot of support both on
Speaker 3: the technical and non technical side. And soon we will
Speaker 3: be releasing our improved version of the system, which we
Speaker 3: call as Phoenix in a few months.
Speaker 1: Okay, excellent, looking forward to it. And can you tell
Speaker 1: me what I've seen a little bit of a video
Speaker 1: on it where you've got a backpack. Maybe you could
Speaker 1: just describe some of the main system elements.
Speaker 3: Yeah, the physical system mainly consists of a backpack that
Speaker 3: has Intel Look with a couple of new compute sticks
Speaker 3: and this is the sort of the compute resource. And
Speaker 3: at the front we have a camera. It's Obi camera
Speaker 3: that is is put in the front and connect it
Speaker 3: to the system behind and whatever this sensor collects the data.
Speaker 3: We run some AA processing behind using deep learning techniques
Speaker 3: and the system will infer useful information about the environment
Speaker 3: and update the user such as where are the obstacles
Speaker 3: and what are the common objects seen in the scenario,
Speaker 3: what are the moving objects, what are the traffic conditions?
Speaker 3: And more similar features for communicating there is audio interface
Speaker 3: through bluetooth headphones, and we're also working on a haptic
Speaker 3: band to communicate the same sort of information in form
Speaker 3: of vibrations through tacktail information.
Speaker 1: Lama was just wondering if you had any comments or
Speaker 1: thoughts on this AI backpack.
Speaker 2: I mean, it's a fantastic idea, and you know, if
Speaker 2: you think about what is actually now possible with perception
Speaker 2: and AI, I mean, it's it's just kind of like
Speaker 2: the most natural thing to do to actually empower users
Speaker 2: with such a capability that are vision impaired. I was
Speaker 2: actually also quite intrigued by the haptic aspect of what
Speaker 2: you mentioned, and I think it's something that tends to
Speaker 2: be un they're utilized, but really kind of a natural
Speaker 2: thing for this type of application, especially if you're trying
Speaker 2: to kind of guide somebody in a direction. So I
Speaker 2: was wondering maybe you can say a few words about that.
Speaker 2: I was really intrigued by that.
Speaker 3: Yeah, So if the first prototype contained mainly the audio interface,
Speaker 3: all the information is actually shared via the wireless headphones
Speaker 3: and not all the users prefer that main reason is
Speaker 3: because they usually impair people rely on audio cues when
Speaker 3: they're wearing earphones. We are sort of blocking a lot
Speaker 3: of environmental cues, which is why we wanted to introduce
Speaker 3: another modality for user interface, which is haptic bands. Basically,
Speaker 3: using a combination of motors and vibration patterns, we can
Speaker 3: communicate tons of information just using few motors, like even
Speaker 3: less than ten morrors. And the current prototype that we're
Speaker 3: working on is pretty simple version. It can be put
Speaker 3: on the wrist and this can communicate potentially hundreds of
Speaker 3: combinations of vibrations, and at some point we're really aiming
Speaker 3: for a set of where we can communicate pretty much
Speaker 3: everything the system sees through the happic vibrations. If a
Speaker 3: user prefers completely one hundred percent haptic bands, that is
Speaker 3: something that we are targeting for. At the same time,
Speaker 3: some users might prefer, you know what, I want this
Speaker 3: sort of information to be communicated via audio and some
Speaker 3: sort of information with the haptics. We're also are working
Speaker 3: with the combination of system as well, but having hapic
Speaker 3: bands in a solution like this opens a sort of
Speaker 3: a different dimension for the users here, especially we're visually impaired.
Speaker 1: What Jagadish hints at with his explanation of haptic bands
Speaker 1: versus audio interface is a very fascinating, multi pronged approach
Speaker 1: to the solution. In technology terms, haptics is all about
Speaker 1: how your device interacts with you through touch. Think of
Speaker 1: the times when your phone vibrates in your pocket, or
Speaker 1: when you play a video game and the controller shakes
Speaker 1: in response to you taking damage from the endgame boss. Oftentimes,
Speaker 1: in developing solutions for disabilities, there is a one size
Speaker 1: fits all approach that seeks to do an adequate job
Speaker 1: for the most number of people. This strategy fails to
Speaker 1: take into account the nuances of the human experience in
Speaker 1: the same way that some people are audio learners while
Speaker 1: others are visual. When it comes to aiding someone with
Speaker 1: a disability, it is important to consider what methods complement
Speaker 1: their strengths and experiences. The beauty of how jagger Dish
Speaker 1: seeks to develop this AI tool is that it is
Speaker 1: constantly studying and creating more specialized options for the users,
Speaker 1: from audio to haptics. It has the potential to grow
Speaker 1: in a number of ways to accommodate the visually impaired
Speaker 1: ways we never thought to supplement them, and maybe these
Speaker 1: developments will even have an impact on those with perfect sight.
Speaker 1: Leans into the human computer interface component that Lama mentioned earlier,
Speaker 1: the constant study and assessment of how people will actually
Speaker 1: use the tools. Given you're listening to technically Speaking an
Speaker 1: Intel podcast will be right back. Welcome back to technically
Speaker 1: speaking an Intel podcast. I'd just like to get more
Speaker 1: broadly into Intel and it's AI efforts now, Jaged you
Speaker 1: have a partnership with Intel. You've mentioned it before, how
Speaker 1: you're working with Intel and how they've come to the party,
Speaker 1: so to speak. What's it like working with their team
Speaker 1: in terms of their support and assistance they've given you.
Speaker 1: It's fantastic. The amount of exposure and the support that
Speaker 1: we've received from Intel is really amazing. What we admire
Speaker 1: about Intel is how open they are in developing the
Speaker 1: solutions for accessibility, and they have a dedicated team who's
Speaker 1: purely working on solutions like this. And we also got
Speaker 1: opportunity to look into the projects that Lama's team has
Speaker 1: been working on. They're simply superb. I think these solutions
Speaker 1: like this are transformative and it's going to change lives
Speaker 1: for people. And in terms of the support that we've received,
Speaker 1: they have been helping us on many aspects all the
Speaker 1: way from helping with putting up a process training the
Speaker 1: model assets, you know, creating a platform for training models,
Speaker 1: and also sharing the connections, and also with funding. So
Speaker 1: a lot of the features that is going to come
Speaker 1: as part of Phoenix is coming out of the IrDA project,
Speaker 1: and the sort of feedbacks that would risk in improving
Speaker 1: the solution is something that we don't get outset easily.
Speaker 2: Yeah, and it's one of the things that I believe
Speaker 2: we're really all about at Intel, right If you look
Speaker 2: at our mission, it's really enriched the life of every
Speaker 2: person on the planet, and every person, right, not just
Speaker 2: able people. So it's really wonderful that you're seeing that
Speaker 2: support and the diversity of the type of platforms and
Speaker 2: solutions that we have, right. So I'm really just very
Speaker 2: heartened by what you said, Drakhandesh. One of the things
Speaker 2: maybe that is a top of mind project something called Omnibridge,
Speaker 2: and Omnibridge is essentially a software that is meant to
Speaker 2: bridge again the silence gap, but for people who are
Speaker 2: hearing impaired, so that you know, essentially you're translating in
Speaker 2: and out of like sign language, so you know, people
Speaker 2: can sign into their PC and then the PC can
Speaker 2: actually translate that into language on the other end, and
Speaker 2: then vice versa. Right, So it's like, you know, what
Speaker 2: you're really enabling again is to enable people in their
Speaker 2: everyday life life to actually be able to do that.
Speaker 2: And to be able to do that, you need a
Speaker 2: lot of the AI support and AI compute on these platforms.
Speaker 2: So one of the reasons again what I was saying,
Speaker 2: it's really nice to see it at these platforms and
Speaker 2: at the lowest cost that you can actually bring it.
Speaker 2: You start to really democratize AI in ways that really
Speaker 2: improve people's lives.
Speaker 1: Yeah, for me, I mean one of the key things
Speaker 1: you've just said is democratizing technology, and I think that's
Speaker 1: the real power of it is. Yes, we can have
Speaker 1: those really fancy solutions that Professor Hawking has, but for me,
Speaker 1: it's about trying to get that cost down so that
Speaker 1: it makes it so much easier for people to use.
Speaker 2: So actually, just as a correction, so Professor Hawking didn't
Speaker 2: have a fancy system, I was actually at PC with
Speaker 2: a very lightweight sensor and in fact, like a big
Speaker 2: part of what we've been really trying to do with
Speaker 2: BCI is also democratize that because the problem with BCI
Speaker 2: is if you want something with really high fidelity, you're
Speaker 2: paying fifteen to two thousand dollars on a headset versus
Speaker 2: what we're really trying to do is like use OpenBCI,
Speaker 2: so it's you know, a really low cost, but you know,
Speaker 2: compensate for the fidelity constraints with a lot of machine learning.
Speaker 1: Okay, great, and jacket ashly did say it was relatively
Speaker 1: low cost. Is that one of the primary motivating factors
Speaker 1: for you? And how do you go about designing systems
Speaker 1: to try and get that cost down.
Speaker 3: Absolutely, it's a major restricting factor. Just a bit of context,
Speaker 3: The unemployment rate in the visually impaired people community is
Speaker 3: extremely high. I think it's more than sixty percent, so
Speaker 3: it's hard for them to afford any product that is expensive.
Speaker 3: And this is something that we want to change by
Speaker 3: one making it completely open source, so that anybody in
Speaker 3: the world they can just if they have the technical skills,
Speaker 3: they can just assemble the system and they can get
Speaker 3: the system. If not, we can help them assemble the system.
Speaker 3: The complete solution is going to be open source. Two
Speaker 3: is building the product using the hardware systems that are cheap.
Speaker 3: At the same time, that are efficient, and that's where
Speaker 3: products like Intelook stands apart one because it has very
Speaker 3: good capability for running a lot of models in bartle
Speaker 3: and also using accelerators like neural computer stick. So things
Speaker 3: like that help us in shrinking the form factor and
Speaker 3: also the cost quite a bit. And at the same time,
Speaker 3: at the software design level, if you are putting in
Speaker 3: a modular based design, where if somebody wants to use
Speaker 3: a cheaper sensor, they could plug in a different sensor.
Speaker 3: The rest of the robotics or stack will remain intact
Speaker 3: as far as they take care of the sensor obstruction layer.
Speaker 3: And same thing goes for probably for haptic interface, probably
Speaker 3: audio interface, and potentially for computer interface. So we want
Speaker 3: to modularize it as much as possible and shrink the
Speaker 3: cost as much as possible.
Speaker 1: Jagadish mentions something I had never really considered, which is
Speaker 1: the difficulty in finding gainful employment for those with visual impairments.
Speaker 1: In the US and other developed nations, there are protocols
Speaker 1: to provide reasonable accommodations to workers with disabilities, but globally
Speaker 1: that has yet to become a common practice. With an
Speaker 1: AI tool such as Jagadees being open source. It really
Speaker 1: helps move the needle in terms of what those with
Speaker 1: visual impairments can do for themselves. Lama also mentions BCI,
Speaker 1: or brain computer interfaces. Most brain computer interfaces use electrical
Speaker 1: energy of the brain to directly interface with computers or machines.
Speaker 1: The best way to imagine BCI is the character Cyborg
Speaker 1: from the Teen Titan series, where he developed superpowers from
Speaker 1: interfacing computing technology with his biological self. I'm wondering what
Speaker 1: accommodations are considered when the user has ADHD or some
Speaker 1: other form of cognitive processing disorder.
Speaker 2: So we've been looking specifically at utilizing BCI for communication
Speaker 2: for locked in patients, right, And really, you don't want
Speaker 2: to use BCI for communication unless you have to, because
Speaker 2: it's not i mean, unless you're actually have something that's
Speaker 2: implanted in your brain. If you're going outside of the skull,
Speaker 2: you have a very very noisy signal. So that's in
Speaker 2: some sense you can think of it as a last resort. However,
Speaker 2: what you just mentioned is something very different, right, which
Speaker 2: is utilizing BCI as another sensing modality for all sorts
Speaker 2: of other inferences, not to communicate your intention, but to
Speaker 2: actually understand your state, and that is something that is
Speaker 2: you know, yes, can be totally utilized for understanding, for example,
Speaker 2: things like emotional state and concentration and focus and all
Speaker 2: sorts of things like that that can help in cases
Speaker 2: where you have people with autism, for example, and they're
Speaker 2: having a hard time expressing emotional state as it's actually
Speaker 2: getting worse.
Speaker 1: Right.
Speaker 2: There has been actually quite a lot of interesting research
Speaker 2: out of Jojia Tech, for example, specifically looking at that
Speaker 2: as an interesting modality for these type of settings.
Speaker 1: In terms of other individuals and organizations contributing, you've mentioned
Speaker 1: both of you mentioned the open source initiative that Intel's pushing.
Speaker 1: If individuals and organizations want to be involved, what's the
Speaker 1: best way for them to get in and start contributing.
Speaker 2: So basically with ACAT, we have essentially it's an open
Speaker 2: source project, right, and it's open to developers. We have
Speaker 2: different people contributing all sorts of different things, right. I mean,
Speaker 2: for example, we've seen a lot of interest in having
Speaker 2: ACAT beyond in different languages for people around the world, Right,
Speaker 2: So we have a way for having people easily contribute
Speaker 2: to extend it to other languages. As an example, extending
Speaker 2: it to other sensing modalities and so on, so you
Speaker 2: can go through that project and then just kind of
Speaker 2: communicate and submit what you want and communicate with us
Speaker 2: as the people who are still kind of overseeing the project.
Speaker 2: There are also like specific groups that we work with
Speaker 2: because we're trying to also kind of get access to
Speaker 2: users that we can test that technology with. So for example,
Speaker 2: you know the M and D or the ALS groups
Speaker 2: and things like that. So depending on usually some of
Speaker 2: these groups have access to a lot of the different
Speaker 2: solutions and open source systems that exist there. So that
Speaker 2: also is a way I mean not necessarily just for ACAT,
Speaker 2: but more broadly.
Speaker 3: We are seeing the very strong trend of a lot
Speaker 3: of projects being open sourced, and because of this trend,
Speaker 3: we're seeing a lot of powerful projects being democratized and
Speaker 3: reaching people much easily than before. In fact, a lot
Speaker 3: of companies are actually following this model, starting to switch
Speaker 3: from a different model to open sourcing model, which is
Speaker 3: fantastic for the community. It's just fantastic for the world. However,
Speaker 3: there are certain things needs to be considered when developing
Speaker 3: open source solution. One of the most important things is
Speaker 3: how an open source project is defined, how can it
Speaker 3: evolve by itself at some point. Initiatively there is going
Speaker 3: to be primary contributors, but at some point there is
Speaker 3: going to be a lot of people. You're going to
Speaker 3: get contribution from all over the world, and this can
Speaker 3: be both good and bad. If the response is very high,
Speaker 3: then the initial contributors cannot handle it, right, it might
Speaker 3: end up pretty damaging, right, But at the same time,
Speaker 3: you need those responses, So it's important to know that
Speaker 3: balance and also come up with how do we address
Speaker 3: this as a process in general?
Speaker 1: Right?
Speaker 3: How can somebody contribue, but how can somebody create a
Speaker 3: pr It's going to be completely democratized and there will
Speaker 3: be more reviewers distributed throughout the world.
Speaker 2: One of the things that I'm really happy to see
Speaker 2: is really the amount of contribution in the open source
Speaker 2: on all sorts of AI capabilities and language models, and
Speaker 2: which really I think is enabling a lot of democratization
Speaker 2: of AI, specifically to all of these different usages. Right,
Speaker 2: because if you think about a sist of computing in
Speaker 2: some sense, in many cases you're trying to compensate for
Speaker 2: some sort of a sense impairment. Right, So if you're
Speaker 2: able to actually use AI to help extract that sense
Speaker 2: automatically from the world. Having access to that democratization in
Speaker 2: AI models and algorithms is something that is really transformational
Speaker 2: for this space. And if I remember, for example, like
Speaker 2: in the past, right even getting something access to something
Speaker 2: like an ASR was really hard to do right in
Speaker 2: the open source, at least the level of quality that
Speaker 2: you would see. But now lately, because of that quick movement,
Speaker 2: you're seeing a lot of capability in the open source
Speaker 2: that actually rivals that of the really you know, big companies,
Speaker 2: which is I think is absolutely transformational.
Speaker 1: Yeah, that's great, no question for both of you. Are
Speaker 1: start with jaggedesh. You know, we're seeing AI being used
Speaker 1: for accessibility efforts. Looking forward ten years, what's the number
Speaker 1: one area which you would want AI to help in
Speaker 1: this industry.
Speaker 3: I'd be really pleased to see a system that is
Speaker 3: really small that somebody can put in like a glass
Speaker 3: or any firm, that goes totally unnoticed and it provides
Speaker 3: all the capabilities of human eye. I think that'll be fantastic,
Speaker 3: And same thing goes for other forms of disabilities. I
Speaker 3: think that will be fantastic to see and in tenuous timeline,
Speaker 3: I think it might be possible.
Speaker 2: My number one area that I want to see solved,
Speaker 2: not necessarily in a sist of computing, but actually climate change.
Speaker 2: That's where I think, like we all need this otherwise
Speaker 2: I'm not sure we're going to have a world to
Speaker 2: actually do anything else. And in the area of asis
Speaker 2: of computing, it's really what I was saying earlier, which
Speaker 2: is I envision being able to compensate for every single
Speaker 2: sense that the human is missing, and that, to Jaggediesh's point,
Speaker 2: is only going to be possible if that is meeting
Speaker 2: people where there are in the world, which means they
Speaker 2: have to be sustainable, they have to be extremely power efficient,
Speaker 2: they need to be robust enough to everything that it
Speaker 2: hasn't seen in the world right, so, which is really
Speaker 2: not necessarily where things are today, but you know, given
Speaker 2: that appid improvement, I would really hope that that's where
Speaker 2: we would be in ten years from now.
Speaker 1: Excellent. Okay, thank you very much, thank you, thank you.
Speaker 1: I would like to thank my guests Jaggedish Mahindra and
Speaker 1: Lama Nachman for joining me on this episode of Technically Speaking,
Speaker 1: an Intel podcast. I really enjoyed this conversation with Jagged
Speaker 1: Ash and Lama. I love being able to delve into
Speaker 1: the motivations of the why, but also the how. You
Speaker 1: heard from Jaggedesh and the story of his visually impaired
Speaker 1: friend being struck by a tree branch, and that was
Speaker 1: the seed for his idea for an AI assistant backpack.
Speaker 1: For me, this is the true technological empowerment, the ability
Speaker 1: for individuals to use their skills and talent to make
Speaker 1: a difference, taking action rather than just talking about it.
Speaker 1: These are the true innovators. It was great to hear
Speaker 1: of Lama's work with Professor Stephen Hawking and the context
Speaker 1: of where system her team developed. What is so pleasing
Speaker 1: to me was that it wasn't a Rolls Royce design,
Speaker 1: but rather an elegant yet simple system of sensors connected
Speaker 1: to a PC to allow Professor Hawking to interact and
Speaker 1: communicate with others. Because of this relatively inexpensive solution, it
Speaker 1: can be used by a wider range of people. This
Speaker 1: is what democratization of technology does for the world. I
Speaker 1: hope that Lama and Jaggedish's stories inspire you to take
Speaker 1: the leap and contribute to improving the lives of people,
Speaker 1: regardless of their background. Please join us on Tuesday, November
Speaker 1: fourteenth for the next episode of Technically Speaking, an Intel podcast.
Speaker 1: Technically Speaking was produced by Ruby Studios from iHeartRadio in
Speaker 1: partnership with Intel, and hosted by me Graham Class. Our
Speaker 1: executive producer is Molly Sosher, our EP of Post Production
Speaker 1: is James Foster, and our Supervising producer is Nikair Swinton.
Speaker 1: This episode was edited by Sierra Spreen and written and
Speaker 1: produced by Tyree Rush.